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• Policy and Social Care Move Fast: How…

Policy and Social Care Move Fast: How Rapid Qualitative Methods Can Help Researchers Match Their Pace

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The field of social care integration, which refers to the study and implementation of clinically based programs to address the social needs of patients and families, is advancing at an increasingly rapid pace. This acceleration, driven by heightened need post-pandemic as well as mandates at the state and federal levels for health systems to implement screening and referral programs, has increased the urgency for high-quality evidence to support policy decisions about the delivery of social care—in other words, how health systems identify and address social needs, like access to healthy food and safe housing.  

Qualitative research is particularly useful in guiding social care integration as it can shed light on the patient or caregiver experience of participating in social care interventions, barriers to getting help that should be addressed, and appropriate next steps from the perspective of those directly impacted.

However, traditional qualitative data analysis can be time consuming, and evidence-based solutions for addressing families’ social needs from the clinical setting are needed in the short term. In this post, I’ll share how we adapted and applied rapid qualitative methods to a social care-focused study as an example of how this approach can be used to inform social care integration in real time.

Integrating a Rapid Research Approach

The Socially Equitable Care by Understanding Resource Engagement ( SECURE ) study is a mixed method pragmatic trial aimed at understanding how best to increase family-level engagement with social resources from the pediatric health care setting. Caregivers in the study were randomized to complete one of three different social assessments (surveys asking about their social circumstances and/or desire for social resources) before receiving a resource map on their personal smartphone where, if interested, they could search for community resources in their neighborhood. Caregivers also had the option of talking to our study-specific resource navigator to receive additional support finding resources.

The overall goal of the qualitative component of the study is to capture caregivers’ preferences and experiences receiving social care through SECURE. Our traditional qualitative protocol involved transcribing caregiver interviews verbatim, coding transcripts and conducting thematic analysis. Recognizing the need for implementation-oriented results on a fast timeline, our team explored rapid qualitative methodologies to supplement the traditional approach. The rapid methods we chose were derived from existing literature on rapid qualitative approaches, which were then adapted to suit our study’s protocol and the social care field in general.

In our rapid approach, interviewers took notes using a structured template during or immediately after each caregiver interview. The template was designed to capture the data most salient to social care integration efforts such as caregiver’s likes, dislikes and preferences about receiving social care at their child’s doctor’s office. Then, content from the templates was transposed onto an analytic matrix, where we compared data across participants to identify themes. While we explored the full range of themes that emerged from our caregiver interviews in traditional qualitative analysis, we wanted to be sure that rapid analysis focused on findings that would be most applicable to social care integration efforts so the results could inform social care policy at Children’s Hospital of Philadelphia (CHOP) and elsewhere in real time. For example, what parts of participating in SECURE were helpful for caregivers? Did anything make them uncomfortable?

To ensure that our rapid approach produced results in line with those generated through traditional methods, we analyzed ten of our interviews using both traditional and rapid methods and compared the results. This analysis yielded a 92.8% theme match—meaning the two qualitative methods yielded largely the same themes. This builds upon previous literature, indicating that rapid analysis can be an effective tool in capturing implementation-oriented themes from qualitative data.

How the SECURE Study Can Inform Future Research Efforts

Our rapid qualitative methods allowed us to effectively adapt and respond to the quickly evolving landscape of social care integration, even before we had the full study results. I personally saw this first-hand while working with the SECURE team in 2023 conducting caregiver interviews. For example, we were able to inform hospital efforts in response to a recent insurance requirement of health systems to share caregivers' responses to social screening questions. We successfully gathered patients’ feedback on this new requirement and shared this information and suggestions for what CHOP could do to make caregivers feel more comfortable answering social assessment questions.

While not intended to replace traditional qualitative analysis, being able to produce actionable qualitative findings in a timely manner through rapid methods has allowed SECURE findings to help shape social care interventions at CHOP and beyond in real time.

Our hope is that other researchers in social care who face time pressures may find similar rapid qualitative methods as a useful and effective approach to adapt to the dynamic nature of the field and generate family-centered solutions faster than would otherwise be possible.

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Making Sense of Research in Nursing, Health and Social Care

• Pam Moule - University of the West of England, UK
• Description

What is research and how does it work in the context of nursing, health and social care?

Now in its 7 th  edition, this introductory guide provides you with a concise overview of the different research methods and terminology that you will come across when undertaking research in any course related to nursing, health and social care. The book’s easy-to-follow structure takes you from research novice to confident researcher, helping you to make sense of research and understand how it is implemented in healthcare practice.

The new edition includes:

• Updates in line with the 2018 NMC standards, with more information on the impact of GDPR, consent and vulnerable groups, Personal and Public Involvement (PPI), and work-based projects.
• Improved case examples of real research, with more on group work, poster presentations, research output and dissemination, literature reviews, and dissertations.
• Upgraded activities that include reflective exercises, critical appraisal tools, a dissemination plan, and a glossary, all in the book.

This is essential reading for undergraduate and postgraduate students within the health and therapy professions, nurses, midwives, physiotherapists, radiographers, occupational therapists, speech and language therapists, and paramedics.

See what’s new to this edition by selecting the Features tab on this page. Should you need additional information or have questions regarding the HEOA information provided for this title, including what is new to this edition, please email [email protected] . Please include your name, contact information, and the name of the title for which you would like more information. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html .

For assistance with your order: Please email us at [email protected] or connect with your SAGE representative.

SAGE 2455 Teller Road Thousand Oaks, CA 91320 www.sagepub.com

Some books reach their silver anniversary and start to look dated and lose their relevancy. Making Sense of Research in Nursing, Health and Social Care however, has renewed and refreshed at each edition and maintains its applicability for today’s health and social care professionals. 

One of the marks of a good textbook is its ability to appeal to readers across professional boundaries and with varying levels of experience in the topic at hand; Moule achieves this both engaging those new to research as well as providing different insights for those with more research knowledge and experience. One of the stated intentions of the book is to make research interesting and in so doing to help practitioners in their adoption of research and evidenced based practice within their work. Moule achieves this with the use of an accessible writing style which is at once both engaging and thought provoking. I would recommend this book as a must have on the shelf for any student of health and social care be they a first year undergraduate or a more experienced individual engaging in post graduate studies.

Evidence-based practice is crucial for the modern healthcare practitioner. Students can often shy away from the topic of research thinking that the subject is too complex for them. However, the benefits of this book in guiding them through the subject include: easy to read short sections with headings, clear key messages at the beginning and end of each chapter and links to current, credible sources of evidence to expand their reading further. Some students find it difficult to seek out credible secondary sources and this book gives them links to guidelines and reports which would be appropriate to inform their assignment work.

Books about the research process are not rare but few authors can clarify the basics with such ease like Pam Moule. This textbook is easy-to-read, speaks to the research novice in accessible language, and leaves the reader feeling well-initiated in research literacy. Without hesitation I would endorse this textbook for undergraduate health and social care students who will draw from it from the first term of study to the last. The chapters take the reader on a journey through critical reading right through to the fundamentals of research project design, and instill habits of systematic thought and process in all elements of research. Included are a number of helpful links and templates as well as examples to aid visualization of new concepts. This book is the perfect springboard to launch health and social care students into evidence-informed practice without overwhelming and scaring them off from what can undoubtedly become a more complex topic with further reading.

This is an informative and easy to read book, which introduces the students to research and directs them through the research process. I have used previous editions of this book and have it on the reading list for research modules I teach to both undergraduate and postgraduate students. The use of practice examples and scenarios clearly demonstrate research in action in health and social care. This new 7th edition will be a valuable addition to the reading list on my modules.

The previous editions of this book have been a steadfast resource and the ‘go to book’ for all levels of paramedic students studying at undergraduate level. The seventh edition of this book does not disappoint and will be the new ‘go to’ edition for current students who want to understand how to make sense of research in health and social care. The format of the book makes it easy to access the information making it a valuable and informative resource for all students in healthcare settings, and especially useful when undertaking a final project/dissertation.

This book is an excellent text that will provide an invaluable resource to health and social care practitioners who are new to research or those undertaking projects. The detailed discussion of the research process is written in an informative and authoritative way that informs the reader and makes the research process and terminology accessible.

Excellent - I will be directing students to this resource to support learning for enquiries into health and social care research.

Such a clear and easy to read text. A seminal volume!

Easy to understand for L5 students, applied examples and clear explanations.

this book is clearly written, easy to read and easy to understand

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• Open access
• Published: 18 April 2024

Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research

• James Shaw 1 , 13 ,
• Joseph Ali 2 , 3 ,
• Caesar A. Atuire 4 , 5 ,
• Phaik Yeong Cheah 6 ,
• Armando Guio Español 7 ,
• Judy Wawira Gichoya 8 ,
• Adrienne Hunt 9 ,
• Daudi Jjingo 10 ,
• Katherine Littler 9 ,
• Daniela Paolotti 11 &
• Effy Vayena 12  

BMC Medical Ethics volume  25 , Article number:  46 ( 2024 ) Cite this article

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The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice. In this paper we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, research ethics committee members and other actors to engage with challenges and opportunities specifically related to research ethics. In 2022 the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations, 16 governance presentations, and a series of small group and large group discussions. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. In this paper, we highlight central insights arising from GFBR 2022.

We describe the significance of four thematic insights arising from the forum: (1) Appropriateness of building AI, (2) Transferability of AI systems, (3) Accountability for AI decision-making and outcomes, and (4) Individual consent. We then describe eight recommendations for governance leaders to enhance the ethical governance of AI in global health research, addressing issues such as AI impact assessments, environmental values, and fair partnerships.

Conclusions

The 2022 Global Forum on Bioethics in Research illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

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Introduction

The ethical governance of Artificial Intelligence (AI) in health care and public health continues to be an urgent issue for attention in policy, research, and practice [ 1 , 2 , 3 ]. Beyond the growing number of AI applications being implemented in health care, capabilities of AI models such as Large Language Models (LLMs) expand the potential reach and significance of AI technologies across health-related fields [ 4 , 5 ]. Discussion about effective, ethical governance of AI technologies has spanned a range of governance approaches, including government regulation, organizational decision-making, professional self-regulation, and research ethics review [ 6 , 7 , 8 ]. In this paper, we report on central themes related to challenges and strategies for promoting ethics in research involving AI in global health research, arising from the Global Forum on Bioethics in Research (GFBR), held in Cape Town, South Africa in November 2022. Although applications of AI for research, health care, and public health are diverse and advancing rapidly, the insights generated at the forum remain highly relevant from a global health perspective. After summarizing important context for work in this domain, we highlight categories of ethical issues emphasized at the forum for attention from a research ethics perspective internationally. We then outline strategies proposed for research, innovation, and governance to support more ethical AI for global health.

In this paper, we adopt the definition of AI systems provided by the Organization for Economic Cooperation and Development (OECD) as our starting point. Their definition states that an AI system is “a machine-based system that can, for a given set of human-defined objectives, make predictions, recommendations, or decisions influencing real or virtual environments. AI systems are designed to operate with varying levels of autonomy” [ 9 ]. The conceptualization of an algorithm as helping to constitute an AI system, along with hardware, other elements of software, and a particular context of use, illustrates the wide variety of ways in which AI can be applied. We have found it useful to differentiate applications of AI in research as those classified as “AI systems for discovery” and “AI systems for intervention”. An AI system for discovery is one that is intended to generate new knowledge, for example in drug discovery or public health research in which researchers are seeking potential targets for intervention, innovation, or further research. An AI system for intervention is one that directly contributes to enacting an intervention in a particular context, for example informing decision-making at the point of care or assisting with accuracy in a surgical procedure.

The mandate of the GFBR is to take a broad view of what constitutes research and its regulation in global health, with special attention to bioethics in Low- and Middle- Income Countries. AI as a group of technologies demands such a broad view. AI development for health occurs in a variety of environments, including universities and academic health sciences centers where research ethics review remains an important element of the governance of science and innovation internationally [ 10 , 11 ]. In these settings, research ethics committees (RECs; also known by different names such as Institutional Review Boards or IRBs) make decisions about the ethical appropriateness of projects proposed by researchers and other institutional members, ultimately determining whether a given project is allowed to proceed on ethical grounds [ 12 ].

However, research involving AI for health also takes place in large corporations and smaller scale start-ups, which in some jurisdictions fall outside the scope of research ethics regulation. In the domain of AI, the question of what constitutes research also becomes blurred. For example, is the development of an algorithm itself considered a part of the research process? Or only when that algorithm is tested under the formal constraints of a systematic research methodology? In this paper we take an inclusive view, in which AI development is included in the definition of research activity and within scope for our inquiry, regardless of the setting in which it takes place. This broad perspective characterizes the approach to “research ethics” we take in this paper, extending beyond the work of RECs to include the ethical analysis of the wide range of activities that constitute research as the generation of new knowledge and intervention in the world.

Ethical governance of AI in global health

The ethical governance of AI for global health has been widely discussed in recent years. The World Health Organization (WHO) released its guidelines on ethics and governance of AI for health in 2021, endorsing a set of six ethical principles and exploring the relevance of those principles through a variety of use cases. The WHO guidelines also provided an overview of AI governance, defining governance as covering “a range of steering and rule-making functions of governments and other decision-makers, including international health agencies, for the achievement of national health policy objectives conducive to universal health coverage.” (p. 81) The report usefully provided a series of recommendations related to governance of seven domains pertaining to AI for health: data, benefit sharing, the private sector, the public sector, regulation, policy observatories/model legislation, and global governance. The report acknowledges that much work is yet to be done to advance international cooperation on AI governance, especially related to prioritizing voices from Low- and Middle-Income Countries (LMICs) in global dialogue.

One important point emphasized in the WHO report that reinforces the broader literature on global governance of AI is the distribution of responsibility across a wide range of actors in the AI ecosystem. This is especially important to highlight when focused on research for global health, which is specifically about work that transcends national borders. Alami et al. (2020) discussed the unique risks raised by AI research in global health, ranging from the unavailability of data in many LMICs required to train locally relevant AI models to the capacity of health systems to absorb new AI technologies that demand the use of resources from elsewhere in the system. These observations illustrate the need to identify the unique issues posed by AI research for global health specifically, and the strategies that can be employed by all those implicated in AI governance to promote ethically responsible use of AI in global health research.

RECs and the regulation of research involving AI

RECs represent an important element of the governance of AI for global health research, and thus warrant further commentary as background to our paper. Despite the importance of RECs, foundational questions have been raised about their capabilities to accurately understand and address ethical issues raised by studies involving AI. Rahimzadeh et al. (2023) outlined how RECs in the United States are under-prepared to align with recent federal policy requiring that RECs review data sharing and management plans with attention to the unique ethical issues raised in AI research for health [ 13 ]. Similar research in South Africa identified variability in understanding of existing regulations and ethical issues associated with health-related big data sharing and management among research ethics committee members [ 14 , 15 ]. The effort to address harms accruing to groups or communities as opposed to individuals whose data are included in AI research has also been identified as a unique challenge for RECs [ 16 , 17 ]. Doerr and Meeder (2022) suggested that current regulatory frameworks for research ethics might actually prevent RECs from adequately addressing such issues, as they are deemed out of scope of REC review [ 16 ]. Furthermore, research in the United Kingdom and Canada has suggested that researchers using AI methods for health tend to distinguish between ethical issues and social impact of their research, adopting an overly narrow view of what constitutes ethical issues in their work [ 18 ].

The challenges for RECs in adequately addressing ethical issues in AI research for health care and public health exceed a straightforward survey of ethical considerations. As Ferretti et al. (2021) contend, some capabilities of RECs adequately cover certain issues in AI-based health research, such as the common occurrence of conflicts of interest where researchers who accept funds from commercial technology providers are implicitly incentivized to produce results that align with commercial interests [ 12 ]. However, some features of REC review require reform to adequately meet ethical needs. Ferretti et al. outlined weaknesses of RECs that are longstanding and those that are novel to AI-related projects, proposing a series of directions for development that are regulatory, procedural, and complementary to REC functionality. The work required on a global scale to update the REC function in response to the demands of research involving AI is substantial.

These issues take greater urgency in the context of global health [ 19 ]. Teixeira da Silva (2022) described the global practice of “ethics dumping”, where researchers from high income countries bring ethically contentious practices to RECs in low-income countries as a strategy to gain approval and move projects forward [ 20 ]. Although not yet systematically documented in AI research for health, risk of ethics dumping in AI research is high. Evidence is already emerging of practices of “health data colonialism”, in which AI researchers and developers from large organizations in high-income countries acquire data to build algorithms in LMICs to avoid stricter regulations [ 21 ]. This specific practice is part of a larger collection of practices that characterize health data colonialism, involving the broader exploitation of data and the populations they represent primarily for commercial gain [ 21 , 22 ]. As an additional complication, AI algorithms trained on data from high-income contexts are unlikely to apply in straightforward ways to LMIC settings [ 21 , 23 ]. In the context of global health, there is widespread acknowledgement about the need to not only enhance the knowledge base of REC members about AI-based methods internationally, but to acknowledge the broader shifts required to encourage their capabilities to more fully address these and other ethical issues associated with AI research for health [ 8 ].

Although RECs are an important part of the story of the ethical governance of AI for global health research, they are not the only part. The responsibilities of supra-national entities such as the World Health Organization, national governments, organizational leaders, commercial AI technology providers, health care professionals, and other groups continue to be worked out internationally. In this context of ongoing work, examining issues that demand attention and strategies to address them remains an urgent and valuable task.

The GFBR is an annual meeting organized by the World Health Organization and supported by the Wellcome Trust, the US National Institutes of Health, the UK Medical Research Council (MRC) and the South African MRC. The forum aims to bring together ethicists, researchers, policymakers, REC members and other actors to engage with challenges and opportunities specifically related to research ethics. Each year the GFBR meeting includes a series of case studies and keynotes presented in plenary format to an audience of approximately 100 people who have applied and been competitively selected to attend, along with small-group breakout discussions to advance thinking on related issues. The specific topic of the forum changes each year, with past topics including ethical issues in research with people living with mental health conditions (2021), genome editing (2019), and biobanking/data sharing (2018). The forum is intended to remain grounded in the practical challenges of engaging in research ethics, with special interest in low resource settings from a global health perspective. A post-meeting fellowship scheme is open to all LMIC participants, providing a unique opportunity to apply for funding to further explore and address the ethical challenges that are identified during the meeting.

In 2022, the focus of the GFBR was “Ethics of AI in Global Health Research”. The forum consisted of 6 case study presentations (both short and long form) reporting on specific initiatives related to research ethics and AI for health, and 16 governance presentations (both short and long form) reporting on actual approaches to governing AI in different country settings. A keynote presentation from Professor Effy Vayena addressed the topic of the broader context for AI ethics in a rapidly evolving field. A total of 87 participants attended the forum from 31 countries around the world, representing disciplines of bioethics, AI, health policy, health professional practice, research funding, and bioinformatics. The 2-day forum addressed a wide range of themes. The conference report provides a detailed overview of each of the specific topics addressed while a policy paper outlines the cross-cutting themes (both documents are available at the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ ). As opposed to providing a detailed summary in this paper, we aim to briefly highlight central issues raised, solutions proposed, and the challenges facing the research ethics community in the years to come.

In this way, our primary aim in this paper is to present a synthesis of the challenges and opportunities raised at the GFBR meeting and in the planning process, followed by our reflections as a group of authors on their significance for governance leaders in the coming years. We acknowledge that the views represented at the meeting and in our results are a partial representation of the universe of views on this topic; however, the GFBR leadership invested a great deal of resources in convening a deeply diverse and thoughtful group of researchers and practitioners working on themes of bioethics related to AI for global health including those based in LMICs. We contend that it remains rare to convene such a strong group for an extended time and believe that many of the challenges and opportunities raised demand attention for more ethical futures of AI for health. Nonetheless, our results are primarily descriptive and are thus not explicitly grounded in a normative argument. We make effort in the Discussion section to contextualize our results by describing their significance and connecting them to broader efforts to reform global health research and practice.

Uniquely important ethical issues for AI in global health research

Presentations and group dialogue over the course of the forum raised several issues for consideration, and here we describe four overarching themes for the ethical governance of AI in global health research. Brief descriptions of each issue can be found in Table  1 . Reports referred to throughout the paper are available at the GFBR website provided above.

The first overarching thematic issue relates to the appropriateness of building AI technologies in response to health-related challenges in the first place. Case study presentations referred to initiatives where AI technologies were highly appropriate, such as in ear shape biometric identification to more accurately link electronic health care records to individual patients in Zambia (Alinani Simukanga). Although important ethical issues were raised with respect to privacy, trust, and community engagement in this initiative, the AI-based solution was appropriately matched to the challenge of accurately linking electronic records to specific patient identities. In contrast, forum participants raised questions about the appropriateness of an initiative using AI to improve the quality of handwashing practices in an acute care hospital in India (Niyoshi Shah), which led to gaming the algorithm. Overall, participants acknowledged the dangers of techno-solutionism, in which AI researchers and developers treat AI technologies as the most obvious solutions to problems that in actuality demand much more complex strategies to address [ 24 ]. However, forum participants agreed that RECs in different contexts have differing degrees of power to raise issues of the appropriateness of an AI-based intervention.

The second overarching thematic issue related to whether and how AI-based systems transfer from one national health context to another. One central issue raised by a number of case study presentations related to the challenges of validating an algorithm with data collected in a local environment. For example, one case study presentation described a project that would involve the collection of personally identifiable data for sensitive group identities, such as tribe, clan, or religion, in the jurisdictions involved (South Africa, Nigeria, Tanzania, Uganda and the US; Gakii Masunga). Doing so would enable the team to ensure that those groups were adequately represented in the dataset to ensure the resulting algorithm was not biased against specific community groups when deployed in that context. However, some members of these communities might desire to be represented in the dataset, whereas others might not, illustrating the need to balance autonomy and inclusivity. It was also widely recognized that collecting these data is an immense challenge, particularly when historically oppressive practices have led to a low-trust environment for international organizations and the technologies they produce. It is important to note that in some countries such as South Africa and Rwanda, it is illegal to collect information such as race and tribal identities, re-emphasizing the importance for cultural awareness and avoiding “one size fits all” solutions.

The third overarching thematic issue is related to understanding accountabilities for both the impacts of AI technologies and governance decision-making regarding their use. Where global health research involving AI leads to longer-term harms that might fall outside the usual scope of issues considered by a REC, who is to be held accountable, and how? This question was raised as one that requires much further attention, with law being mixed internationally regarding the mechanisms available to hold researchers, innovators, and their institutions accountable over the longer term. However, it was recognized in breakout group discussion that many jurisdictions are developing strong data protection regimes related specifically to international collaboration for research involving health data. For example, Kenya’s Data Protection Act requires that any internationally funded projects have a local principal investigator who will hold accountability for how data are shared and used [ 25 ]. The issue of research partnerships with commercial entities was raised by many participants in the context of accountability, pointing toward the urgent need for clear principles related to strategies for engagement with commercial technology companies in global health research.

The fourth and final overarching thematic issue raised here is that of consent. The issue of consent was framed by the widely shared recognition that models of individual, explicit consent might not produce a supportive environment for AI innovation that relies on the secondary uses of health-related datasets to build AI algorithms. Given this recognition, approaches such as community oversight of health data uses were suggested as a potential solution. However, the details of implementing such community oversight mechanisms require much further attention, particularly given the unique perspectives on health data in different country settings in global health research. Furthermore, some uses of health data do continue to require consent. One case study of South Africa, Nigeria, Kenya, Ethiopia and Uganda suggested that when health data are shared across borders, individual consent remains necessary when data is transferred from certain countries (Nezerith Cengiz). Broader clarity is necessary to support the ethical governance of health data uses for AI in global health research.

Recommendations for ethical governance of AI in global health research

Dialogue at the forum led to a range of suggestions for promoting ethical conduct of AI research for global health, related to the various roles of actors involved in the governance of AI research broadly defined. The strategies are written for actors we refer to as “governance leaders”, those people distributed throughout the AI for global health research ecosystem who are responsible for ensuring the ethical and socially responsible conduct of global health research involving AI (including researchers themselves). These include RECs, government regulators, health care leaders, health professionals, corporate social accountability officers, and others. Enacting these strategies would bolster the ethical governance of AI for global health more generally, enabling multiple actors to fulfill their roles related to governing research and development activities carried out across multiple organizations, including universities, academic health sciences centers, start-ups, and technology corporations. Specific suggestions are summarized in Table  2 .

First, forum participants suggested that governance leaders including RECs, should remain up to date on recent advances in the regulation of AI for health. Regulation of AI for health advances rapidly and takes on different forms in jurisdictions around the world. RECs play an important role in governance, but only a partial role; it was deemed important for RECs to acknowledge how they fit within a broader governance ecosystem in order to more effectively address the issues within their scope. Not only RECs but organizational leaders responsible for procurement, researchers, and commercial actors should all commit to efforts to remain up to date about the relevant approaches to regulating AI for health care and public health in jurisdictions internationally. In this way, governance can more adequately remain up to date with advances in regulation.

Second, forum participants suggested that governance leaders should focus on ethical governance of health data as a basis for ethical global health AI research. Health data are considered the foundation of AI development, being used to train AI algorithms for various uses [ 26 ]. By focusing on ethical governance of health data generation, sharing, and use, multiple actors will help to build an ethical foundation for AI development among global health researchers.

Third, forum participants believed that governance processes should incorporate AI impact assessments where appropriate. An AI impact assessment is the process of evaluating the potential effects, both positive and negative, of implementing an AI algorithm on individuals, society, and various stakeholders, generally over time frames specified in advance of implementation [ 27 ]. Although not all types of AI research in global health would warrant an AI impact assessment, this is especially relevant for those studies aiming to implement an AI system for intervention into health care or public health. Organizations such as RECs can use AI impact assessments to boost understanding of potential harms at the outset of a research project, encouraging researchers to more deeply consider potential harms in the development of their study.

Fourth, forum participants suggested that governance decisions should incorporate the use of environmental impact assessments, or at least the incorporation of environment values when assessing the potential impact of an AI system. An environmental impact assessment involves evaluating and anticipating the potential environmental effects of a proposed project to inform ethical decision-making that supports sustainability [ 28 ]. Although a relatively new consideration in research ethics conversations [ 29 ], the environmental impact of building technologies is a crucial consideration for the public health commitment to environmental sustainability. Governance leaders can use environmental impact assessments to boost understanding of potential environmental harms linked to AI research projects in global health over both the shorter and longer terms.

Fifth, forum participants suggested that governance leaders should require stronger transparency in the development of AI algorithms in global health research. Transparency was considered essential in the design and development of AI algorithms for global health to ensure ethical and accountable decision-making throughout the process. Furthermore, whether and how researchers have considered the unique contexts into which such algorithms may be deployed can be surfaced through stronger transparency, for example in describing what primary considerations were made at the outset of the project and which stakeholders were consulted along the way. Sharing information about data provenance and methods used in AI development will also enhance the trustworthiness of the AI-based research process.

Sixth, forum participants suggested that governance leaders can encourage or require community engagement at various points throughout an AI project. It was considered that engaging patients and communities is crucial in AI algorithm development to ensure that the technology aligns with community needs and values. However, participants acknowledged that this is not a straightforward process. Effective community engagement requires lengthy commitments to meeting with and hearing from diverse communities in a given setting, and demands a particular set of skills in communication and dialogue that are not possessed by all researchers. Encouraging AI researchers to begin this process early and build long-term partnerships with community members is a promising strategy to deepen community engagement in AI research for global health. One notable recommendation was that research funders have an opportunity to incentivize and enable community engagement with funds dedicated to these activities in AI research in global health.

Seventh, forum participants suggested that governance leaders can encourage researchers to build strong, fair partnerships between institutions and individuals across country settings. In a context of longstanding imbalances in geopolitical and economic power, fair partnerships in global health demand a priori commitments to share benefits related to advances in medical technologies, knowledge, and financial gains. Although enforcement of this point might be beyond the remit of RECs, commentary will encourage researchers to consider stronger, fairer partnerships in global health in the longer term.

Eighth, it became evident that it is necessary to explore new forms of regulatory experimentation given the complexity of regulating a technology of this nature. In addition, the health sector has a series of particularities that make it especially complicated to generate rules that have not been previously tested. Several participants highlighted the desire to promote spaces for experimentation such as regulatory sandboxes or innovation hubs in health. These spaces can have several benefits for addressing issues surrounding the regulation of AI in the health sector, such as: (i) increasing the capacities and knowledge of health authorities about this technology; (ii) identifying the major problems surrounding AI regulation in the health sector; (iii) establishing possibilities for exchange and learning with other authorities; (iv) promoting innovation and entrepreneurship in AI in health; and (vi) identifying the need to regulate AI in this sector and update other existing regulations.

Ninth and finally, forum participants believed that the capabilities of governance leaders need to evolve to better incorporate expertise related to AI in ways that make sense within a given jurisdiction. With respect to RECs, for example, it might not make sense for every REC to recruit a member with expertise in AI methods. Rather, it will make more sense in some jurisdictions to consult with members of the scientific community with expertise in AI when research protocols are submitted that demand such expertise. Furthermore, RECs and other approaches to research governance in jurisdictions around the world will need to evolve in order to adopt the suggestions outlined above, developing processes that apply specifically to the ethical governance of research using AI methods in global health.

Research involving the development and implementation of AI technologies continues to grow in global health, posing important challenges for ethical governance of AI in global health research around the world. In this paper we have summarized insights from the 2022 GFBR, focused specifically on issues in research ethics related to AI for global health research. We summarized four thematic challenges for governance related to AI in global health research and nine suggestions arising from presentations and dialogue at the forum. In this brief discussion section, we present an overarching observation about power imbalances that frames efforts to evolve the role of governance in global health research, and then outline two important opportunity areas as the field develops to meet the challenges of AI in global health research.

Dialogue about power is not unfamiliar in global health, especially given recent contributions exploring what it would mean to de-colonize global health research, funding, and practice [ 30 , 31 ]. Discussions of research ethics applied to AI research in global health contexts are deeply infused with power imbalances. The existing context of global health is one in which high-income countries primarily located in the “Global North” charitably invest in projects taking place primarily in the “Global South” while recouping knowledge, financial, and reputational benefits [ 32 ]. With respect to AI development in particular, recent examples of digital colonialism frame dialogue about global partnerships, raising attention to the role of large commercial entities and global financial capitalism in global health research [ 21 , 22 ]. Furthermore, the power of governance organizations such as RECs to intervene in the process of AI research in global health varies widely around the world, depending on the authorities assigned to them by domestic research governance policies. These observations frame the challenges outlined in our paper, highlighting the difficulties associated with making meaningful change in this field.

Despite these overarching challenges of the global health research context, there are clear strategies for progress in this domain. Firstly, AI innovation is rapidly evolving, which means approaches to the governance of AI for health are rapidly evolving too. Such rapid evolution presents an important opportunity for governance leaders to clarify their vision and influence over AI innovation in global health research, boosting the expertise, structure, and functionality required to meet the demands of research involving AI. Secondly, the research ethics community has strong international ties, linked to a global scholarly community that is committed to sharing insights and best practices around the world. This global community can be leveraged to coordinate efforts to produce advances in the capabilities and authorities of governance leaders to meaningfully govern AI research for global health given the challenges summarized in our paper.

Limitations

Our paper includes two specific limitations that we address explicitly here. First, it is still early in the lifetime of the development of applications of AI for use in global health, and as such, the global community has had limited opportunity to learn from experience. For example, there were many fewer case studies, which detail experiences with the actual implementation of an AI technology, submitted to GFBR 2022 for consideration than was expected. In contrast, there were many more governance reports submitted, which detail the processes and outputs of governance processes that anticipate the development and dissemination of AI technologies. This observation represents both a success and a challenge. It is a success that so many groups are engaging in anticipatory governance of AI technologies, exploring evidence of their likely impacts and governing technologies in novel and well-designed ways. It is a challenge that there is little experience to build upon of the successful implementation of AI technologies in ways that have limited harms while promoting innovation. Further experience with AI technologies in global health will contribute to revising and enhancing the challenges and recommendations we have outlined in our paper.

Second, global trends in the politics and economics of AI technologies are evolving rapidly. Although some nations are advancing detailed policy approaches to regulating AI more generally, including for uses in health care and public health, the impacts of corporate investments in AI and political responses related to governance remain to be seen. The excitement around large language models (LLMs) and large multimodal models (LMMs) has drawn deeper attention to the challenges of regulating AI in any general sense, opening dialogue about health sector-specific regulations. The direction of this global dialogue, strongly linked to high-profile corporate actors and multi-national governance institutions, will strongly influence the development of boundaries around what is possible for the ethical governance of AI for global health. We have written this paper at a point when these developments are proceeding rapidly, and as such, we acknowledge that our recommendations will need updating as the broader field evolves.

Ultimately, coordination and collaboration between many stakeholders in the research ethics ecosystem will be necessary to strengthen the ethical governance of AI in global health research. The 2022 GFBR illustrated several innovations in ethical governance of AI for global health research, as well as several areas in need of urgent attention internationally. This summary is intended to inform international and domestic efforts to strengthen research ethics and support the evolution of governance leadership to meet the demands of AI in global health research.

Data availability

All data and materials analyzed to produce this paper are available on the GFBR website: https://www.gfbr.global/past-meetings/16th-forum-cape-town-south-africa-29-30-november-2022/ .

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Acknowledgements

We would like to acknowledge the outstanding contributions of the attendees of GFBR 2022 in Cape Town, South Africa. This paper is authored by members of the GFBR 2022 Planning Committee. We would like to acknowledge additional members Tamra Lysaght, National University of Singapore, and Niresh Bhagwandin, South African Medical Research Council, for their input during the planning stages and as reviewers of the applications to attend the Forum.

This work was supported by Wellcome [222525/Z/21/Z], the US National Institutes of Health, the UK Medical Research Council (part of UK Research and Innovation), and the South African Medical Research Council through funding to the Global Forum on Bioethics in Research.

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JS led the writing, contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. CA contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. PYC contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AE contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. JWG contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. AH contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DJ contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. KL contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. DP contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper. EV contributed to conceptualization and analysis, critically reviewed and provided feedback on drafts of this paper, and provided final approval of the paper.

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Shaw, J., Ali, J., Atuire, C.A. et al. Research ethics and artificial intelligence for global health: perspectives from the global forum on bioethics in research. BMC Med Ethics 25 , 46 (2024). https://doi.org/10.1186/s12910-024-01044-w

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Addressing Social Issues Affecting Health to Improve US Health Outcomes

• 1 Gail Wilensky, PhD, is an economist and Senior Fellow at Project HOPE, an international health foundation. She directed the Medicare and Medicaid programs, served as a senior adviser on health and welfare issues to President George H. W. Bush, and was the first chair of the Medicare Payment Advisory Commission. She is an elected member of the Institute of Medicine

In a recent JAMA Forum , Ashish Jha, MD, MPH, wrote about tackling the social determinants of health as a process that will require taking “small steps on a long journey” ( http://bit.ly/1JM5hFM ). I agree with him about the complexity raised by the social issues affecting health. And his admonition that investments in social determinants such as education, housing, and nutrition may not reduce spending on medical care—especially in the near term—are important warnings.

Gail Wilensky, PhD

I want to use a different rationale in advocating more attention to the social determinants of health: they reflect our best opportunity to improve health outcomes reported for the United States that are relatively poor, despite how much we spend on medical care.

For many years, the United States has focused on the need to slow spending on health care. Although levels of spending increases for health care have been historically low during the last 7 years, the higher spending reported for 2014 is expected to continue for the next decade, averaging 5.8% per year ( http://bit.ly/1JsXPgt ). That would bring the share of the gross domestic product (GDP) spent on health care from 17.5% to 19.6% by 2024. The estimated spending growth rate may not be precisely correct, but the end of the recession and the continued numbers of baby boomers entering retirement age guarantee continued upward pressure on health care spending.

Fortunately, there are many strategies available to help slow health care spending, some of which are currently being tried. Some of the most promising pilot projects include various types of payment changes, including bundled payments across clinicians and institutions that reward improved value, as well as changes that encourage the delivery of more integrated, evidence-based care. There are also efforts to provide better, more reliable and easily accessible information on quality and prices.

I’m not suggesting that sustaining a slower rate of growth will be easy. The mixed results reported thus far for many accountable care organizations (ACOs), including the more experienced Pioneer ACOs, suggests otherwise ( http://bit.ly/1fmhGlo ). But sustained efforts in these directions should produce results.

The reason to focus on social determinants of health is the relatively poor health outcomes the country reports, particularly disturbing given our high rate of spending. Even though it should be possible to improve outcomes with increased use of evidence-based medicine and comparative effectiveness research, along with more cogent use of electronic medical records and payment incentives, a more effective way to improve health is to focus on social determinants.

Focusing on Social Factors

There is substantial evidence that addressing social or nonmedical determinants of health such as early childhood development, economic opportunities, and education is more important than medical care per se for better health outcomes and avoiding premature death. And the role of social determinants for health is as important for developed countries as it is for developing countries. People know that life expectancy tends to be low in the developing world compared with the developed world. But differences in life expectancy for the poorest vs wealthiest populations or for minorities vs the majority population in developed countries are also large ( http://bit.ly/1pGedxt ). Life expectancy, for example is just 63 years for black men in Washington, DC, compared with 80 years for white men in affluent, adjacent Montgomery County.

I and the other 19 commissioners on the World Health Organization (WHO) Commission on the Social Determinants ( http://bit.ly/1Xvb04r ) advised the agency that beyond health legislation, improving health and reducing differences in health outcomes required more focus on the social factors affecting health: daily living conditions, healthy places to live and work, investments in early childhood development, and recognizing the health effects resulting from all legislation. When so much attention has been focused on the health care system these past 7 years—an understandable preoccupation when 15% to 16% of the population is without health insurance—it is easy to forget how much more effective focusing on the social determinants can be for improving health outcomes, especially for children.

Former US Surgeon General David Satcher, MD (another WHO commissioner) and I raised this point in an article jointly written ( http://bit.ly/1Z0I1GU ) after the commission reported its recommendations for action to the WHO’s Director-General ( http://bit.ly/1U7Yji7 ). Improving the conditions that shape early childhood development can enhance opportunities for health throughout a lifetime. Conditions such as obesity, cardiovascular disease, cancer, and mental health problems often have their roots in the early years of life. Programs that address the needs of children with very low food security are important, as are the various food programs for pregnant and postpartum women. Similarly, investing in early childhood education, especially for individuals living in poverty, can be a cost-effective strategy for preventing disease and increasing productivity later in life.

Efforts to reduce substance abuse are also important for young adults and for pregnant women in particular. Too many children start life with serious medical challenges because their mothers had substance abuse problems. These women almost always are covered by Medicaid or other insurance, but for various reasons don’t receive the help they need—a reminder that coverage is important but frequently not sufficient to ensure that care is available.

A Healthy Early Start

Securing a healthy start in life for children and improving living conditions for adults will require a more integrated policy environment than typically occurs in the United States, although the increase in capitated health care make this easier to occur than the past silos of health care. Responsibility for full health care encourages insurers to look beyond the narrow provisions of traditional health care plans. However, most plans focus primarily on better aligning the provision of traditional medical care than expanding their mission to include the social determinants of care.

The potential flexibility for states to innovate in the delivery of care that seemed to be part of the ACA with its 1332-waiver process is now looking to be more constrained. The waivers are limited to direct ACA coverage, require budget neutrality in each year, with at least the same number of people covered and receiving as much coverage as without the waiver. More importantly, the waiver process doesn’t create opportunities to count savings from other government programs, such as Medicaid, for purposes of calculating budget neutrality ( http://bit.ly/1SF1mxt ).

When I was a policy adviser to President George H. W. Bush, the city leaders of Atlanta, with assistance from the Carter Center, approached the White House with a request to be allowed to pool their federal resources to provide their residents with better care and support through health and other social service programs. The federal resources, along with commitments of support from the business community, were believed to be adequate—just in the wrong buckets, with too many silos separating (and duplicating) programs. The White House was very supportive but recognized the prospect of getting all the committees of jurisdiction to waive control over all the federal programs in question was too daunting.

We spend enough money on health care and other social services to improve health outcomes. We just spend it badly.

Corresponding Author: Gail Wilensky, PhD ( [email protected] ).

Published Online: March 16, 2016, at http://newsatjama.jama.com/category/the-jama-forum/ .

Disclaimer: Each entry in The JAMA Forum expresses the opinions of the author but does not necessarily reflect the views or opinions of JAMA, the editorial staff, or the American Medical Association.

Additional Information: Information about The JAMA Forum is available at http://newsatjama.jama.com/about/ . Information about disclosures of potential conflicts of interest may be found at http://newsatjama.jama.com/jama-forum-disclosures/ .

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Wilensky G. Addressing Social Issues Affecting Health to Improve US Health Outcomes. JAMA. 2016;315(15):1552–1553. doi:10.1001/jama.2016.3863

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Addressing Ethical, Social, and Cultural Issues in Global Health Research

* E-mail: [email protected]

Affiliations Ethical, Social and Cultural Program for Global Health, Centre for Research on Inner City Health and Centre for Global Health Research, Keenan Research Centre in the Li Ka Shing Knowledge Institute of St. Michael's Hospital, Toronto, Ontario, Canada, Dalla Lana School of Public Health and Joint Centre for Bioethics, University of Toronto, Toronto, Ontario, Canada

Affiliations Dalla Lana School of Public Health and Joint Centre for Bioethics, University of Toronto, Toronto, Ontario, Canada, Ethical, Social and Cultural Program for Global Health, Sandra Rotman Centre, University Health Network & University of Toronto, Toronto, Ontario, Canada

Affiliation Ethical, Social and Cultural Program for Global Health, Sandra Rotman Centre, University Health Network & University of Toronto, Toronto, Ontario, Canada

Affiliation Bill & Melinda Gates Foundation, Seattle, Washington, United States of America

Affiliations Dalla Lana School of Public Health and Joint Centre for Bioethics, University of Toronto, Toronto, Ontario, Canada, Ethical, Social and Cultural Program for Global Health, Sandra Rotman Centre, University Health Network & University of Toronto, Toronto, Ontario, Canada, Centre for the AIDS Programme of Research in South Africa (CAPRISA), Doris Duke Medical Research Institute, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Congella, Durban, South Africa

Affiliations Dalla Lana School of Public Health and Joint Centre for Bioethics, University of Toronto, Toronto, Ontario, Canada, Ethical, Social and Cultural Program for Global Health, Sandra Rotman Centre, University Health Network & University of Toronto, Toronto, Ontario, Canada, Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada

• James V. Lavery, 
• Shane K. Green, 
• Sunita V. S. Bandewar, 
• Anant Bhan, 
• Abdallah Daar, 
• Claudia I. Emerson, 
• Hassan Masum, 
• Filippo M. Randazzo, 
• Jerome A. Singh, 

Published: August 8, 2013

• https://doi.org/10.1371/journal.pntd.0002227
• Reader Comments

Citation: Lavery JV, Green SK, Bandewar SVS, Bhan A, Daar A, Emerson CI, et al. (2013) Addressing Ethical, Social, and Cultural Issues in Global Health Research. PLoS Negl Trop Dis 7(8): e2227. https://doi.org/10.1371/journal.pntd.0002227

Editor: David Joseph Diemert, The George Washington University Medical Center, United States of America

Copyright: © 2013 Lavery et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: JVL, SKG, AB, AD, CIE, JAS, REGU, and PAS performed this work as members of and/or consultants to the Ethical, Social and Cultural (ESC) Program for Global Health, which receives funding from the Bill & Melinda Gates Foundation. FMR is an employee of the foundation. Other than FMR's contributions as an author, the funder had no role in the preparation or revision of the manuscript, or in the decision to publish the manuscript.

Competing interests: The authors have declared that no competing interests exist.

The purpose of this paper is to encourage reflection among the global health research community and the research ethics community about how a wide range of ethical, social, and cultural (ESC) influences on the conduct, success, and impact of global health research can best be addressed by consultation services in research ethics (CSRE). We draw on lessons we have learned during our experiences with the ESC Program of the Grand Challenges in Global Health initiative to propose key features of CSRE that may prove useful for those designing or implementing similar programs.

Introduction

The past decade has seen unparalleled investment in large-scale global health science initiatives and international research consortia, such as the International HapMap Project, Grand Challenges in Global Health program, and International AIDS Vaccine Initiative. These initiatives have resulted in promising advances, such as candidate vaccines for malaria and HIV, nutritionally enhanced staple crops, novel vector control strategies, and an advanced understanding of human genetic diversity. They have also reflected the growing emphasis on innovation in global health and on the urgent need to test innovations in real-world settings, especially resource-constrained ones, to determine their potential effectiveness and value. Alongside—and necessitated by—these shifts in global health research, there has also been a broadening in the conversation about the ethical aspects of that research, from an almost singular focus on standard of care issues [1] to a more holistic consideration of a wide range of ethical, social, and cultural (ESC) influences on the conduct, success, and impact of biomedical science on underlying public health problems.

This broadening, in turn, has helped to fuel a growing interest within the health research community in consultation services in research ethics (CSRE). These are teams of experts in research ethics, typically based at academic bioethics centres, that provide advice and guidance to researchers and institutions about ethical issues that arise in the design and conduct of research. Since first proposed [2] , there has been some attention to the evolution of CSREs in the literature [3] , [4] , with much of the focus on how to achieve an appropriate balance between the advisory/consulting role of the emerging CSREs and the review, monitoring, and oversight responsibilities of their counterpart institutional review boards (IRBs) [5] . Most recently, an article published in Science Translational Medicine from the Stanford University CSRE has provided important insights into circumstances that the authors argue should “trigger" investigators to seek consultations with the service [4] . Although the authors point to “research in developing nations" as one such trigger, there continues to be a gap in the literature about why and how CSREs might play an important role in proactively considering and helping to address the unique ESC challenges posed by global health research—in particular, research in low- and middle-income countries (LMICs) that is funded and conducted, in whole or in part, by organizations and investigators from high-income countries—and thereby provide a valuable complement to customary institutional research ethics review for this type of research.

The purpose of this paper is to encourage reflection among the global health research community, including funders, researchers, research institutions, and administrators of large-scale global health research initiatives, about how ESC issues can best be addressed within these initiatives. We draw on lessons we have learned during our experiences with the Ethical, Social and Cultural Program (ESC Program) of the Grand Challenges in Global Health (GCGH) initiative, funded by the Bill & Melinda Gates Foundation between 2005–2011 [6] , to propose key features of a focused CSRE, which may prove useful for those designing or implementing similar programs.

Key Features of an ESC Program for Global Health Research

1. integrate esc consultation with the planning and performance of the research.

Integrating science and ethics is fundamentally about acknowledging that values permeate not only trials and applications of new technologies, but all aspects along the “critical path" of the scientific process—from discovery science through development of novel products and technologies to their effective delivery to end users, e.g., patients, consumers, communities, public health authorities—and identifying where lack of sufficient attention to ESC issues can undermine the ethics, social value, quality, feasibility, or sustainability of the science and its outputs. Effective integration enables proactive, deeply informed, interdisciplinary thinking, as well as mutual learning and otherwise unattainable insights. Previous ethics programs for large-scale science initiatives, such as the Ethical, Legal and Social Implications (ELSI) Program of the Human Genome Project, have been criticized for failing to integrate the ELSI work effectively with the science [7] . Others, like the US National Nanotechnology Initiative [8] and Genome Canada's GE 3 LS Program [9] , have made attempts to improve integration through the mandated formation of multidisciplinary research teams, but the extent to which these mandates have led to meaningful integration of ESC considerations remains unclear.

In designing the ESC Program for the GCGH, our goal was to prevent ESC challenges from becoming problems, where possible, by identifying them much further upstream than when research proposals are typically submitted to IRBs for prospective review, and where prevention was not possible, to help solve them. Working closely with foundation staff responsible for R&D program strategy and funding, in addition to individual scientists funded through the GCGH initiative, was a critical element of this design. Rather than viewing ESC issues simply as interesting by-products of complex science, such upstream integration enabled us to better understand how ESC issues present as specific challenges at numerous points along the projects' critical paths, and how they may be amenable to ethical analysis and various ESC solutions or management strategies.

Establishing the necessary working relationships with researchers and foundation staff took time and effort. And we occasionally had to counter two common misconceptions about our work: first, that ESC issues are primarily theoretical and therefore of limited relevance to the day-to-day work of successfully conducting research; and second, that our role was simply to facilitate the science by clearing ESC “bottlenecks" for the researchers. We addressed these concerns by focusing more of our attention on how R&D program staff experienced ESC challenges and their ability to facilitate ESC solutions. We were initially concerned that our increasing interactions with R&D program staff would compromise our objectivity or contribute to this impression. In fact, this has rarely been an issue, because we have been consistent in articulating the importance and value of our independent perspective, and also because the “upstream" ESC problems tend to be poorly characterized and therefore less polarized than some other more well-worn ESC issues. As well, R&D staff turnover has, in some situations, required us to “reset" these interactions and is one of the challenges that can limit the rate of penetration of the ESC program model.

But despite these challenges, we believe that intensifying our interactions with the R&D program staff in particular was helpful in four main ways: 1. It enabled identification of ESC issues early in the critical path of a particular research initiative; 2. It contributed to a normalizing of the idea of shared “ESC thinking," a process we have tried to engender by regularly engaging program staff in dialogue about emerging challenges and what might count as effective “solutions"; 3. It nurtured a sophisticated expert forum for “pressure-testing" our proposed solutions to ESC challenges to help ensure they were feasible, practical, and viable in the contexts in question; and 4. It helped to ensure that potentially viable solutions could be applied to any subsequent research project within the GCGH program, and beyond, in addition to the immediate value for the particular project involved in the initial consultation.

2. Privilege Southern Perspectives

Integration of science and ethics gives prominence to the perspectives of R&D program staff and researchers—scientists, social scientists, and humanists alike—in large-scale research endeavors. In global health research, there are particularly complex ethical, social, and cultural dimensions to challenges that arise in host communities that are beyond the knowledge and experience of strictly foreign ESC teams. To address these challenges adequately and appropriately it is necessary not only to incorporate the perspectives of local ESC experts, but to privilege them. Therefore, it is important that an ESC program seek meaningful contributions from these essential yet often under- or unrepresented perspectives, thereby ensuring that investigators and program staff have a sufficient depth of understanding and appreciation of the social, economic, and political contexts within which the proposed research will be conducted [10] . For an ESC program in global health research, this translates into privileging perspectives from the “global South."

Despite a great deal of rhetoric to the contrary, funding programs and individual research programs and projects aimed at addressing key health problems of LMICs continue to arise disproportionately from elite northern institutions. Although this state of affairs reflects real and relevant economic and institutional differences between high- and LMICs, too little attention is paid to how LMIC perspectives can be more successfully brought to bear in the shaping of the agendas and practices of global health research. It has also been argued that the conditions required to support an effective research ethics “system"—to which we would add more meaningful integration of science and ethics—are themselves intimately tied to countries' level of development [11] .

Nonetheless, strong representation of Southern perspectives and expertise in the process of identifying and addressing ESC challenges in global health research is critical for: providing cultural guidance, particularly in situations in which differences in the meaning of various research activities can lead to ethically problematic misunderstandings [12] ; leveraging lived experiences to enhance interpretation of issues related to relevant LMIC guidelines and regulations; and more readily and knowledgeably providing navigation through complex social and institutional and regulatory structures in the South as science moves closer to various forms of field testing. With this in mind, we recommend that ESC programs focused on global health engage bioethicists from LMICs as co-investigators, staff members, and post-doctoral fellows.

This is not without its challenges, however. In our experience, which relies heavily on each team member to provide substantive input on specific cases and to contribute to the broader evolution and strategic direction of our program, common challenges related to connecting to team members working in LMICs—i.e., unreliable phone and internet services—have often proved debilitating. Similarly, although the initial design of our program was to base one of our three primary programmatic foci at an institution in the South, those plans were stymied by a number of administrative hurdles that stemmed largely from our Northern institution's limited experience with international partnerships and the lack of readily accessible “off-the-shelf" models to help design and guide the development of these partnerships. The specific challenges faced in meaningfully engaging essential yet underrepresented perspectives in other large-scale research initiatives will depend, of course, on the particulars of the initiatives. Nonetheless, we suggest that due consideration be given to who might/should bring those perspectives, followed by planning and feasibility testing of strategies for engagement prior to implementation.

3. Build on Specific Cases to Identify and Propose Solutions to Cross-Cutting Issues

Our experience has taught us to not only focus on discrete ESC issues specific to a particular project or program, but also to look for opportunities to devise potential solutions to challenges that cut across numerous research endeavors. Although such cross-cutting “model solutions" may vary significantly in their impact and ultimate value, they lend themselves well to strategic dissemination and are thus useful for stimulating broader dialogue in the field as well as among leaders and decision makers looking for concrete proposals. One path to identifying cross-cutting issues in need of solutions is to work upstream in the research process, as described above, while another is to start by solving problems at the level of specific project consultations and extrapolate key concepts to facilitate development of broad solutions. Three illustrative examples of this latter approach from our work in global health are described below.

Promote respect through effective and ethical community engagement: There are myriad examples of how superficial, awkward, hurried, or otherwise disrespectful forms of engagement with individuals and communities in LMICs have jeopardized or prematurely ended global health research or delivery initiatives [13] , [14] . And yet, despite the seemingly obvious significance of community engagement (CE), current research ethics guidelines and regulations have an almost exclusive focus on the individual and provide very little guidance about successful interactions with communities or the underlying rationales for what respectful engagement of communities entails [15] . This point has been reinforced most recently in the recommendations of the U.S. Presidential Commission in its aim to “further develop operational guidelines for the protection and ethical treatment of human subjects through the means of community engagement" [16] . From the outset of our program we have prioritized the importance of community engagement (CE), recognizing that the complex human interactions accompanying the introduction of new global health technologies—from new contraceptives to vaccines to TB treatments—can play a critical role in their impact and sustainability.

Our ability to provide effective integrated consultation on CE in specific research projects stems directly from our own empirical research on CE—funded through the ESC Program—which generated insights about how CE can contribute to respectful conduct in research through in-depth case studies in various research contexts. For example, our study of CE at the National Health Research Centre (NHRC) in northern Ghana revealed how incorporating traditional community entry practices into the centre's approach to CE helped to promote respectful conduct by correcting power imbalances between guest researchers and the host community [17] . As well, our study of the CE strategies employed in a long-standing prospective observational cohort study of the genetic epidemiology of HIV among sex workers in Nairobi improved our understanding of the social power of CE practices by demonstrating how research projects can create entirely new communities [18] .

These insights and experiences from our empirical research have helped us to effectively shape a number of cross-cutting solutions related to CE. For example, our consultation to help map out ESC considerations for site selection for a caged field trial of genetically modified mosquitoes (GMM) for the control of dengue virus transmission expanded the scope of site selection criteria to include key regulatory and CE considerations [19] . These expanded criteria have been referenced in draft WHO guidance for GMM trials [20] , and a subsequent framework for CE in GMM trials that arose from the same collaboration [21] has been cited by the U.S. Presidential Commission for the Study of Bioethical Issues [16] and singled out as a promising general approach in an editorial in Nature [22] .

Fill gaps in regulation, governance, policies and guidelines:.

Many ESC challenges in global health arise from situations in which regulations, governance mechanisms, policies, or guidelines in relevant jurisdictions are either nonexistent or not tailored sufficiently to the nuances of particular scientific endeavors. Still other challenges arise when asymmetries among various countries' regulatory schemes complicate the uniform implementation of research or delivery activities within a region. We've attempted to meet these challenges by focusing our efforts on identifying, critically analyzing, and proposing solutions to fill the regulatory, governance, and policy gaps encountered in specific research domains, and then seeking broader application and impact for those solutions where feasible and appropriate. In some instances, the solutions proposed have remained limited to specific projects (e.g., the development of a project-specific oversight mechanism for a project involving stem cell research at Peking University) [23] , while others have broader implications (e.g., principles for researchers' obligations to participants in observational studies in LMICs, principles for global health data access) [24] , [25] .

Promote and facilitate responsible partnerships with the private sector:.

The private sector has enormous capacities in manufacturing, product development, and supply chain infrastructure that could prove valuable in many global health initiatives. But many private companies have been severely criticized for unethical practices. As a result, there is a widespread distrust of the private sector within many public sector and civil society organizations, which results in missed opportunities to leverage private sector capacities to improve global health R&D and delivery in certain circumstances. Driven by the belief that trust and effective collaboration between public and private sector partners can be achieved with the appropriate oversight, policies, and governance mechanisms, we have developed several model solutions focused explicitly on the goal of improving trust and accountability in public-private partnerships (PPPs) [26] – [28] . Our aim has been to build on experiences with specific PPPs (e.g., in infant nutrition, agricultural development) to reduce a vast and seemingly insurmountable problem into discrete aspects—e.g., identify and/or develop useful mechanisms of accountability, declarations of values, codes of conduct—that can be applied and evaluated in a broad set of real world applications.

A standing challenge for the ESC Program has been balancing our responsiveness to demands for ESC consultation in specific cases with the need to maintain an active program of empirical and conceptual research to help ensure that the insights and lessons learned through our consultations can be applied successfully to improve our understanding of cross-cutting ESC issues. This tension should be anticipated by any new ESC program and addressed as a key aspect of the design and funding structure of the program.

4. Improve the Evaluation of Strategies, Activities, and Outcomes

The evaluation of the impact of research ethics review and consultation is grossly underdeveloped [3] , [4] . As ESC programs achieve greater integration with scientific program development and conduct, and gain more experience with the development and dissemination of model solutions to ESC challenges, it will become increasingly essential to develop the strategies and means to fairly and thoroughly evaluate the extent to which ESC problem-solving can improve the global health research enterprise. As with many complex programs, however, there are few if any natural or obvious measures of impact or effectiveness. Traditional academic metrics like publications and citations are generally poor indicators of the real impact of global health research on, for example, the health of LMIC populations. Further complicating the assessment of ESC programs' attributable impact on global health is the fact that their greatest successes may be in preventing the undesirable—but not inevitable—from occurring.

Through trial and error, we have come to recognize that meaningful and rigorous evaluation of the impact of the ESC Program requires us to look beyond simple evaluation practices to embrace new methods for the evaluation of complex interventions [29] . For example, over the course of the evolution of the ESC Program we have progressively shifted our focus toward improving our “program theory" of how the ESC Program works; that is, what are its essential components and what pathways link them with specific outcomes? This paper is one product of this type of analysis. One specific insight drawn from complex evaluation has been that our interactions with R&D program staff, described above, create an ongoing context for “co-learning" [29] , i.e., opportunities for the ESC Program to gain a better understanding of how ESC challenges arise and how R&D program staff understand and manage them, and opportunities for R&D program staff to contribute to ESC solutions from the outset and scrutinize and critique them during their development. This, in effect, functions as a built-in evaluation mechanism. We continue to develop our evaluation practices and welcome dialogue and collaboration with other groups who are grappling with these same challenges.

Conclusions

Research ethics permeates the entirety of the modern scientific endeavor: institutions and researchers promote and protect scientific integrity, IRBs protect and promote the interests of human research subjects, and CSREs are increasingly called upon to address ethical issues that can present perplexing obstacles along the critical paths to the responsible realization of scientific and technological advances. In no domain are scientific advances more needed than in global health. We hope, therefore, that in sharing these lessons above we can help ESC programs focused on global health to evolve, improve their practices, and gain prominence. Moreover, the importance of integration, of looking for broad applications of narrowly intended solutions, of bringing diverse perspectives to bear on complex ethical challenges, and of rigorous impact evaluation are by no means limited to global health; as such, we hope these lessons may also prove useful for CSREs focused on a wide range of scientific endeavors.

• Integrate ESC consultation with the scientific endeavor.
• Privilege Southern perspectives.
• Promote respect through effective and ethical community engagement.
• Fill gaps in regulation, governance, policies, and guidelines.
• Promote and facilitate responsible partnerships with the private sector.
• Evaluate strategies, activities, and outcomes.

Acknowledgments

The authors thank Lauren Leahy and Kelsey Martin for their support and assistance in preparing the manuscript and Jocalyn Clark for helpful comments on earlier drafts.

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• 9. Genome Canada (2012) GE 3 LS: Genomics and Society. Available: http://www.genomecanada.ca/en/ge3ls/ . Accessed 4 September 2012.
• 16. Presidential Commission for the Study of Bioethical Issues (2011) Moral science: protecting participants in human subjects research. Washington, DC. Available: http://bioethics.gov/node/558 . Accessed 13 July 2013.
• 20. World Health Organization (2012 October 29) Guidance framework for testing of genetically modified mosquitoes. TDR news item. Available: www.who.int/tdr/news/2012/guidance_framework/en/index.html . Accessed 8 July 2013.
• 25. Bill and Melinda Gates Foundation (2011) Global health data access principles. Available: http://www.gatesfoundation.org/global-health/Documents/data-access-principles.pdf . Accessed 4 September 2012.

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Maximising the benefits of research: Guidance for integrated care systems

England has a vibrant research and development ecosystem, with well-developed research infrastructure and research expertise within our health and care workforce. The value of research in transforming health and care is significant; additionally, staff satisfaction, recruitment and retention is higher among staff who are involved in research. The inception of integrated care systems (ICSs) provides the opportunity for systems to embed research within health and care for the benefit of our population. Supporting this opportunity, a clear research thread runs through ICS strategies and plans, from joint strategic needs assessments and joint health and wellbeing strategies , integrated care strategies , joint forwards plans , integrated care board (ICB) annual reports and the assessment by NHS England of the discharge of duties by ICBs.

The Health and Care Act 2022 (the 2022 Act) sets new legal duties on ICBs around the facilitation and promotion of research in matters relevant to the health service, and the use in the health service of evidence obtained from research. NHS England will assess ICBs for their discharge of these duties. The ICS design framework sets the expectation that in arranging provision of health services, ICBs will facilitate their partners in the health and care system to work together, combining expertise and resources to foster and deploy research and innovations. This guidance supports ICBs in fulfilling their research duties.

ICSs are encouraged to develop a research strategy that aligns to or could be included in their integrated care strategy. This strategy will enable the unification of research across ICS partners, and be consistently embedded to:

• identify and address local research priorities and needs, and work collaboratively to address national research priorities
• improve the quality of health and care and outcomes for all through the evidence generated by research
• increase the quality, quantity and breadth of research undertaken locally
• extend and expand research in settings such as primary care, community care, mental health services, public health and social care
• drive the use of research evidence for quality improvement and evidence-based practice
• influence the national research agenda to better meet local priorities and needs
• improve co-ordination and standardisation within and between localities for the set up and delivery of research
• harness the patient and economic benefits of commercial contract research
• co-ordinate and develop the research workforce across all settings.

1. Introduction

This guidance sets out what good research practice looks like. It supports integrated care systems (ICSs) to maximise the value of their duties around research for the benefit of their population’s health and care and, through co-ordination across ICSs, for national and international impact. It supports integrated care boards (ICBs), integrated care partnerships (ICPs) and their partners to develop a research strategy that aligns to or can be incorporated into their integrated care strategy, and helps them and their workforce to build on existing research initiatives and activities across health and social care to improve sector-wide performance and best practice

• explains the ICB legal duties and other requirements around research and the use of evidence from research, and that research is included in forward planning and reporting
• encourages system leaders to develop a footprint-wide research strategy that aligns to local and national research priorities, develops and supports their workforce, takes the opportunities offered by commercial research and includes plans to embed research in their system’s governance and leadership
• identifies best practice examples and other resources that ICBs may find useful as they develop their research strategies.

This guidance provides comprehensive information for use by:

• those with senior responsibility, including at board level, for research strategy development and/or operationalising research
• managers responsible for developing joint strategic needs assessments, integrated care strategies, joint health and wellbeing strategies, joint forward plans, other linked strategies, or reporting on ICB activities
• research managers
• research and development/innovation leads
• heads of services
• knowledge and library specialists.

It may also be useful to individuals involved in research, education, and partner organisations such as local authorities, social care services, the voluntary, community and social enterprise sector (VCSE) and other providers of healthcare services.

NHS England provides guidance on embedding research in the NHS and secure data environments, and the Office for Life Sciences (OLS ) champions research, innovation and the use of technology to transform health and care service. Other sources of guidance, support and information are signposted in this guidance to support ICSs in aligning to national visions, strategies and plans around research.

1.1 Definition of research

NHS England uses the UK Policy Framework for Health and Social Care Research definition of research:

“… the attempt to derive generalisable or transferable new knowledge to answer or refine relevant questions with scientifically sound methods. This excludes audits of practice and service evaluation. It includes activities that are carried out in preparation for or as a consequence of the interventional part of the research, such as screening potential participants for eligibility, obtaining participants’ consent and publishing results. It also includes non-interventional health and social care research (that is, projects that do not involve any change in standard treatment, care, or other services), projects that aim to generate hypotheses, methodological research and descriptive research”.

This broad definition encompasses the range of types of research:

• clinical trials and other clinical investigations into the safety and effectiveness of medicines, devices and health technologies
• public health research
• observational studies
• discovery science and experimental medicine
• translational research in which results from basic research are developed into results that directly benefit people
• applied research
• research to support policy-making and commissioning
• social care research and research in social care settings
• research into NHS services and care pathways.

1.2 Why research is important

The UK is a world leader for research and invention in healthcare, with around 25% of the world’s top 100 prescription medicines being discovered and developed in the UK ( The impact of collaboration: The value of UK medical research to EU science and health ). Research in the health and care system is important because it underpins all advances in health and care and is the basis for evidence-based practice. Engaging clinicians and healthcare organisations in research is associated with improvements in delivery of healthcare ( Does the engagement of clinicians and organisations in research improve healthcare performance: a three-stage review) . To benefit service users and the public, the NHS and local government, and achieve return on investment, it is vital that research is disseminated, shared and translated into practice.

The National Institute for Health and Care Research (NIHR) is funded by the Department of Health and Social Care (DHSC) to transform research in the health and social care system, including through support for NHS research. Research led to the first proven treatments for Covid, for example the use of dexamethasone, estimated to have saved over a million lives worldwide . This success was in part due to how research is undertaken in the unique environment of the NHS, innovative trial designs, the support provided by the NIHR, frontline staff enabling research, and the awareness and readiness of the public to support research. We need to learn from these and other successes, and translate this across all health and care settings. ICSs will play a vital role in enabling research to be embedded in evolving patient pathways across their footprints.

Example: PRINCIPLE trial – finding treatments for Covid recovery at home

The Platform Randomised Trial of Treatment in the Community for Epidemic and Pandemic Illnesses (PRINCIPLE) was a UK-wide, clinical study to find Covid treatments for recovery at home without the need to attend hospital. The study was open to all with ongoing Covid symptoms, registration was easy, and the trial was run entirely remotely by delivering ‘participant packs’ to people’s homes. It was one of the first trials in the world to show that azithromycin and doxycycline did not benefit patients with Covid and to identify the effectiveness of a commonly used drug – inhaled budesonide –in reducing time to recovery.

The PRINCIPLE study team demonstrated the integral role that primary, secondary and ambulatory care staff can play in the delivery of studies. Local collaborators were trained in good clinical practice to allow them to assess and confirm the eligibility of potential participants, and were commended specifically for their use of patient data to contact people soon after they received a positive test result. It is this network of local staff contributing to research within their healthcare setting that has enabled over 10,000 people to be recruited onto this study so far – one of the largest at home Covid treatment studies worldwide.

This is an example of a study design that incorporates the vital contributions of healthcare providers across the system.

Policy-makers and commissioners need evidence to support their decision-making around the delivery and system-wide transformation of health and care services, including how health inequalities will be reduced.

There is also evidence that:

• staff involved in research have greater job satisfaction and staff turnover is lower in research active trusts ( Academic factors in medical recruitment: evidence to support improvements in medical recruitment and retention by improving the academic content in medical posts)
• research active hospitals have lower mortality rates, and not just among research participants ( Research activity and the association with mortality )
• 83% of people believe that health research is very important ( Survey of the general public: attitudes towards health research)
• healthcare performance improvements have been seen from the creation of academic research placements ( Experiences of hospital allied health professionals in collaborative student research projects: a qualitative study )
• clinical academic research, and in particular the practice changes resulting from it, is associated with improved patient and carer experiences ( A qualitative systematic review and thematic synthesis exploring the impacts of clinical academic activity by healthcare professionals outside medicine ).

Key to having research embedded in health and care is having staff who can understand, undertake, use and generate new research, and share actionable research finding as part of a pro-research culture. Education and training are therefore critical for research to be sustainably embedded within health and care, and for people to develop careers in research and support it in their clinical or care roles.

DHSC, NHS England, the devolved administrations, NIHR and other partners expect to publish a clinical research workforce strategy in 2023/24 to help the UK realise the national clinical research vision outlined in Saving and Improving Lives: The Future of UK Clinical Research Delivery and deliver the Life Sciences Vision to see research embedded in the NHS as part of health and care pathways.

Research will support ICSs to deliver on their four key aims:

Improving outcomes

The NHS 2023/34 priorities and operational planning guidance emphasises the importance of research in improving patient care, outcomes and experience.

Research evidence will inform commissioning decisions to improve experience and outcomes. Research activities should align with the local health priorities identified through local joint strategic needs assessments, and may be best designed and delivered by collaborating with partners. Research priorities may be best addressed by collaborating with partners nationally to design and deliver research.

Tackling inequalities

Research can give a better understanding of local populations and the wider determinants of health, and with this the steps to maintain health and narrow health inequalities.

Enhancing productivity

The development of ICSs creates the opportunity to consider research delivery within the ICS and across ICS boundaries, increasing flexibility of workforce or recruitment while reducing bureaucracy and improving research productivity and value for money.

Supporting social and economic development

An active research ecosystem working in a co-ordinated way and to national standards brings revenue and jobs to regions. The NIHR Clinical Research Network (CRN) supports service users, the public and health and care organisations across England to participate in high-quality research. The 2019 impact and value report detailed the significant income and cost savings that commercial research generates for NHS trusts. Between 2016/17 and 2018/19 the NHS received on average £9,000 per patient recruited to a commercial clinical trial and saved over £5,800 in drug costs for each of these patients. This equates to income of £355 million and cost savings of £26.8 million in 2018/19.

In 2021 150 members of the Association of Medical Research Charities funded £1.55 billion of medical research, including the salaries of 20,000 researchers. Every £1 million spent by charities on medical research in the UK contributes £1.83 million to the economy.

Example: Research that cut problematic prescribing and generated cost savings in general practice – a local health priority

Analysis of routine patient data identified the need for strategies targeting clinicians and patients to curb rising opioid prescribing. From this, the Campaign to Reduce Opioid Prescription (CROP) was launched in 2016, urging GPs across West Yorkshire to ‘think-twice’ before prescribing opioids. This promoted the NICE guidance on chronic pain , which recommends reducing the use of opioids because there is little or no evidence that they make any difference to people’s quality of life, pain or psychological distress, but they can cause harm, including possible addiction.

Over a year 15,000 fewer people were prescribed opioids (a 5.63% relative reduction), a net saving to the NHS of £700,000. The biggest reduction was in people aged over 75, who are at higher risk of opioid-related falls and death, and there was no compensatory rise in the prescribing of other painkillers or referrals to musculoskeletal services.

The CROP campaign, led by researchers at the University of Leeds, has subsequently been rolled out across all ICBs in Yorkshire and the Humber, and the North East and North Cumbria ICB, and the 1,045 practices to which it has been delivered are reporting results similar to the above.

Foy R, Leaman B, McCrorie C, Petty D, House A, Bennett M, et al (2016) Prescribed opioids in primary care: cross-sectional and longitudinal analyses of influence of patient and practice characteristics | BMJ Open 69(5).

Alderson SL, Faragher TM, Willis TA, Carder P, Johnson S, Foy R (2021) The effects of an evidence- and theory-informed feedback intervention on opioid prescribing for non-cancer pain in primary care: A controlled interrupted time series analysis. PLOS Med .

2. ICS, ICP and ICB responsibilities and requirements

ICBs have legal duties and other requirements that relate to research. These are additional to the duties and responsibilities of individual providers within ICS footprints. This section sets out what these duties mean in practical terms and gives examples of how to meet them.

2.1 Legal duties relating to research in the Health and Care Act 2022

Part 1 of the 2022 Act includes specific legal duties for ICBs and NHS England in respect of research. In the Explanatory Notes to the 2022 Act, government sets out how ICBs could discharge their research duty.

Duty to facilitate or otherwise promote research

The ICB duty builds on the previous clinical commissioning group (CCG) duty to promote research, by requiring each ICB, in the exercise of its functions, to facilitate or otherwise promote research on matters relevant to the health service. This duty is intended to include a range of activities to enable research. Section 3 of this guidance outlines ways in which ICBs can do this.

The NHS Constitution also makes clear that patients should be enabled to take part in research: “the NHS pledges … to inform you of research studies in which you may be eligible to participate”.

The Provider Selection Regime (PSR) will be a new set of rules for arranging healthcare services in England, introduced by regulations made under the 2022 Act. The research component should be referred to once the PSR is published.

Duty to facilitate or otherwise promote the use in the health service of evidence obtained from research

This duty similarly builds on the CCG requirement to promote the use of evidence. ICBs must, in the exercise of their functions, facilitate or otherwise promote the use in the health service of evidence obtained from research. For example, ICBs should facilitate or otherwise promote the use of evidence in care, clinical and commissioning decisions.

Duty for ICSs to include research in their joint forward plans and annual reports

Joint forward plans are five-year plans developed by ICBs and their partner NHS trusts and foundation trusts. Systems are encouraged to use the joint forward plan as a shared delivery plan for the integrated care strategy and joint health and wellbeing strategy, aligned to the NHS’s universal commitments. The plan must explain how the ICB will discharge its duties around research, and the ICB must report on the discharge of its research duties in its annual report. These inclusions will raise the profile of research at board level and help embed research as a business-as-usual activity.

The joint forward plan and NHS Oversight Framework guidance set the minimum requirements for what needs to be included in plans and reports.

NHS England duty to include how each ICB is carrying out its duties relating to research in its annual performance assessment of each ICB

NHS England has a new legal duty to annually assess the performance of each ICB and publish a summary of its findings. For 2022/23 NHS England will complete a narrative assessment, identifying areas of good and/or outstanding performance, areas for improvement and any areas that are particularly challenged, drawing on national expertise as required and having regard to relevant guidance. This assessment will include a section considering how effectively the ICB has discharged its duties to facilitate or otherwise promote research and the use of evidence obtained from research.

This, alongside the implementation of the NHS Long Term Plan commitment to develop research metrics for NHS providers, will increase transparency across the system and enable more targeted support for research. Research metrics from NHS England, the Care Quality Commission (CQC) and NIHR will enable the monitoring of progress over time, and are under development with sector colleagues, including providers.

2.2 Legal requirement to work with people and communities

Working with people and communities is a requirement of ICBs, and statutory guidance is available to support them and their partner providers meet this legal duty. A co-ordinated approach across healthcare delivery and research will make it more likely that research reflects what matters to people and communities.

This will also help ICBs to fulfil their legal duty in the 2022 Act to reduce health inequalities in access to health services and the outcomes achieved. Section 3.9 includes links to resources to help guide engagement with underserved communities around research.

The Public Sector Equality Duty also applies and requires equality of opportunities between persons who share a relevant protected characteristic and persons who do not.

2.3 Research governance

While research can address local priorities, it typically operates across ICS boundaries and at national and international levels. Health and social care research is governed by a range of laws, policies, and international, national and professional standards.

The Health Research Authority (HRA ) is responsible for ensuring such regulation is co-ordinated and standardised across the UK to make it easier to do research that people can trust. The HRA is an executive non-departmental public body created by the Care Act 2014 to protect and promote the interests of patients and the public in health and social care research, including by co-ordinating and standardising the practice of research regulation. Local authorities and the NHS are obliged to have regard to its guidance on the management and conduct of research.

Before a research project can start in the NHS in England it must receive approval from the HRA. This includes research taking place in NHS trusts, NHS foundation trusts, ICBs or primary care providers of NHS commissioned services in England, and all research under an NHS duty of care, including that undertaken by NHS staff working in social care or other non-NHS environments.

The HRA schemes indemnify NHS organisations accepting these assurances against any claim covered by the NHS Litigation Authority arising as a result of incorrect assurances. If an NHS organisation duplicates the HRA assessments, it will be liable for any consequences of the decisions it bases on its own checks.

ICBs and partner organisations should have processes for the set up and delivery of research that comply with national laws and systems, and does not duplicate them. Such national systems include confirmation of capacity, National Contract Value Review (NCVR), management of Excess Treatment Costs (ETCs) and contracting arrangements (see section 2.4).

The UK Policy Framework for Health and Social Care sets out the roles and responsibilities of individuals and organisations involved in research.

2.4 Contractual requirements around research

NHS England mandates commissioner use of the NHS Standard Contract for all contracts for healthcare services other than primary care. The contract is updated annually. References to research in the current NHS Standard Contract and service conditions fall into three main areas.

Recruitment of service users and staff into approved research studies

The NHS Standard Contract obliges every provider of NHS-funded services to assist the recruitment of suitable subjects (whether patients or staff) into approved research studies. This requirement aligns to those in the 2022 Act that require ICBs to facilitate or otherwise promote research (see section 2.1). Section 3 considers how this requirement can best be met. Research involving people or their data requires ethical and potentially other approvals (see section 2.3).

National Directive on Commercial Contract Research Studies

Adherence to the National Directive is mandated as part of the NHS Standard Contract. The directive states that providers must:

• Use the unmodified model agreements for sponsor-to-site contracting; HRA and Health and Care Research Wales (HCRW) approval of studies will be dependent on use of these templates.
• Use the standard costing methodology to set prices for commercial contract research undertaken by NHS providers; this is currently in the NIHR interactive costing tool (NIHR iCT).
• Introduce the National Contract Value Review (NCVR) process in line with national rollout. NCVR is a standardised national approach to costing commercial contract research within the NHS. It currently covers acute, specialist and mental health trusts, but the intention is to roll it out to all NHS providers. The creation of ICSs is the ideal opportunity to explore how commercial study set up can be supported across these footprints, reducing the resource needed and time taken.

Comply with HRA/NIHR research reporting guidance

The provider must comply with HRA/NIHR research reporting guidance, as applicable.

2.5 Excess treatment costs

Patients in a research study may receive healthcare that differs from what is standard in the NHS, requires more clinician time or is delivered in a different location. The associated NHS treatment costs may exceed or be less than those of standard treatment. If greater, the difference is referred to as the NHS Excess Treatment Costs (ETCs).

In the case of commercial contract research, the commercial funder will pay the full cost of the study. In the case of non-commercial research, the commissioner of the service in which the study operates is responsible for funding the ETCs.

ICBs as commissioners of services are responsible for ETCs in services that they commission. Guidance for the management of ETCs is available.

DHSC and NIHR are piloting interim arrangements to support non-NHS ETCs for research in public health and social care (non-NHS intervention costs). Please refer to the further detail on the NIHR website .

2.6 Care Quality Commission

The CQC is currently developing its approach for ICS-level assessments, and its new assessment framework will be introduced towards the end of 2023 .

CQC inspection of NHS providers continue, with research assessed as part of the review of the trust-level Well-led framework. Providers are asked:

• Are divisional staff aware of research undertaken in and through the trust, how it contributes to improvement and the service level needed across departments to support it?
• How do senior leaders support internal investigators initiating and managing clinical studies?
• Does the vision and strategy incorporate plans for supporting clinical research activity as a key contributor to best patient care?
• Does the trust have clear internal reporting systems for its research range, volume, activity, safety and performance?
• How are service users and carers given the opportunity to participate in or become actively involved in clinical research studies in the trust?

3. Developing a research strategy

3.1 why develop a research strategy.

Like the health and care system, the research environment is complex. Developing a research strategy will help bring together the legal and other duties around research in a coherent way, and help the ICS understand its local research capability, workforce, activity and needs, set ambitions around research and maximise the benefits associated with commercial research. It will help demonstrate the benefit of research locally, nationally and internationally, and guide the production of clear plans.

Example: Value of research partnerships and integration with ICSs

Bristol Health Partners (BHP) Academic Health Science Centre (AHSC) has a fully integrated relationship as the new Research and Innovation Steering Group for the Bristol, North Somerset and South Gloucestershire (BNSSG) ICS, and reports directly to ICB chief executives.

The group provides the strategic direction and oversight for all research undertaken and delivered across the system. Membership includes directors of research, clinical strategy, public health, social care, senior innovation and education leaders from its core funding partners. It also includes public contributors and senior representatives from primary care, NIHR Applied Research Collaboration West, NIHR CRN West of England, West of England Academic Health Science Network (WEAHSN), Healthier Together ICS, university research institutes and People in Health West of England.

The group has reviewed ICS programmes, identified current and potential research and innovation connections, and begun to establish new connections. It has also supported work with the ICS Ageing Well programme and secured funding for innovative pilots to improve dementia care and increase physical activity for older adults.

Since 2016 BHP has directly contributed an estimated additional £1.1 million to support ICS priorities through Health Integration Team projects and other activities, and has attracted more than £33 million of external research, service redesign and infrastructure into the region.

3.2 General considerations

In developing its research strategy, the ICS may find it helpful to consider these overarching questions alongside the suggested focused content covered in the sections below:

• What do you hope to achieve within a given timeframe?
• Are all the right organisations involved in developing the research strategy?
• How will the health and care workforce be enabled to deliver the research strategy?
• How can research be embedded in existing health and care delivery and pathways?
• What mechanisms are in place to translate actionable research findings into practice and decision-making?
• What inequalities exist in different areas, communities or groups? How will you ensure planning and delivery of research aligns to CORE20plus5 priorities?
• Are you considering equality, diversity and inclusivity and the Public Sector Equality Duty in facilitating and promoting research opportunities for service users and for health and care staff?
• Is the ICS considering the opportunities of developing their commercial research portfolio?
• Is research informing or being informed by population health management?
• How will you plan and deliver research in a sustainable manner, aligning it to the Greener NHS agenda and the ICB’s duties in relation to climate change ?

Buy-in from NHS staff, patients and the public will be vital if ICBs are to discharge their research duties and deliver on their research plans. An important consideration is how to develop sustainable, routine and accessible information flows to ensure the ICB, partners, staff, patients and public can access up-to-date and appropriate information around local research activity, regional, national and international research opportunities and findings, and contact information.

3.3 Leadership and governance across the ICS

Executive leadership.

The Explanatory Notes to the 2022 Act suggest that ICBs have board-level discussions on research activity, the use of the evidence from research, the research workforce and research culture within the ICS. ICSs should refer to the NHS Leadership Competency Framework for board-level leaders at organisation and ICS level for the competencies relating to the research duties of ICSs, once published.

All ICBs are encouraged to have an executive lead responsible for fulfilling the research duties conferred by the 2022 Act. They should help give the ICB a clear understanding of research across the area, regularly reporting on progress towards agreed aims. An executive lead can take responsibility for ensuring clear research ambitions and a research strategy are developed; oversight of organisational research portfolios, diversity in research, alignment to national priorities; promotion of research skills and the need for research skills training; and succession planning.

Senior leaders could engage, consult and be supported by representatives of each registered health and social care professional group when developing strategic plans, and for oversight of training, succession planning, and equality and inclusivity. They could use the capacity and capability of the research and development leads within provider organisations, although established lead roles across social care settings are rare so extra effort may be needed to garner social care research insight.

Research steering group, board or forum

Some CCGs had research steering groups and some of these have expanded with the widening remit of ICBs. ICSs that do not have a such a group should consider adopting a model similar to one in other ICSs where research is effectively embedded in ICS governance structures.

A dedicated steering research group, board and/or forum can:

• provide dedicated time to plan, oversee and report on research
• bring a range of representatives from research infrastructure organisations, patients and the public together with representation from across the ICS, to develop a common aim and objective
• ensure board-level sight of research
• take a cross-ICS approach to research, increasing participation and diversity in research, and reducing bureaucracy.

Example: A dedicated research and innovation subgroup

East and North Hertfordshire Health Care Partnership established a formal research and innovation subgroup to support its objectives to transform services, reduce health inequalities and improve patient health and wellbeing. This subgroup is dedicated to determining and supporting local research priorities and developing an innovation agenda. With effective patient and public involvement, it is working to ensure the local population has access to more research opportunities.

Bringing together the NIHR, academia, industry and local health and care services, the subgroup develops collaborative work plans that support the design, implementation and evaluation of local transformation needs, sharing resources, staff, expertise and facilities. Its work exemplifies a sustainable approach to partnership working and supports Hertfordshire and West Essex ICS’s developing strategy.

HWE ICS Partnership Board 14 September 2021

3.4 Understanding your research activity and working with local and national research infrastructure

Research in NHS and non-NHS settings across an ICS footprint will be supported by different organisations. In some areas networks or collaboratives already exist to bring these organisations together, but in others the links are not as well formed. ICBs would benefit from having a clear map of the research infrastructure and pre-existing local or national investment into research in their area.

It may be valuable to consider:

• Who are the research leaders in your local health and care system, NIHR, higher education institutions, VCSE sector and businesses?
• Are there any pre-existing local or regional research, researcher or research engagement networks?
• What are the opportunities to inform, participate in, collaborate with or lead national and international research efforts in addition to local opportunities?

A list of organisations involved in research including NIHR-funded infrastructure and programmes is included in Annex 1 .

Much of the research undertaken in NHS and other health and care settings is funded though national calls and grants provided by funders such as NIHR, research charities , UK Research and Innovation (UKRI) , including the Medical Research Council (MRC ) and Economic and Social Research Council (ESRC) , and is aligned to national priorities. Other research may include national or international commercial or non-commercial clinical trials funders.

Partners within ICS systems can use NIHR research portfolio data to monitor and plan research activity; however, not all research is included within the NIHR’s portfolio, so this will not give a full picture of the research within the footprint. Mechanisms to map and monitor research more widely could be incorporated in ICB research strategies.

Some local needs may best be addressed through public health or social care research rather than research in primary, secondary or tertiary healthcare settings. Public health and social care research are described in Annex 2 .

Example: Mapping health and care research activity, expertise, interests and infrastructure

The Nottingham and Nottinghamshire Integrated Care System Research Partners Group meets bi-monthly and is chaired by the ICB Head of Research and Evidence. It brings together senior managers from the NHS providers, ICB, two local authorities, two universities and the NIHR CRN East Midlands, providing a forum for ICS-wide research discussions and the development of a system-wide collaborative approach to health and care research across the ICS. Among its aims, the group seeks to increase participation in research at both the organisational and population level, enable equity of access to research opportunities and generate impact on health and care pathways.

The group have mapped health and care research activity, expertise, interests and infrastructure in the constituent organisations. With this the ICS can see the research capabilities, strengths, expertise, and areas of synergy and opportunities for future collaboration that align to its needs and priorities, and also gaps for future development, recognising that organisations are at different stages of research development.

3.5 Understanding local needs

Universal NHS priorities will be reflected in local research needs, and each ICS footprint is likely to have its own specific local research needs. Joint strategic needs assessments (JSNAs) are undertaken jointly by local authorities and ICBs through health and wellbeing boards (HWBs) to identify current health and social care needs of local communities, where more information is needed to do so or to understand how best to address the need. People and communities should be directly involved in identifying local need, including by working with local charities, specific communities or groups who face inequalities in access to, experience of or outcomes from healthcare, eg to target health research at those areas and populations with greatest need.

ICPs are required to develop an integrated care strategy informed by JSNAs and the joint health and wellbeing strategy (JHWS). The integrated care strategy sets out how the assessed needs can be met through the exercise of the functions of the ICB, partner local authorities or NHS England, and is informed by research and practice-based evidence, as stated in the health and wellbeing guidance. In considering where such evidence is lacking, HWBs should identify in JSNAs those research needs that ICBs, local authorities and NHS England could meet through the exercise of their research functions.

Systems are encouraged to use their joint forward plan to develop a shared delivery plan for the Integrated Care Strategy and the JHWS that is supported by the whole system, including local authorities and VCSE partners. ICBs and trusts must also use their Joint Forward Plan to describe how the ICB will discharge its duty in respect of research.

The Explanatory Notes to the 2022 Act suggest how ICBs can discharge their duties around research. These include the articulating local research needs when assessing local needs and how they will be addressed when preparing strategies and plans, and encouraging partner organisations to play an active and collaborative role in pursuing these.

3.6 Supporting delivery of research

Once an ICS has a clear picture of its local research infrastructure it can consider how best to target and support research and the research workforce across its footprint and how research findings will be used. For this, the ICB should ensure that its approaches reflect national approaches to costing, contracting, approvals and information governance, and that they are also informed by learning from effective practices across equivalent ICBs.

As healthcare shifts into communities, ICSs should support the parallel shift in research by embedding research in health and care. Increasing access to research opportunities will give service users earlier access to new treatments, and faster research set up and delivery may provide the evidence needed to support improvements to local care sooner. Inclusive recruitment practices will be needed to ensure that all groups in society have the opportunity to help shape and take part in research, and benefit from research findings.

In developing its research strategy, an ICS has opportunities to reduce bureaucracy, and make research more efficient and effective across its own and with other ICS footprints, and across NHS and non-NHS boundaries, while meeting national regulatory guidance. ICBs will be expected to work with the HRA to co-develop, build on and implement strategies for further co-ordination and standardisation of study set-up and delivery processes. Any regional systems and processes that ICBs do establish must support consistent national practice in relation to the management and regulation of research, and should not duplicate them. The HRA will work with ICBs to address barriers to efficient and rapid study set-up, including model agreements, information governance and R&D office functions.

Other potential areas for streamlining and cross-organisational working include:

• cross-ICS research proposals to identify research needs
• research delivery – identifying how ICS-wide approaches could accelerate patient recruitment and deployment of research delivery staff
• shared data architecture, including the NHS Secure Data Environment for Research Network and its subnational secure data environments (SDEs). Subnational SDEs cover multiple ICSs to achieve access to multimodal data at a scale of approximately 5 million citizens, and over time will achieve technical and governance interoperability
• a greater focus on translation and implementation of research findings into health and care practice, supporting faster improvements
• sharing access to and funding for knowledge and library services
• shared processes and repositories for research assets.

The Explanatory Notes to the 2022 Act suggest that one way an ICB could discharge its research duty would be to have a dedicated research office or team supporting research.

3.7 Enabling cross-provider research

Health and care priorities can often only be addressed with complex, multiorganisational approaches and as such the research to inform these needs to span organisational boundaries. Organisational policies should promote cross-organisational research and dissemination of research findings, including through participation in collaborative research to address national priorities, joint staff posts, honorary contracts, and administratively easier movement of researchers between health and care organisations and other sector partners, including higher education, industry, charities and local authorities.

The HRA and ICS partners are developing national guidance to support cross-provider research.

The NIHR CRN can offer ICSs opportunities to participate in national and international research studies, including those the NIHR, industry and others commission.

3.8 Commercial research

Commercial contract research is research funded solely by industry, where NHS providers are contracted to carry out the research. Most of these research studies in the NHS are interventional clinical trials, such as the NHS-Galleri trial and Astra Zeneca’s COVID-19 vaccine development . Commercial research can give patients access to a wider range of research opportunities, earlier access to novel therapies and treatments, provide drugs free of charge to patients in trials, accelerate the development of new treatments and devices, generate income for providers, and fund NHS staff. It is vitally important for the benefit of patients, the NHS and the UK economy that we create an environment in the NHS that makes it easy and efficient for the NHS to undertake commercial research. This is particularly important when it comes to international commercial research, where companies can place their studies in a number of different countries and consideration of anticipated set up and recruitment times informs where they place trials.

Data gathered during some commercial research is specific to the study and is the property of the company, as is any Intellectual Property (IP) generated. In other cases, where the NHS contributes to the foreground IP – such as through the use of NHS data for research or where NHS expertise provides important contributions to a commercial product – it is important that the NHS shares in the value of IP generated as a consequence of its contributions.

The establishment of ICSs is an ideal opportunity for their creation of ambitions to enable, grow and benefit from commercial research. ICSs should explore how efficient commercial study set up and delivery could be streamlined across sites within their footprint, and should set ambitions around commercial research.

3.9 Involving patients, service users, carers and the public in research

In developing a research strategy ICSs should set out their approach to diverse public and patient involvement (PPI) in relation to research.

Areas where working with people and communities could add value in the context of research include:

• identification of local research needs, including through JSNAs and JHWSs
• designing research proposals in partnership with local or national experts
• raising awareness of research opportunities and recruitment of participants
• developing research outcome reports and identification of how and when participants will be able to access these
• consideration of how members of the public can access the outputs from publicly-funded research
• how volunteers should be involved and what they should be paid.

The UK Standards for Public Involvement sets out the core components of good public involvement. A guide outlining good practice in engaging underserved communities around research is available from NHS England. Resources about good practice around PPI in designing and delivering research, including around incentivisation , are also available from the HRA and NIHR .

It will be useful to link into established community involvement approaches. NIHR infrastructure organisations may have established networks of expert PPI representatives, and ICSs have extensive VCSE Alliances. A co-ordinated community engagement approach across health and care delivery and research will reduce the risk of overburdening communities with organisations wanting to work with them, and will support the identification of under-served communities.

3.10 Ensuring anyone can participate in research

Making research more visible within communities and increasing the public’s understanding of research can ensure greater diversity in research participation. Research findings will then be more generalisable to a broader range of groups or communities, or can be targeted and specific to relevant communities.

ICSs should seek mechanisms to ensure that opportunities to take part in research are available to all. They should consider encouraging patients and members of the public to register on NIHR Be Part of Research (a national registry where people can express their interest in being contacted about research that is relevant to them), widely disseminate research opportunities and make provision for inclusive access for communities to take part in research. Decentralised or virtual trials are remote access trials recruited to and delivered using electronic tools, making it easier for people to participate in some studies without needing to visit a recruiting hospital or attend appointments in person. ICBs should consider ways in which research delivery can increase access to research opportunities for people within their area. ICBs should also advise the public how they can access research outputs.

NIHR and UK Research and Innovation provide resources that help organisations address issues of equality, diversity and inclusion in research settings.

Example: RELIEVE-IBS decentralised trial

In 2020, Newcastle researchers launched RELIEVE-IBS, one of the first interventional decentralised clinical studies in the UK to trial Enterosgel, a new treatment for irritable bowel syndrome with diarrhoea (IBS-D). Decentralised trials are remote access trials that use electronic tools for trial recruitment and delivery, without the patient needing to visit a recruiting hospital site, which could be miles from their homes – a convenient option for patients with IBS-D. By running the trial remotely, researchers could reach beyond the small proportion of those with this condition who attend specialist clinics, as well as save resource for the sponsor.

Not only did this trial embrace technological developments to deliver research, but it empowered more patients to become involved regardless of where they lived. With in-depth patient input, the research team were able to shape the recruitment approach to be highly accessible to participants and were offered feedback on how to refine the trial design by the sponsors. The resulting patient-centric design ensured a good recruitment response when the trial opened.

NIHR (2020) Virtual trial recruits 67% faster led by NIHR Patient Recruitment Centre in Newcastle in collaboration with Enteromed

NIHR (2021) Pushing virtual boundaries to improve patient engagement and accessibility

NIHR (2022) RELIEVE IBS-D trial case study

3.11 Health data in research

Health data generated through care of service users in the NHS can fuel a revolution in the research and development of new diagnostics and treatments, maximising the potential to improve service user outcomes and experiences, support diversity in research, and minimise health inequalities through research. To do this, researchers need access to high quality and timely data to generate insights. The public expect data to be used legally and efficiently to conduct and support research.

National commitments around data for research can be found in Data saves lives: reshaping health and social care with data . This strategy shows how data will be used to bring benefits to all parts of health and social care. To achieve this vision, the NHS will be making a strategic move away from a system of data dissemination to one of data access when making NHS health and social care data available for research and analysis. This will be facilitated by the implementation of secure data environments (SDEs).

SDEs are data storage and access platforms with features that enable organisations to have greater control and oversight over their data. SDEs allow approved users to view and analyse data without it having to leave the environment. The SDE policy guidelines provide a clear signal to the sector that SDEs will become the default way of accessing NHS data for research.

This change is supported by major investments in digital infrastructure through the Data for Research & Development Programme, which is funding the development of national and subnational SDEs. The subnational SDEs will cover the entirety of England and individual platforms will cover several ICS.

ICBs should seek ways to promote and enable the use of these rich data sources for research and include them in their research strategy.

3.12 Using evidence for planning, commissioning and improving health and care

Evidence-based commissioning has advantages for the commissioner, workforce and service users, as it can:

• lead to innovation in service design and delivery
• enhance the quality of health and care provision
• reduce clinical variation between locations and providers
• improve equity of access to services
• improve patient and population outcomes.

As part of the commissioning process, commissioners are expected to use evidence-based clinical policies, as per the Roadmap for integrating specialised services within integrated care systems . Knowledge and library services can help source and interpret evidence.

The Provider Selection Regime will reflect the research duties of the 2022 Act and should be referred to when commissioning provider services, once it has been published.

NHS knowledge and library services provide access to evidence and support for knowledge management; they train people in searching for, handling and publishing information. The Knowledge for Healthcare strategy encourages and equips NHS knowledge and library services to support NHS organisations with the translation of knowledge for the spread and adoption of research and innovation. To fulfil their obligations under the 2022 Act, ICBs could commit to active knowledge translation.

Evidence for commissioning information is available from a number of sources:

• NHS Library and Knowledge Hub
• Health Libraries and Information Services Directory
• NICE guidance
• NIHR evidence
• NHS evidence works toolkit
• Academy of Medical Royal Colleges: Evidence-based Intervention
• A million decisions

The infographic for the role of research and evidence in commissioning also provides sources for evidence-based commissioning.

Example: Evidence mobilisation, knowledge sharing and improving outcomes

The STEMClub (Sustaining Transformation by Evidence Mobilisation) is a network in the North East and North Cumbria that brings together local policy and decision-makers with NHS knowledge and library specialists to facilitate evidence-based decision-making. The input of knowledge specialists ensures timely access to published research and provides knowledge management expertise to shape how soft intelligence is translated into knowledge assets.

As members within the STEMClub network, knowledge and library specialists are providing ongoing detailed evidence reviews and information management expertise to facilitate system-wide working , eg:

• North East North Cumbria Frailty Framework
• North East and North Cumbria Maternity Clinical Network
• a review of optimal patient transfer times in the North East and North Cumbria
• regular evidence summaries for the ICS Mental Health Evidence and Evaluation subgroup.

3.13 The health and care workforce and research

Staff involved in research have greater job satisfaction and research active trusts have lower staff turnover [3] . Clinical academic roles [7] , having research colleagues within services [8] and taking students on research placements [6] are felt to foster an increase in knowledge and skills across the wider staff workforce. The General Medical Council (GMC) and the Royal College of Physicians (RCP) and NIHR have issued position statements and recommendations around research, with additional signatories including UKRI, UKRD, the Academy of Medical Royal Colleges and the Royal College of Surgeons of England. Learning resources, including programmes for ongoing professional development of the research delivery workforce, are available through NIHR Learn.

In developing a research strategy ICSs could ensure that, as part of their people function and approach to workforce planning :

• Staff roles in leading, delivering or facilitating research and in supervising those developing research skills are recognised, supported and enabled across all staff groups and health and care settings as part of a positive research culture.
• The value of evidence is recognised, and education and training around research are facilitated. Opportunities to develop research careers or in overseeing the development of other researchers are enabled; this may include having protected time, inclusion in job plans and joint appointments across health and care providers and academic institutions.
• Ensuring that there is capacity and systems that support research through services like imaging, pathology and pharmacy, as well as finance and human resources.
• Individual organisations do not always have the necessary skills or services to support effective research and its impact, such as IP management, methodological expertise, regulatory compliance, statistical analysis, knowledge mobilisation expertise, genomics expertise, health informatics and data analytics. Mechanisms are needed to ensure that these can readily and rapidly be accessed across other health and care organisations, including from local authorities and other non-NHS care providers.

A UK Clinical Research Workforce Strategy is under development. ICSs should update their approaches to their research workforce once DHSC publishes this in 2023/24.

Example: Investing in the research workforce – developing capacity for chief investigators

Across the West Midlands NIHR CRN, an investment of approximately £750,000 to develop capacity for chief investigators returned additional research grant income of over £18 million in three years. This was achieved primarily by increasing the programme activity for consultants in areas where chief investigators were underrepresented.

The funding was provided through a competitive process and co-supported by the local NIHR CRN, with several local trusts jointly funded these scholars.

Kirk J, Willcocks J, Boyle P, Brocklehurst P, Morris K, Kearney R, et al (2022) Developing chief investigators within the NHS: the West Midlands clinical trials scholars programme. Clin Med 22(2): 149–52.

Kirk J, Reynolds F, Adey E, Boazman M, Brookes M, Brocklehurst P (2022) Developing paediatric chief investigators within the NHS: the Clinical Trials Scholars programme . Arch Dis Child Educ Pract Published online first: 22 February 2022. doi: 10.1136/archdischild-2021-322186

4. References

• Varnai P, Rentel M, Dave A, De Scalzi M, Timmerman W, Rosemberg-Mantes C, Simmonds P, Technopolis Group (2017) The impact of collaboration: The value of UK medical research to EU science and health .
• Boaz A, Hanney S, Jones T, Soper B (2015) Does the engagement of clinicians and organisations in research improve healthcare performance: a three-stage review. BMJ Open 5: e009415. doi:10.1136/ bmjopen-2015-009415 .
• Rees MR, Bracewell M (2019) Academic factors in medical recruitment: evidence to support improvements in medical recruitment and retention by improving the academic content in medical posts. Postgrad Med J 95(1124): 323-327. doi:10.1136/postgradmedj-2019-136501 .
• Ozdemir BA, Karthikesalingham A, Singha S, Poloniecki JD, Hinchliffe RJ, Thompson MM, et al (2015) Research activity and the association with mortality. PLoS ONE 10(2): doi.org/10.1371/journal.pone.0118253 .
• Hunn A (2017) Survey of the general public: attitudes towards health research . Health Research Authority.
• Angus RL, Hattingh HL, Weir KA (2022) Experiences of hospital allied health professionals in collaborative student research projects: a qualitative study. BMC Health Services Research 22(1). Available at: https://doi.org/10.1186/s12913-022-08119-7 .
• Newington L, Wells M, Adonis A, Bolten L, Bolton Saghdaoui L, Coffey M, et al (2021) A qualitative systematic review and thematic synthesis exploring the impacts of clinical academic activity by healthcare professionals outside medicine. BMC Health Serv Res 21(1). Available at: https://doi.org/10.1186/s12913-021-06354-y .
• Wenke RJ, Hickman I, Hulcombe J, Phillips R, Mickan S (2017) Allied health research positions: A qualitative evaluation of their impact. Health Res Policy Syst 15(6). Available at: https://doi.org/10.1186/s12961-016-0166-4

Annex 1 – Organisations that may be involved in regional or local research

• Clinical Research Networks (CRNs) , which will be retendered and renamed regional research delivery networks (RRDNs) from April 2024
• Applied Research Collaborations (ARCs)
• Biomedical Research Centres (BRCs)
• Experimental Cancer Medicine Centres (ECMCs) , jointly funded with Cancer Research UK
• Research Design Services (RDSs) and Clinical Trials Units (CTUs) which will be replaced by the NIHR Research Support Service from 1 October 2023
• Patient Recruitment Centres (PRCs)
• MedTech and In vitro diagnostic Co-operatives (MICs) , which will be replaced with HealthTech research centres from April 2024
• School of Public Health Research, School of Primary Care Research and School of Social Care Research
• Health Determinants Research Collaborations (HDRCs)
• Clinical Research Facilities (CRFs)
• Patient Safety Research Collaborations (PSRCs)
• Translational Research Collaborations (TRCs)
• Academic Health Science Centres (AHSCs)
• university teaching hospitals and all trusts that deliver research activity
• primary care organisations, including GP practices, that deliver research activity
• higher education institutions (HEIs)
• local authorities
• social care partners
• Local Government Association
• local and national charities that fund, collaborate in or support participation in research
• research and development offices in providers or CSUs, including primary care providers and ambulance, community and mental health trusts, and those in the VCSE sector
• UKRD members
• NHS subnational secure data environments for research
• NHS R&D Forum
• NHS Genomic Medicines Service Research Collaborative
• NHS Knowledge and Library Services
• Academic Health Science Networks (AHSNs) are often well linked with research organisations and infrastructure as part of their roles in development, adoption and spread of innovation.

Annex 2 – Public health and social care research

Public health research investigates issues that impact at a population rather than an individual level. This can be done within the NHS with system-level studies, such as secondary prevention of cardiovascular disease and examining the impact on health inequalities of changes to the NHS resource allocation formula, and outside the NHS for the wider determinants of health such as air quality, transport systems and housing. There is a substantial body of public health evidence for the clinical and cost effectiveness of prevention, health protection, health service redesign and addressing health inequalities.

Social care research aims to improve the lives of children and adults who need to draw on personal or practical care and support, and family members or other unpaid carers. It can include research around the introduction, use and impact of technologies, and changing social care interventions, policies and practice. Social care research also examines issues pertaining to the safeguarding of adults and children and workforce, commissioning of services, and questions about organisational and professional practice, including decision-making, training and the quality of care.

Publication reference: PR1662

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Ethical issues in health and social care research

From the book ethics.

• Robert Stanley and Susan McLaren

This chapter reviews events that have led to the development of codes of conduct and guidance, together with requirements to conduct ethical reviews of research involving human subjects. An overarching aim of ethical review is to protect the rights, health, and well-being of research participants, utilising an approach that is sensitive to diversity, cultural values, and the social and cultural context in which research is conducted. Ethical principles of respect for autonomy, beneficence, non-maleficence, and justice are examined and applied to the research context as a basis for decision making. Characteristics of vulnerable groups and special considerations that can apply to their participation in research are considered. Recent developments in the arena of research governance frameworks, intended to provide accountability for the moral acceptability, scientific quality, and safety of research, are also briefly reviewed.

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UK Policy Framework for Health and Social Care Research

This policy framework sets out principles of good practice in the management and conduct of health and social care research in the UK. 

These principles protect and promote the interests of patients, service users and the public in health and social care research, by describing ethical conduct and proportionate, assurance-based management of health and social care research, so as to support and facilitate high-quality research in the UK that has the confidence of patients, service users and the public.

It is for organisations and individuals that have responsibilities for health and social care research. This includes funders, sponsors, researchers and their employers, research sites and care providers.

The policy framework applies to health and social care research involving patients, service users or their relatives or carers. This includes research involving them indirectly, for example using information that the NHS or social care services have collected about them.

The Health Research Authority and the health departments in Northern Ireland, Scotland and Wales have developed the policy framework following  public consultation . It replaces the separate Research Governance Frameworks in each UK country with a single, modern set of principles for the whole UK.

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EDITORIAL article

Editorial: social determinants and psychosocial factors that impact on health status.

• 1 Universidade de Vigo, Grupo de Estudos en Traballo Social: Investigación e Transferencia (GETS-IT), Ourense, Spain
• 2 Social Work Studies Group: Research and Transfer (GETS-IT), Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo, Spain
• 3 Department of Psychiatry, Radiology, Public Health, Nursing and Medicine, University of Santiago de Compostela, Santiago de Compostela, Spain
• 4 Institute of Education at the University of Minho, Universidade do Minho, Braga, Portugal

Editorial on the Research Topic Social determinants and psychosocial factors that impact on health status

Historically, several conceptual frameworks have been proposed to explain the determinants affecting the health-disease continuum. All of them considered individual variables, lifestyle, and health systems, but also contextual variables. Currently, there is consensus on the importance of the impact of social conditions, such as working conditions, socio-environmental setting, income level, access to education, or political-economic variables that play a crucial role in determining the health status of the population. To address these concerns, the World Health Organization (WHO) defines the social determinants of health as the “structural factors and living conditions that are responsible for much of the health inequities (…). The term ≪social determinants≫ summarizes the set of social, political, economic, environmental, and cultural factors that have a strong influence on health status” ( WHO, 2008 ).

All countries have social inequalities in health, and they occur gradually along the social scale. The impact of these disparities is significant, and their trend is increasing. However, it seems that the greater the social disadvantage in any of the social determinants, the worse the health outcomes, and the worse when several axes of inequality concur ( Ruiz et al., 2022 ). However, there is enough evidence to demonstrate how the implementation of appropriate health and social policies can reduce these health disparities ( Benach, 1997 ), establishing strategies that consider these social inequalities in a multidisciplinary manner and focusing actions on primary interventions and health promotion ( De La Guardia and Ruvalcaba, 2020 ).

This set of social factors and exposure to them condition the health status of the individual and his or her social participation in the community. From variables linked to the labor context, such as unemployment, which is associated with greater cardiovascular risk factors, especially in young people ( Vancea and Utzet, 2017 ), or mental illness ( Frasquilho et al., 2015 ). The physical environment in which we live also influences our state of health and enhances (or diminishes) the healthy lifestyle habits that individuals develop ( Twohig-Bennett and Jones, 2018 ). Also, the public policies implemented have led to a decrease in citizen participation, as well as to the exclusion of many people, depriving them of the right to health ( Falkenbach and Greer, 2018 ). Other variables linked to the generation of social inequalities in health deserve special attention, such as gender or ethnicity. When we refer to gender, we are not referring to physical differences related to sex, but to the social inequalities in health that gender entails, such as inequalities to enjoy good health. These inequalities seem to persist even in crises, such as the COVID-19 pandemic ( Zwar et al., 2023 ). This Research Topic aims to shed light on how psychosocial and contextual factors determine people's wellbeing and quality of life.

From a cultural perspective, Li et al. found gender differences in binge eating behavior. Their results indicated that, in Chinese culture, body dissatisfaction and self-acceptance, independently or through a serial form, mediate gender differences in binge eating behavior. Shin and Park also addressed gender, in this case, linked to the existence and quality of social networks, examining their associations with various impacts on physical and mental health and analyzing the results according to gender. The findings suggest that women benefit more from support networks and are also more vulnerable to network deficits.

The family and residential context was also a focus of interest. A narrative review ( Faraji et al. ) updates the available evidence on how different family-related factors are related to the fear of cancer recurrence among survivors. This research made it possible to categorize them into four factors: partner-related, parenting-related, family-related, and social interactions. Their categorization makes it possible to construct a more comprehensive model that helps healthcare personnel improve the design of family interventions. The family and communication with their cancer patient relatives was the subject of interest for Naghavi et al. . They analyzed the general and individual attitudes of caregivers and non-caregivers regarding communication with cancer patients. Their results noted the contrast between positive attitudes toward direct communication and the actual practices observed. They suggest the creation of protocols for conveying bad news in a culturally competent manner and facilitating the patient's need to express their emotions and needs. Melero et al. were concerned with the psychological wellbeing of adults raised in foster families. They found that there is no direct relationship between aging and a decrease in psychological wellbeing. Increasing age is only related to lower psychological wellbeing in the case of a lack of mastery of certain developmental tasks of adulthood.

Several studies addressed psychosocial variables closely linked to contextual elements of the health systems. Bayraktar and Ozkan studied posttraumatic growth, coping, and illness perceptions in cancer patients. They highlight the need to strengthen positive coping methods and implement interventions targeting the cognitive aspects of their illness perceptions. Their results indicate that the relevant variables affecting posttraumatic growth in cancer patients in different cultures do not change. Jeon and Noh analyze psychosocial factors associated with health behaviors in older pregnant women to identify which behaviors promote and harm health in the Korean context. Among the psychosocial factors that explained prenatal health-promoting behaviors were maternal-fetal attachment and the social atmosphere of pregnancy stress. In contrast, artificial conception, multipara, and maternal role stress influenced prenatal health-damaging behaviors.

The instruments used in the health system have been another focus of interest. Norouzkhani et al. were concerned about the information and support provided to patients with inflammatory bowel disease. Through a Delphi consensus study, they generated a questionnaire of 100 items grouped into three categories: support needs, sources of information, and specific information needs. Buki et al. warn of the difficulties in assessing psychosocial factors associated with colorectal cancer. As a solution, they develop and validate the psychometric properties of the Colorectal Cancer Literacy Scale-Uruguay Version, that assess culturally based factors that influence colorectal cancer screening behaviors.

Abudoush et al. analyze the lived experiences of chronic pain in Arabic-speaking populations and its relationship with psychosocial processes such as care, coping, or social support. It addresses realities in sociocultural settings other than the Western setting and provides conclusions that justify the development of culturally sensitive interventions. Zhou et al. also considered ethnic differences, analyzing the role of perceived discrimination as a mediator between cultural identity and mental health symptoms in adults. They highlight the need to consider racial, ethnic, and socioeconomic inequalities, as well as cultural identity and bias, in mental health research and interventions.

Concern for the more structural social determinants, specifically those affecting the health and wellbeing of the elderly, was addressed by Zhang et al. . They refer to the following primary structural indicators: socioeconomic development factors, political factors, environmental factors, and cultural factors. Their findings show that individual social factors alone are insufficient to achieve high levels of health in older adults.

This Research Topic covers a wide range of social determinants and psychosocial factors that affect health and wellbeing, including socioeconomic context, culture, family, and gender, among others. The scientific contributions of the subject suggest that approaches to health interventions should consider these social variables that have an impact on health. The findings provide important information for families, patients, healthcare professionals, and policymakers.

Author contributions

RG-R: Conceptualization, Supervision, Writing – original draft, Writing – review & editing. MG-C: Conceptualization, Writing – review & editing. TV: Conceptualization, Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Benach, J. (1997). La desigualdad social perjudica seriamente la salud. Gaceta Sanit. 11, 255–258. doi: 10.1016/S0213-9111(97)71304-9

PubMed Abstract | Crossref Full Text | Google Scholar

De La Guardia, M. A., and Ruvalcaba, J. C. (2020). Health and its determinants, health promotion and health education. J. Negat. No Posit. Results 5, 81–90. doi: 10.19230/10.19230/jonnpr.3215

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Falkenbach, M., and Greer, S. L. (2018). Political parties matter: the impact of the populist radical right on health. Eur. J. Public Health 28, 15–18. doi: 10.1093/eurpub/cky157

Frasquilho, D., Matos, M. G., Salonna, F., Guerreiro, D., Storti, C. C., Gaspar, T., et al. (2015). Mental health outcomes in times of economic recession: a systematic literature review. BMC Public Health 16:115. doi: 10.1186/s12889-016-2720-y

Ruiz, M., Aginagalde, A. H., and Del Llano, J. E. (2022). The social determinants of health in Spain (2010-2021): an exploratory review of the literature. Rev. Española Salud Pública 96:e202205041. Available online at: https://www.sanidad.gob.es/biblioPublic/publicaciones/recursos_propios/resp/revista_cdrom/VOL96/REVISIONES/RS96C_202205041.pdf

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Twohig-Bennett, C., and Jones, A. (2018). The health benefits of the great outdoors: a systematic review and meta-analysis of greenspace exposure and health outcomes. Environ. Res. 166, 628–637. doi: 10.1016/j.envres.2018.06.030

Vancea, M., and Utzet, M. (2017). How unemployment and precarious employment affect the health of young people: a scoping study on social determinants. Scand. J. Public Health 45, 73–84. doi: 10.1177/1403494816679555

WHO (2008). Comisión Sobre Determinantes Sociales de la Salud. Informe de la secretaría. Available online at: https://apps.who.int/gb/ebwha/pdf_files/EB124/B124_9-sp.pdf (accessed March 22, 2024).

Zwar, L., König, H.-H., and Hajek, A. (2023). Gender differences in mental health, quality of life, and caregiver burden among informal caregivers during the second wave of the COVID-19 Pandemic in Germany: a representative, population-based study. Gerontology 69, 149–162. doi: 10.1159/000523846

Keywords: social determinants, psychosocial factors, health, wellbeing, behavior, health education

Citation: González-Rodríguez R, Gandoy-Crego M and Vilaça T (2024) Editorial: Social determinants and psychosocial factors that impact on health status. Front. Psychol. 15:1405206. doi: 10.3389/fpsyg.2024.1405206

Received: 22 March 2024; Accepted: 09 April 2024; Published: 26 April 2024.

Edited and reviewed by: Changiz Mohiyeddini , Oakland University William Beaumont School of Medicine, United States

Copyright © 2024 González-Rodríguez, Gandoy-Crego and Vilaça. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Rubén González-Rodríguez, rubgonzalez@uvigo.gal

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Ethics: Contemporary challenges in health and social care

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While ethics has been addressed in the health care literature, relatively little attention has been paid to the subject in the field of social care. This book redresses the balance by examining theory, research, policy, and practice in both fields. The analysis is set within the context of contemporary challenges facing health and social care, not only in Britain but internationally. Contributors from the United Kingdom, United States, and Australia consider ethical issues in health and social care research and governance; inter-professional and user perspectives; ethics in relation to human rights, the law, finance, management, and provision; key issues of relevance to vulnerable groups such as children and young people; those with complex disabilities, older people, and those with mental health problems; and lifecourse issues – ethical perspectives on a range of challenging areas from new technologies of reproduction to euthanasia.

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2021 National Healthcare Quality and Disparities Report [Internet]. Rockville (MD): Agency for Healthcare Research and Quality (US); 2021 Dec.

2021 National Healthcare Quality and Disparities Report [Internet].

Disparities in healthcare.

Healthcare delivery is not experienced equitably by all populations. A healthcare disparity is a difference between population groups in the way they access, experience, and receive healthcare. Factors that influence healthcare disparities include social, economic, environmental, and other disadvantages, 1 , 2 some of which are explored in this report.

Unfortunately, Americans too often do not receive care they need, or they receive care that causes harm. Care can be delivered too late or without full consideration of a patient’s preferences and values. Many times, our healthcare system distributes services inefficiently and unevenly across populations. Some Americans receive worse care than others. These disparities may occur for a variety of reasons, including differences in access to care, social determinants, provider biases, poor provider-patient communication, and poor health literacy.

• Research Framework for Health Disparities

The Research Framework in Exhibit 1 was developed by the National Institutes of Health (NIH) National Institute on Minority Health and Health Disparities (NIMHD). This framework is based on an evolving conceptualization of factors relevant to the understanding and promotion of minority health and to the understanding and reduction of health disparities.

The framework serves as a vehicle for encouraging NIH-supported research that addresses the complex and multifaceted nature of minority health and health disparities. This research needs to span different domains of influence (Biological, Behavioral, Physical/Built Environment, Sociocultural Environment, Healthcare System) and different levels of influence (Individual, Interpersonal, Community, Societal) within those domains.

The framework also provides a classification structure that facilitates analysis of the NIMHD minority health and health disparities research portfolios to assess progress, gaps, and opportunities. Examples of factors are provided within each cell of the framework (e.g., Family Microbiome within the Interpersonal-Biological cell). These factors are not intended to be exhaustive. Health disparity populations, as well as other features of this framework, may be adjusted over time.

NIMHD Research Framework. * Health Disparity Populations: Race/ethnicity, low socioeconomic status, rural, sexual/gender minority. Other Fundamental Characteristics: Sex/gender, disability, geographic region.

• Role of Research Framework in the NHQDR

The NHQDR reports on progress and opportunities for improving healthcare quality and reducing healthcare disparities. The NIMHD Minority Health and Health Disparities Research Framework highlights factors ranging from individual biology and behavior to social structure that affect disparities. To successfully reduce disparities, it is necessary to address all these factors.

All Americans should have equitable access to high-quality care. Instead, racial and ethnic minorities and poor people often face more barriers to care and receive poorer quality of care when they can get it. 3 In this report, measures were analyzed to assess disparities both by socioeconomic and cultural groups and by settings of care.

An increasing number of healthcare organizations and payers are experimenting with strategies to identify needs and connect patients to resources that address identified needs. The goals are to improve health outcomes, reduce avoidable use of costly health services, and improve health equity. 4

Inequitable health outcomes result from inequities in the distribution of or access to resources that promote good health outcomes. Differences refer to outcomes that result from biological risk or other factors that are not a matter of policy or discrimination in access. A difference may become a disparity when some subgroups and not others are given access to resources to manage their differential risk from biology or other factors and the groups without access have poorer outcomes. Thus, differences and disparities may have different determinants requiring different forms of intervention. 5

The Disparities in Healthcare section of the 2021 NHQDR examines the best and worst performing quality measures among the measures used in the report. These quality measures are analyzed in this section of the report by race and ethnicity, income, insurance status, and residence location. While these categories are broad, each section begins with key definitions to orient readers and includes analyses showing quality measure performance in the latest data year and analyses showing whether disparities were widening or narrowing over time.

More information on the measures included in this section of the report is available through the NHQDR Data Query Tool ( https://datatools.ahrq.gov/nhqdr ). The tool also allows readers to stratify NHQDR data by variables such as education, sex, and age, where available.

• Racial and Ethnic Disparities

Researchers, patients, providers, and policymakers have worked to identify, understand, and eliminate the disparities experienced by different racial and ethnic groups across the healthcare system. In 1985, the Department of Health and Human Services published the Report of the Secretary’s Task Force on Black and Minority Health (Heckler Report), which marked the first comprehensive study of racial and minority health by the U.S. government. 6 Since then, the Department, along with other stakeholders, has continued this work, including throughout the NHQDR. The growing evidence base shows that patients of different racial and ethnic groups experience quality of care inequitably and disparately. 7 , 8

• American Indian or Alaska Native (AI/AN). A person having origins in any of the original peoples of North and South America (including Central America) and maintains tribal affiliation or community attachment.
• Asian. A person having origins in any of the original peoples of the Far East, Southeast Asia, or Indian subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam.
• Black or African American. A person having origins in any of the Black racial groups of Africa. Terms such as “Haitian” can be used in addition to “Black or African American.”
• Hispanic or Latino. A person of Cuban, Mexican, Puerto Rican, Central or South American, or other Spanish culture or origin, regardless of race. The term “Spanish origin” can be used in addition to “Hispanic or Latino.”
• Native Hawaiian/Pacific Islander (NHPI). A person having origins in any of the original peoples of Hawaii, Guam, Samoa, or other Pacific Islands.
• White. A person having origins in any of the original peoples of Europe, the Middle East, or North Africa.
• Largest disparities for a single data year, focusing on the most recent data year.
• Trends in quality of care (number of measures improving, not changing, and worsening) for the population group.
• Comparison with the reference group, focusing on the change in the gap between the two groups (gap is narrowing, widening, and not changing).
• Overview of Racial and Ethnic Disparities

Figure 1 displays the number of quality measures for which each racial or ethnic group experienced better, same, or worse quality care compared with White populations in the latest data year. Figure 2 shows the number of quality measures with disparities at baseline that were narrowing (improving), widening (worsening), or not changing. xix

Number and percentage of quality measures for which members of selected groups experienced better, same, or worse quality of care compared with White people for the most recent data year, 2015, 2017, 2018, or 2019. Key: n = number of measures; AI/AN = (more...)

• Black populations received worse care than White populations for 43% of quality measures ( Figure 1 ).
• AI/AN populations received worse care than White populations for 40% of quality measures.
• Hispanic populations received worse care than non-Hispanic White populations for 36% of quality measures.
• Asian and NHPI populations received worse care than White populations for about 30% of quality measures but Asian populations also received better care for about 30% of quality measures.

Number and percentage of quality measures with disparity at baseline for which disparities related to race and ethnicity were improving, not changing, or worsening over time, 2000 through 2015, 2016, 2017, 2018, or 2019. Key: n = number of measures; AI/AN (more...)

• For all racial and ethnic groups, at least 90% of measures showed no change in disparities ( Figure 2 ).
• Three measures showed improvement in disparities between AI/AN populations and White populations.
• Black populations and NHPI populations each had two measures that showed improvement in disparities.
• Two measures showed improvement between Hispanic populations and non-Hispanic White populations.
• One measure for Asian populations showed improvement in disparities: People age 13 and over living with HIV who know their HIV status.
• One measure for Asian populations showed worsening disparities: Home health care patients whose management of oral medications improved.
• One measure for Black populations showed worsening disparities: Emergency department visits for asthma, ages 2–19.
• No worsening disparities were observed for AI/AN, Hispanic, or NHPI populations.
• Fewer quality measures are available for select subpopulations overall.
• Disparities for American Indian and Alaska Native Populations

This section presents disparities in quality of care and, new in 2021, access to care for American Indian and Alaska Native (AI/AN) populations. To provide context, findings for other ethnic and racial populations may be included. Additional details on disparities of care for other priority populations are presented in population-specific sections of this report.

Snapshot of Disparities in Access to Care

Number and percentage of access measures for which members of selected racial groups experienced better, same, or worse access to care compared with White people, 2017–2019. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific (more...)

• AI/AN people had worse access to care than White people for 50% of access measures ( Figure 3 ).

Disparities in Quality of Care

American Indian and Alaska Native people experienced worse quality care compared with White people for 40% of all quality measures and 63% of Person-Centered Care measures.

Number and percentage of quality measures for which American Indian and Alaska Native people experienced better, same, or worse quality of care compared with White people for the most recent data year, 2015, 2017, 2018, or 2019. Key: n = number of measures. (more...)

• Data for the most recent year show that quality care was worse for AI/AN people than for White people for 40% of all quality measures and that quality was better for AI/AN people than for White people for 18% of all quality measures ( Figure 4 ).
• Hospital patients who received influenza vaccination.
• Patients with colon cancer who received surgical resection of colon cancer that included at least 12 lymph nodes pathologically examined.
• New HIV cases per 100,000 population age 13 and over.

Influenza Vaccination

Overall, adjusting for age, Black people had the highest flu-associated hospitalization rates across 10 flu seasons, followed by AI/AN and Hispanic people, with similar trends for intensive care admission rates. Among AI/AN children, rates were 3 to 3.5 times higher for all three severe flu-related outcomes. 9

Current clinical guidelines show that people who are 6 months or older should receive an annual flu vaccine, but not all patients can access vaccines or treatment if they become ill. CDC details preventive strategies ( https://www.cdc.gov/flu/prevent/index.html ) to protect against the flu. Moreover, current research shows that influenza vaccination even provides effective flu protection in patients with chronic obstructive pulmonary disease (COPD). 10

Hospital patients who received influenza vaccination, 2018. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable (more...)

• In 2018, 81.6% of AI/AN hospital patients received influenza vaccinations compared with 92.7% of White patients ( Figure 5 ).
• The 2016 achievable benchmark was 96.6%.
• The top 10% of states that contributed to the achievable benchmark were Florida, Indiana, Maine, Utah, and Virginia.

Patients With Colon Cancer

Healthy People 2020 objectives include reducing the colorectal cancer incidence rate to 40 per 100,000 people and the mortality rate to 14.5 per 100,000 people. 11 Healthy People 2020 also includes an objective for colorectal cancer screening. The USPSTF expanded the recommended ages for colorectal cancer screening to 45 to 75 years (previously, it was 50 to 75 years). The USPSTF continues to recommend selectively screening adults ages 76 to 85 years for colorectal cancer. 12

The American Cancer Society’s newest guidelines recommend that colorectal cancer screenings begin at age 45. The recommended age was lowered from 50 to 45 because colorectal cancer cases are on the rise among young and middle-age people. 13

Patients with colon cancer who received surgical resection of colon cancer that included at least 12 lymph nodes pathologically examined, 2017. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: The benchmark (more...)

• In 2017, the percentage of patients with colon cancer who received surgical resection of colon cancer that included examination of at least 12 lymph nodes was lower for AI/AN people (83.7%) compared with White people (93%) ( Figure 6 ).
• The 2015 achievable benchmark was 95.5%.
• The top 10% of states that contributed to the achievable benchmark were District of Columbia, Maine, Massachusetts, Rhode Island, and Vermont.

New HIV Infections

Recent CDC data show new HIV infections fell 8% from 2015 to 2019, after a period of general stability in new infections in the United States. 14 AI/AN people represent about 1.3% of the U.S. population and less than 1% (186) of the HIV diagnoses in 2018 in the United States and dependent areas. 15

It is important for everyone to know their HIV status. People who do not know they have HIV cannot take advantage of HIV care and treatment and may unknowingly pass HIV to others.

The United States has 574 federally recognized AI/AN tribes and many different languages. Meaningful engagement with tribal nations is critically important in creating culturally appropriate prevention programs to reduce HIV transmission.

Poverty, including limited access to high-quality housing, directly and indirectly increases the risk of HIV infection and affects the health of people who have and are at risk for HIV infection. Additional structural factors that influence risks of HIV infection in tribal communities are high rates of poverty, lower levels of education, unemployment, and lack of health insurance.

New HIV cases per 100,000 population age 13 and over, 2019. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable (more...)

• In 2019, the percentage of new HIV cases was higher for AI/AN people (10.5%) compared with White people (5.3%) ( Figure 7 ).
• The 2015 achievable benchmark was 4.2 per 100,000 population.
• The top 10% of states that contributed to the achievable benchmark were Idaho, Iowa, Maine, West Virginia, and Wisconsin.
• Barriers to Care.
• Sensitivity of the Provider.
• Assessment.
• Encounters.

Trends in Quality of Care for American Indian and Alaska Native Populations

Number and percentage of all quality measures that were improving, not changing, or worsening over time, total and by priority area, from 2000 to 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, or 2019. Key: n = number of measures. Note: For each (more...)

• Among the 116 quality measures with data for AI/AN people, 53 (46%) were improving, 55 (47%) were not changing, and 8 (7%) were getting worse from 2000 through 2019 ( Figure 8 ).
• Effective Treatment (52%) and Healthy Living (55%) showed the most improvement.

Changes in Disparities for American Indian and Alaska Native Populations

Number and percentage of quality measures with disparity at baseline for which disparities between AI/AN people and White people were improving, not changing, or worsening over time, total and by priority area, from 2000 to 2010, 2011, 2012, 2013, 2014, (more...)

• Disparities between AI/AN people and White people did not change for most of the quality measures from 2000 through 2019. Of 40 quality measures with a disparity at baseline, 37 (93%) were not changing ( Figure 9 ).
• Adjusted incident rates of end stage renal disease (ESRD) due to diabetes per million population.
• Children ages 2–17 for whom a health provider gave advice within the past 2 years about the amount and kind of exercise, sports, or physically active hobbies they should have.
• Children ages 2–17 for whom a health provider gave advice within the past 2 years about healthy eating.
• No Affordable Care measures with data for AI/AN people were available.

End Stage Renal Disease Due to Diabetes

Diabetes is the leading cause of kidney disease in the United States. According to the National Institute of Diabetes and Digestive and Kidney Diseases, White people experience diabetes and kidney disease at a lower rate than other racial and ethnic groups. 16 , 17

Adjusted incident rates of end stage renal disease due to diabetes per million population, 2001–2018 (lower rates are better). Key: AI/AN = American Indian or Alaska Native.

• From 2001 to 2018, the disparity between AI/AN people and White people decreased for the adjusted incident rate of ESRD due to diabetes. For AI/AN people, the rate decreased from 526 per million population to 273.1 per million, and for White people, there were no statistically significant changes (from 133.3 per million to 152.2 per million) ( Figure 10 ).
• Disparities have been persistent, with AI/AN people having higher incident rates of ESRD due to diabetes than White people in all years.
• Disparities for Asian Populations

This section presents disparities in quality of care and, new in 2021, access to care for Asian populations. To provide context, findings for other ethnic and racial populations may be included. Additional details on disparities of care for other priority populations are presented in population-specific sections of this report.

Number and percentage of access measures for which members of selected racial groups experienced better, same, or worse access to care compared with White people, 2017–2019. Key: AI/AN = American Indian or Alaska Native; NHPI = Native Hawaiian/Pacific (more...)

• Asian people had worse access to care than White people for 29% of access measures and better access to care for 14% of access measures ( Figure 11 ).

Snapshot of Disparities in Quality of Care

For the most recent year, Asian people experienced worse quality care than White people for 28% of all quality measures.

Number and percentage of quality measures for which Asian people experienced better, same, or worse quality of care compared with White people for the most recent data year, 2015, 2017, 2018, or 2019. Key: n = number of measures. Note: The difference (more...)

• Data for the most recent year show that quality care was better for Asian people than for White people on 29% of all quality measures, the same for 43%, and worse for 28% ( Figure 12 ).

Largest Disparities

• Adults with limited English proficiency and usual source of care (USC) whose USC had language assistance.
• Adults who reported that home health care providers always treated them with courtesy and respect in the last 2 months of care.
• Adults who reported that home health care providers always treated them as gently as possible in the last 2 months of care.

Providers With Language Assistance

Current research shows that Asian people continue to experience health disparities in several quality areas, including patient-centered care and satisfaction. 18 Adults who have limited English proficiency may experience disparities in their care and gaps in communication with their healthcare team. 19

According to the Migration Policy Institute, in 2015, an estimated 25.9 million individuals living in the United States reported having limited English proficiency. 20 “More than one in four people aged 5 and over with LEP are born in the U.S.” 21 Language assistance such as access to translation services, health education materials written in a known language, and other resources are required by law, but not all patients have access to these services at their usual source of care. 22

Adults with limited English proficiency and a usual source of care (USC) whose USC had language assistance, 2018.

• In 2018, Asian people with limited English proficiency and a usual source of care were less likely than White people to have a USC with language assistance (68.5% compared with 94.0%) ( Figure 13 ).

The Limited English Proficiency website 23 offers a repository of resources collated by the Department of Justice to support improved communication with patients. AHRQ has also established a Limited English Proficiency module as part of its TeamSTEPPS ® training that shows the importance of language assistance services in keeping patients safe and avoiding adverse events. 24

Treatment by Home Health Care Providers

Home health care providers are committed to delivering high-quality and compassionate care and services to patients in a respectful manner that supports each patient’s dignity. Home health performance is examined through several types of quality measures that look at areas such as efficiency, patient safety, and patient-centered care. Evaluation of patient experience of care is conducted with the Consumer Assessment of Healthcare Providers and Systems Home Health Care Survey. 25

Adults who reported that home health care providers always treated them with courtesy and respect in the last 2 months of care, 2019. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: The benchmark calculation (more...)

• In 2019, the percentage of adults who reported that home health providers always treated them with courtesy and respect in the last 2 months was lower for Asian people (85.5%) compared with White people (94.4%) ( Figure 14 ).
• The 2015 achievable benchmark was 95.0%.
• The top 10% of states that contributed to the achievable benchmark were Alabama, Louisiana, Mississippi, Rhode Island, South Carolina, and West Virginia. Guam was not included in the benchmark but its percentage was in the benchmark range.

Adults who reported that home health care providers always treated them as gently as possible in the last 2 months of care, 2019. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: The benchmark calculation takes (more...)

• In 2019, 80.6% of Asian adults reported that home health providers always treated them as gently as possible compared with 91.1% of White adults ( Figure 15 ).
• The 2015 achievable benchmark was 92.5%.
• The top 10% of states that contributed to the achievable benchmark were Alabama, Kentucky, Louisiana, Mississippi, and West Virginia.

Trends in Quality of Care for Asian People

Number and percentage of all quality measures that were improving, not changing, or worsening over time, total and by priority area, from 2000 to 2019. Key: n = number of measures. Note: For each measure with at least four data points over time, the estimates (more...)

• Across the 120 measures of healthcare quality tracked in the report for Asian populations, 58% were improving, 38% were not changing, and 4% were getting worse from 2000 to 2019 ( Figure 16 ). xx
• Affordable Care (no measures) and Effective Treatment (41% of measures) showed the least improvement.
• Healthy Living (66%) and Person-Centered Care (62%) showed the most improvement.

Changes in Disparities for Asian People

Number and percentage of quality measures with disparity at baseline for which disparities between Asian people and White people were improving, not changing, or worsening over time, total and by priority area, from 2000 to 2019. Key: n = number of measures. (more...)

• From 2000 through 2019, disparities in quality of care between Asian people and White people remained the same for most measures. Of 41 quality measures with a disparity at baseline, disparities were not changing for 39 (95%) ( Figure 17 ).
• One measure showed narrowing disparities: People age 13 and over living with HIV who know their HIV status.
• One measure showed a widening disparity: Home health patients whose management of oral medications improved.
• No Affordable Care measures with data for Asian people were available.

Knowledge of HIV Status

HIV and other related stigmas hinder patients from getting tested, which may delay treatment and affect a patient’s health and quality of life. 26 According to CDC, people ages 13–24 are less likely to know their HIV status. 27 Accurate estimates of new HIV infection rates are crucial for preventing the spread of the disease.

People age 13 and over living with HIV who know their HIV status, 2010–2019. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: The benchmark calculation takes the average of the top 10% of states with (more...)

• Data from 2010 to 2019 show that the disparity between Asian people and White people is narrowing as the percentage of Asian people (68.1% to 86.6%) who know their HIV status increased at a faster rate compared with White people (85.8% to 89.2%) ( Figure 18 ).
• The 2015 achievable benchmark was 90.2%. At the current rate of increase, overall, the benchmark could be achieved in 2 years.
• The top 10% of states that contributed to the achievable benchmark were Connecticut, District of Columbia, Massachusetts, New Hampshire, and New York. Puerto Rico was not included in the benchmark but its percentage was in the benchmark range.

Oral Medication Management

The ability to perform daily activities, such as taking medications correctly, is important to the health status and quality of life of people living in the community. Taking too much or too little can keep the drugs from working properly and may cause unintended harm, including death. The home health team can help teach patients ways to organize medications and to take them properly. If patients get better at taking medications correctly, it means the home health team is doing a good job teaching patients how to take their drugs and about the possible harm if they do not follow these instructions.

Specific items that should be discussed include all the prescriptions and other medications the patient takes, allergic or other adverse reactions to drugs experienced in the past, and actions to take if a medication is not working. This measure shows how often the home health team helped patients get better at taking their medications correctly (including prescription medications, over-the-counter medications, vitamins, and herbal supplements). Only medications the patient takes by mouth are considered.

Home health care patients whose management of oral medications improved, 2013–2018. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander.

• From 2013 to 2018, the percentage of home health care patients whose management of oral medications improved increased for both Asian and White populations. The percentage for White people, however, improved faster than for Asian people, so the disparity between the groups increased ( Figure 19 ).
• The 2015 achievable benchmark was 66.2%. At the current rate of increase, the benchmark could be achieved by Asian people in 2 years; White people have already achieved the benchmark.
• The top 10% of states that contributed to the achievable benchmark were Delaware, Mississippi, New Jersey, North Dakota, and South Carolina.
• Disparities for Black Populations

This section presents disparities in quality of care and, new in 2021, access to care for Black populations. To provide context, findings for other ethnic and racial populations may be included. Additional details on disparities of care for other priority populations are presented in population-specific sections of this report.

• Black people had worse access to care than White people for 53% of access measures ( Figure 20 ).

In 2019, Black people were more than 8 times as likely as White people to have new HIV cases.

Number and percentage of quality measures for which Black people experienced better, same, or worse quality of care compared with White people for the most recent data year, 2015, 2017, 2018, or 2019. Key: n = number of measures. Note: The difference (more...)

• Data for the most recent year show that quality of care was better for Black people than for White people on only 11% of all quality measures and that quality was better for White people than for Black people on 43% of all quality measures ( Figure 21 ).
• For Patient Safety, quality was better for Black people than for White people for 17% of the measures and better for White people than for Black people for 38% of the measures.
• HIV infection deaths per 100,000 population.
• Hospital admissions for hypertension per 100,000 population, adults age 18 and over.

New HIV Cases

According to CDC research, in 2018, Black people accounted for 13% of the nation’s population but represented 42% of all new HIV cases. Most of these cases affect Black male adolescents and adults. 28 The Office of Minority Health reports that in 2019, African Americans were 8.1 times more likely to be diagnosed with HIV infection compared with the White population. 29

New HIV cases per 100,000 population age 13 and over, 2019 (lower rates are better). Note: Black and White are non-Hispanic. Hispanic includes all races. The benchmark calculation takes the average of the top 10% of states with statistically reliable (more...)

• In 2019, Black people reported 45.3 new HIV cases per 100,000 population for people age 13 and over compared with 5.3 per 100,000 cases for White people ( Figure 22 ).

The Department of Health and Human Services has committed to “reducing new infections by 75 percent in the next five years and by 90 percent in the next ten years.” 30 The Department’s website www.hiv.gov also outlines key resources for patients, provides data, and details programs supporting a federal response to the epidemic in the United States.

Deaths From HIV Infection

HIV mortality disproportionately affects some racial and ethnic groups more than others. According to CDC data, in 2019, HIV was the sixth leading cause of death for Black men ages 25–34 and seventh for Black women ages 35–44. 31

HIV infection deaths per 100,000 population, 2018 (lower rates are better). Key: AI/AN = American Indian or Alaska Native. Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories are (more...)

• In 2018, Black people had 6.2 HIV infection deaths per 100,000 population compared with 0.9 per 100,000 cases for White people ( Figure 23 ). These cases represent mortality for which HIV was the primary cause of death.
• The 2015 achievable benchmark was 0.8 per 100,000 population.
• The top 10% of states that contributed to the achievable benchmark were Kansas, Kentucky, Minnesota, Missouri, Ohio, and Washington.

Federal efforts to reduce mortality include promotion of treatment therapies, such as antiretroviral therapy, pre-exposure prophylaxis, and postexposure prophylaxis. 32 Several HHS agencies provide a federal response to the HIV epidemic in the United States, including the Health Resources and Services Administration (HRSA) HIV/AIDS Bureau, which administers the Ryan White HIV/AIDS Program (RWHAP). This is the largest federal program focused exclusively on providing HIV care and treatment to patients with inadequate or no insurance. Through RWHAP’s partnerships, nearly 568,000 people receive care annually. 33

Federal efforts to prevent HIV infections include the High-Impact Prevention (HIP) program. HIP is a public health approach to disease prevention in which cost-effective, proven, and scalable interventions are targeted to specific populations based on disease burden. It provides a strategy for using data to maximize the impact of available resources and interventions. The primary goals of HIP are to prevent the largest number of new infections, save life-years, and reduce disparities among populations. In this approach to disease prevention, resources are aligned with disease burden in geographic areas and within populations. 34

Hospital Admissions for Hypertension

Hypertension affects nearly half of all U.S. adults and is responsible for substantial burden of morbidity, mortality, and financial costs on the healthcare system. 35 The cumulative incidence of hypertension by age 55 years was substantially higher for Black men and women compared with White men and women. Based on the 2017 American College of Cardiology/American Heart Association blood pressure guideline definition, 36 75.5% of Black men and 75.7% of Black women developed hypertension compared with 54.5% of White men and 40.0% of White women by age 55 years. 37

Hospital admissions for hypertension per 100,000 population, adults age 18 and over, 2018 (lower rates are better). Key: API = Asian/Pacific Islander. Note: API, Black, and White are non-Hispanic. Hispanic includes all races.

• In 2018, the rate of hospital admissions for hypertension was 212.9 per 100,000 population for Black adults compared with 38.4 per 100,000 cases for White adults ( Figure 24 ).

CDC’s current effort to reduce prevalence and improve control is Hypertension Control Champions. The Million Hearts ® Hypertension Control Champions are clinicians, practices, and health systems that have successfully completed the Million Hearts ® Hypertension Control Challenge. The Challenge is an opportunity for clinicians, practices, and health systems to demonstrate excellence in hypertension control. Hypertension Control Champions must reach 80% control rates among their hypertensive patients.

Trends in Quality of Care for Black People

• Across the 152 measures of healthcare quality tracked in the report for Black people, 49% showed improvement, 45% remained unchanged, and 7% were getting worse from 2000 to 2019 ( Figure 25 ). xxi
• Healthy Living (60% of measures), Care Coordination (44% of measures), Effective Treatment (42% of measures), and Patient Safety (42% of measures) showed more improvement than other priority areas.

Changes in Disparities for Black People

Number and percentage of quality measures with disparity at baseline for which disparities between Black people and White people were improving, not changing, or worsening over time, total and by priority area, 2000–2019. Key: n = number of measures. (more...)

• From 2000 to 2019, disparities between Black people and White people were narrowing in only 3% of measures of quality of care experienced ( Figure 26 ).
• Disparities were not changing for 95% of measures, and disparities were widening for one measure: Emergency department visits for asthma per 10,000 population, ages 2–19.

According to the Office of Minority Health, African American adults are 60 percent more likely than non-Hispanic White adults to have been diagnosed with diabetes by a physician and 3.5 times more likely to be diagnosed with end stage renal disease (ESRD) compared with non-Hispanic White people. During 2018, there were 131,636 newly reported cases of ESRD and diabetes was listed as the primary cause for nearly half (62,012). 38

The U.S. Renal Data System of the National Institute of Diabetes and Digestive and Kidney Diseases tracks cases of ESRD in the ESRD Incident Count.

• Data from 2001 to 2018 show that the disparity between Black people and White people is narrowing, but Black people are still showing a higher rate of ESRD due to diabetes ( Figure 27 ).
• Disparities have been persistent, with Black people having a higher incident rate of ESRD due to diabetes than White people in all years.

New HIV cases per 100,000 population age 13 and over, 2008–2019 (lower rates are better). Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander. Note: All racial groups are non-Hispanic.

• Data from 2008 to 2019 show that the disparity between Black people and White people was narrowing, but Black people are still showing a much higher rate of new HIV cases (45.3 per 100,000 population in 2019) compared with White people (5.3 per 100,000 population in 2019) ( Figure 28 ).
• Disparities for Hispanic Populations

Hispanic groups experienced worse quality care than non-Hispanic White groups for about 40% of Healthy Living measures.

This section presents disparities in quality of care and, new in 2021, access to care for Hispanic populations. To provide context, findings for other ethnic and racial populations may be included. Additional details on disparities of care for other priority populations are presented in population-specific sections of this report.

Snapshot of Disparities in Access to Care for Hispanic Populations

Number and percentage of access measures for which members of selected racial and ethnic groups experienced better, same, or worse access to care compared with White people, 2017, 2018, or 2019. Key: n = number of measures.

• For the most recent year, Hispanic groups had worse access to care than non-Hispanic White groups for 79% of access measures ( Figure 29 ).

Health Insurance

Hispanic populations have the highest uninsured rates of any racial or ethnic group in the United States. Variation occurs among subgroups, with Cubans having the highest percentage and Central Americans the lowest percentage. 39 Disparities in insurance rates by income are also seen in the Hispanic population.

People under age 65 who were uninsured all year, 2018.

• In 2018, poor (20.8%), low-income (21.9%), and middle-income Hispanic people (15.6%) were more likely to be uninsured compared with high-income Hispanic people (7.3%) ( Figure 30 ).

Number and percentage of quality measures for which Hispanic groups experienced better, same, or worse quality of care compared with non-Hispanic White groups for the most recent data year, 2015, 2017, 2018, or 2019. Key: n = number of measures. Note: (more...)

• Data for the most recent year show that quality care was worse for Hispanic groups compared with non-Hispanic White groups for 36% of all quality measures. Quality was better for Hispanic groups than for non-Hispanic White groups on 20% of all quality measures ( Figure 31 ).
• Home health care patients who had influenza vaccination during flu season.
• People without a usual source of care who indicated a financial or insurance reason for not having a source of care.

Approximately 1.2 million people in the United States have HIV and about 13% of them do not know it and need testing. HIV continues to have a disproportionate impact on certain populations, particularly racial and ethnic minorities and gay, bisexual, and other men who have sex with men. New HIV infections declined from 2015 to 2019, after a period of general stability. 40

New HIV cases per 100,000 population age 13 and over, 2019 (lower rates are better). Key: AI/AN = American Indian or Alaska Native; NHPI = Native Hawaiian/Pacific Islander. Note: Racial groups are non-Hispanic. Hispanic includes all races. The benchmark (more...)

• In 2019, the rate of new HIV cases per 100,000 population age 13 and over was higher for Hispanic people (20.0 per 100,000 population) compared with non-Hispanic White people (5.3 per 100,000 population) ( Figure 32 ).
• The top 10% of states that contributed to the benchmark were Idaho, Iowa, Maine, West Virginia, and Wisconsin.
• Federal resources include the Let’s Stop HIV Together campaign (formerly known as Act Against AIDS ), which has resources and partnerships aimed at stopping HIV stigma and promoting HIV testing , prevention , and treatment . This campaign provides Hispanic and Latino people with culturally and linguistically appropriate messages about HIV testing, prevention, and treatment.
• Federal resources also include Ending the HIV Epidemic: A Plan for America , which aims to end the HIV epidemic in the United States by 2030. The plan leverages critical scientific advances in HIV prevention, diagnosis, treatment, and outbreak response by coordinating the highly successful programs, resources, and infrastructure of many HHS agencies and offices.

Influenza Vaccination Among Home Health Care Patients

Medicare defines home health care as a wide range of healthcare services that can be given in the home for an illness or injury. Patients can qualify for this service if they are under the care of a doctor who certifies that they need at least one service such as intermittent skilled nursing care, physical therapy, speech-language pathology, or continued occupational therapy services, and the patient must be home bound.

Home health care is usually less expensive, more convenient, and as effective as care in a hospital or skilled nursing facility. Home health care services include wound care for pressure sores or a surgical wound, patient and caregiver education, intravenous or nutrition therapy, and monitoring of serious illness and unstable health status.

Influenza vaccination is the primary method for preventing the illness and its severe complications, and annual vaccination is recommended for everyone age 6 months and over. 41 All healthcare contacts, including hospitalizations, provide excellent opportunities for vaccination, particularly for people at the highest risk for complications and death from influenza.

Home health care patients who had influenza vaccination during flu season, 2018. Notes: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories are not included in the calculations. Some (more...)

• In 2018, Hispanic home health care patients (90.4%) were less likely than non-Hispanic White home health care patients (96.0%) to receive an influenza vaccine ( Figure 33 ).
• The 2015 achievable benchmark was 94.1%.
• The top 10% of states that contributed to the benchmark were Montana, Nebraska, North Dakota, South Dakota, Vermont, and Wisconsin.

Difficulty Accessing a Usual Source of Care

The AHRQ Medical Expenditure Panel Survey (MEPS) describes usual source of care as the particular medical professional, doctor’s office, clinic, health center, or other place where a person would usually go if sick or in need of advice about his or her health.

According to Healthy People 2020, patients with a usual source of care are more likely to receive recommended preventive services such as flu shots, blood pressure screenings, and cancer screenings. 42

People without a usual source of care who indicate a financial or insurance reason for not having a source of care, 2018 (lower rates are better).

• In 2018, the percentage of people without a usual source of care who indicate a financial or insurance reason for not having a source of care was higher for Hispanic people (26.3%) than for non-Hispanic White people (11.5%) ( Figure 34 ).

Changes in Quality of Care for Hispanic Populations

Number and percentage of all quality measures that were improving, not changing, or worsening over time, total for Hispanic groups and by priority area, from 2000 through 2015, 2017, 2018, or 2019. Key: n = number of measures. Note: For each measure with (more...)

• Of the 120 quality measures with data for Hispanic groups, 66% were improving, 30% were not changing, and 4% were getting worse from 2000 through 2019 ( Figure 35 ). xxii
• Quality was improving for Hispanic groups for about three-fourths of Healthy Living and Patient Safety measures.
• More than half of Effective Treatment measures improved and 10% of measures showed a worsening trend.

Over time, disparities have narrowed in end stage renal disease due to diabetes between Hispanic and non-Hispanic White people but Hispanic people still have a rate more than twice that of non-Hispanic White people.

Changes in Disparities for Hispanic Populations

Number and percentage of all quality measures with disparity at baseline for which disparities related to race and ethnicity were improving, not changing, or worsening over time, total and by priority area, from 2000 through 2015, 2017, 2018, or 2019. (more...)

• Of the 49 quality measures with a disparity at baseline, disparities between Hispanic and non-Hispanic White people did not change for 47 (96%) from 2000 through 2019 ( Figure 36 ).
• Two measures showed narrowing disparities—one Effective Treatment measure and one Healthy Living measure.
• Home health care patients whose shortness of breath decreased.
• No measure showed widening disparities between Hispanic and non-Hispanic White people.
• No Care Coordination measures with data for Hispanic groups were available.

End Stage Renal Disease

Diabetes is the leading cause of kidney disease in the United States. According to the National Institute of Diabetes and Digestive and Kidney Diseases, non-Hispanic White people experience diabetes and kidney disease at a lower rate than other racial and ethnic groups. 43

Adjusted incident rates of end stage renal disease due to diabetes per million population, 2001–2018 (lower rates are better).

• Data from 2001 to 2018 show that the disparity between Hispanic and non-Hispanic White people was narrowing ( Figure 37 ).
• Rates of ESRD due to diabetes decreased for Hispanic people, from 410.0 per million population to 292.7 per million population.
• Disparities have been persistent, with Hispanic populations having higher incident rates of ESRD due to diabetes than White people in all years.

Improved Breathing Among Home Health Care Patients

To assess the quality of care received by home health care patients, measures of wait time to see provider, timely initiation of care, ambulation, ability to get in and out of bed, bathing, toileting, dressing, pain, confusion, management of oral medications, influenza and pneumococcal vaccination, and shortness of breath are tracked.

Shortness of breath is uncomfortable. Many patients with heart or lung problems experience difficulty breathing and may tire easily or be unable to perform daily activities. Doctors and home health staff should monitor shortness of breath and may give advice, therapy, medication, or oxygen to help lessen this symptom.

Home health care patients whose shortness of breath decreased, 2013–2018.

• From 2013 to 2018, the disparity between Hispanic and non-Hispanic White people was narrowing for home health care patients whose shortness of breath decreased ( Figure 38 ).
• Both Hispanic people (53.7% to 74.5%) and non-Hispanic White people (66.7% to 80.9%) showed improvement over time.
• Disparities for Native Hawaiian/Pacific Islander Populations

Native Hawaiian/Pacific Islander populations experienced worse quality care compared with White populations for about 40%of Person-Centered Care measures.

New in 2021, this section presents disparities in access to care for Native Hawaiian and Pacific Islander (NHPI) populations. To provide context, findings for other ethnic and racial populations may be included. Additional details on disparities of care for other priority populations are presented in population-specific sections of this report.

Number and percentage of access measures for which NHPI groups experienced better, same, or worse access to care compared with White groups, 2017–2019. Key: AI/AN = American Indian or Alaska Native, NHPI = Native Hawaiian/Pacific Islander, n = (more...)

• NHPI data were only available for four measures and all four measures showed that NHPI groups had the same access to care as White groups ( Figure 39 ).

Number and percentage of quality measures for which Native Hawaiian/Pacific Islander groups experienced better, same, or worse quality of care compared with White groups for the most recent data year, 2017, 2018, or 2019. Key: n = number of measures. (more...)

• Data for the most recent year show that NHPI groups experienced worse quality care compared with White groups on 28% of all quality measures. Quality was better for NHPI groups than for White groups on 19% of all quality measures ( Figure 40 ).
• No Affordable Care measures with data for NHPI groups were available.
• Home health care patients who had timely initiation of care.

HIV can affect anyone regardless of sexual orientation, race, ethnicity, gender, age, or geographic location. However, in the United States, some racial/ethnic groups are more affected than others, given their percentage of the population. This disparity occurs because some population groups have higher rates of HIV in their communities, thus raising the risk of new infections with each sexual or injection drug use encounter.

In addition, a range of social, economic, and demographic factors such as stigma, discrimination, income, education, and geographic region can affect people’s risk for HIV. In 2018, 42% of new HIV diagnoses were among Black people and 29% were among Hispanic people. 44

While NHPI individuals represent 0.4% of the total population in the United States, their HIV case rate was more than twice that of the White population in 2019.

New HIV cases per 100,000 population age 13 and over, 2019. Key: NHPI = Native Hawaiian or Pacific Islander Note: All racial groups are non-Hispanic. Hispanic includes all races. The benchmark calculation takes the average of the top 10% of states with (more...)

• In 2019, the percentage of new HIV cases per 100,000 population age 13 and over was more than twice as high for NHPI groups (13.9 per 100,000 population) as for White groups (5.3 per 100,000 population) ( Figure 41 ).

Treatment by Home Health Providers

The goal of home health care is to treat an illness or injury; help patients recover, regain independence, become as self-sufficient as possible, and maintain current condition or level of function; and slow decline. 45

Adults who reported that home health care providers always treated them with courtesy and respect in the last 2 months of care, 2019. Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories (more...)

• In 2019, the percentage of adults who reported that home health care providers always treated them with courtesy and respect in the last 2 months was lower for NHPI people (90.7%) compared with White people (94.4%) ( Figure 42 ).
• The 2015 achievable benchmark was 95%.
• The top 10% of states that contributed to the benchmark were Alabama, Louisiana, Mississippi, Rhode Island, South Carolina, and West Virginia. Guam was not included in the benchmark but its percentage was in the benchmark range.

Initiation of Home Health Care

Timely initiation of home health care is associated with lower risks of 30-day rehospitalization. Therefore, CMS requires that home health care services be initiated within 2 days of hospital discharge when ordered, except when the physician/provider authorizes a delay in the initiation of services due to an outpatient visit or the patient’s or family’s request. 46

Home health care patients who had timely initiation of care, 2018. Note: Initiation of care is defined by CMS as home health quality episodes in which the start or resumption of care date was on the physician-specified start or resumption of care date (more...)

• In 2018, NHPI home health patients were less likely than White patients to receive timely initiation of care (91% vs. 94.4%) ( Figure 43 ).
• The 2015 achievable benchmark was 95%. At the current rate of progress, NHPI people should reach the benchmark in 5 years (trend data not shown).
• The top 10% of states that contributed to the benchmark were Louisiana, Nebraska, North Dakota, South Dakota, and West Virginia.

Trends in Quality of Care for Native Hawaiian and Pacific Islander Populations

Nearly 45% of quality measures for NHPI groups showed improvement.

Number and percentage of all quality measures that were improving, not changing, or worsening over time, total and by priority area, from 2001 through 2017, 2018, or 2019. Key: n = number of measures. Note: For each measure with at least four data points (more...)

• Among the 68 quality measures with data for NHPI populations, 30 (44%) were improving, 34 (50%) were not changing, and 4 (6%) were getting worse from 2001 through 2019 ( Figure 44 ).
• No Affordable Care measures with data for NHPI populations were available.

Changes in Disparities for Native Hawaiian and Pacific Islander Populations

Number and percentage of all quality measures with disparity at baseline for which disparities related to race and ethnicity were improving, not changing, or worsening over time, total and by priority area, from 2008 through 2018 or 2019. Key: n = number (more...)

• Disparities between NHPI and White populations did not change for most of the quality measures from 2008 through 2019. Of the 20 quality measures with a disparity at baseline, disparities were not changing for 18 measures (90%) ( Figure 45 ).
• No measure showed widening disparities, and only two measures showed narrowing disparities: People age 13 and over living with HIV who know their HIV status and People age 13 and over living with diagnosed HIV who had at least two CD4 or viral load tests performed at least 3 months apart during the last year.
• No Affordable Care measures with data for NHPI people were available.

It is important for everyone to know his or her HIV status. Getting an HIV test is the first step for people living with HIV to get care and treatment and control the infection. Taking HIV medicine as prescribed helps people living with HIV to live a long, healthy life and protect their sex partners from HIV. About 85% of people with HIV in the United States know they have the virus. However, 15% (162,500) of people with HIV do not know they have the virus, and about 40% of new HIV infections come from them.

Half of people with HIV had the virus 3 years or more before diagnosis. Most people at high risk who did not get tested last year saw a healthcare provider during the year. Everyone should get tested at least once, and people at high risk should be tested at least once a year. Healthcare providers can diagnose HIV sooner if they test more people and test people at high risk more often. 47

People age 13 and over living with HIV who had knowledge of their HIV status, 2010–2019. Note: Data are statistically unreliable for NHPI groups in 2015. The benchmark calculation takes the average of the top 10% of states with statistically reliable (more...)

• Data from 2010 to 2019 show that the disparity between NHPI people and White people was narrowing due to a larger increase in the percentage of NHPI people (69.8% to 83.6%) than White people (85.8% to 89.2%) who are living with HIV and had knowledge of their HIV status ( Figure 46 ).
• The 2015 achievable benchmark was 90.2%.
• The top 10% of states that contributed to the benchmark were Connecticut, District of Columbia, Massachusetts, New Hampshire, and New York.

Viral Load Monitoring

Viral load is the amount of HIV in the blood of a person who has HIV. Viral load is highest during the acute phase of HIV and when HIV is untreated. People with HIV who keep an undetectable viral load (or stay virally suppressed ) can live long, healthy lives. Having an undetectable viral load also helps prevent transmitting the virus to others through sex or sharing needles, syringes, or other injection equipment, and from mother to child during pregnancy, birth, and breastfeeding. Higher viral load increases the risk of transmitting HIV. 48

People age 13 and over living with diagnosed HIV who had at least two CD4 or viral load tests performed at least 3 months apart during the last year, 2014–2018. Note: The benchmark calculation takes the average of the top 10% of states with statistically (more...)

• Data from 2014 to 2018 show that the disparity between NHPI and White populations was narrowing due to a larger increase in the percentage of NHPI people (50.2% to 55.7%) than White people (58.5% to 58.9%) living with diagnosed HIV who had at least two CD4 or viral load tests performed at least 3 months apart during the last year ( Figure 47 ).
• The 2015 achievable benchmark was 66.2%.
• The top 10% of states that contributed to the benchmark were Connecticut, Iowa, Montana, and Oregon.

An example of a Department of Health and Human Services initiative to end the HIV epidemic is the Minority HIV/AIDS Fund (MHAF). This initiative has the goal of transforming HIV prevention, care, and treatment for communities of color by bringing federal, state, and community organizations together to design and test innovative solutions that address critical emerging needs; and by working to improve the efficiency, effectiveness, and impact of federal investments in HIV programs and services for racial and ethnic minorities.

MHAF supports Ending the HIV Epidemic: A Plan for America , a federal initiative designed to reduce the number of new HIV infections in the United States by 75% over 5 years and 90% by 2030.

• Innovation: The Fund designs and tests innovative programs and strategies to improve the efficiency, effectiveness, and impact of HIV programs in racial and ethnic minority communities.
• Systems Change: Successes generated by the Fund are integrated into existing efforts, creating lasting changes across the federal HIV prevention, care, and treatment portfolio.
• Strategic Partnerships and Collaboration: The Fund breaks down program silos and develops new ways for federal, state, and local agencies to work together in the community to improve outcomes for racial and ethnic minorities.

More information can be found at: https://www.hiv.gov/federal-response/smaif/smaif-in-action .

• Disparities by Income

New in 2021, this section presents disparities in access to care by income groups. Additional details on disparities of care for other priority populations are presented in population-specific sections of this report.

Number and percentage of access measures for which members of selected income groups experienced better, same, or worse access to care compared with the high-income group, 2017, 2018, or 2019. Key: n = number of measures.

• People in poor households had worse access to care than people in high-income households for 79% of access measures ( Figure 48 ).
• People in low-income households had worse access to care than people in high-income households for 71% of access measures.
• People in middle-income households had worse access to care than people in high-income households for 50% of access measures.

Number and percentage of access measures for which people in poor households experienced better, same, or worse access to care compared with people in high-income households, by sub-area, 2017, 2018, or 2019. Key: n = number of measures.

• For the most recent year, people in poor households had worse access to care than people in high-income households for 79% of access measures ( Figure 49 ).
• People in poor households had worse access to care than people in high-income households for 100% of health insurance, source of ongoing care, and timely access to care measures.
• People in poor households had worse access to care than people in high-income households for a quarter of patient perception of need measures.

The measure with the largest disparities across all access to care subsections for people in poor households was people under age 65 with any private health insurance.

People under age 65 with any private health insurance, by income and ethnicity, 2019.

• In 2019, among people under age 65, people in poor, low-income, and middle-income families were less likely than people in high-income families to have private health insurance ( Figure 50 ).
• In 2019, among people under age 65, Hispanic people of all income groups were less likely than non-Hispanic White people to have private health insurance.

The relationship between income and healthcare outcomes has been studied for many years, and researchers have shown the positive relationship between more income and better health outcomes. 49 , 50 , 51 , 52 Income is not the same as wealth, which can include assets other than income. Wealth is disproportionately dispersed among higher income categories, and research also shows a positive association between greater wealth and better health outcomes.

• Poor: Less than 100% of FPL.
• Low income: 100% to less than 200% of FPL.
• Middle income: 200% to less than 400% of FPL.
• High income: 400% or more of FPL

The poverty guidelines are issued annually in the Federal Register by the Department of Health and Human Services, Assistant Secretary for Planning and Evaluation. The guidelines vary by family size and there are different family income criteria for the contiguous 48 states, Alaska, and Hawaii. Criteria for U.S. territories are unavailable. 53 For HCUP measures, income is based on median income of the patient’s ZIP Code and is divided into quartiles.

This section shows quality measures with the largest income disparities and trends in disparities.

Quality of care for high-income groups was better than for poor and low-income groups for more than half of all measures.

Number and percentage of quality measures for which income groups experienced better, same, or worse quality of care compared with the high-income group for the most recent data year, 2017, 2018, or 2019. Key: n = number of measures. Note: The most recent (more...)

• Data for the most recent year show that high-income groups experienced better quality care than other income groups on 53% of all measures ( Figure 51 ).
• Poor and low-income groups experienced worse quality care compared with high-income groups on about 57% of the measures. Compared with high-income groups, middle-income groups experienced worse quality care on 44% of the measures.

The measure with the largest income disparities is “children ages 5–17 with untreated dental caries.”

• Children ages 5–17 with untreated dental caries (all income groups).
• People without a usual source of care who indicated a financial or insurance reason for not having a source of care (all income groups).
• People under age 65 whose family’s health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income (middle income)
• Children ages 19–35 months who received 1 or more doses of measles-mumps- rubella vaccine (low income)
• Hospital admissions for short-term complications of diabetes per 100,000 population, adults (first quartile: lowest income).

Pediatric Dental Caries

Dental caries is one of the most common chronic diseases of childhood in the United States. Untreated caries can cause pain and infections that may lead to problems with eating, speaking, playing, and learning. Children who have poor oral health often miss more school and receive lower grades than children who do not . 54

Children ages 5–17 with untreated dental caries, 2015–2018 (lower rates are better). Note: Poor refers to household incomes below the federal poverty level (FPL); low, the FPL to just below 200% of the FPL; middle, 200% to just below 400% (more...)

• In 2015–2018, the measure with the largest income disparities among all income groups was children ages 5–17 with untreated dental caries ( Figure 52 ).
• In 2015–2018, the percentage of children ages 5–17 with untreated dental caries was higher for poor, low-income, and middle-income children compared with high-income children (19.4%, 16.9%, and 12.1%, respectively, vs. 4.5%).

People with lower incomes may experience difficulty accessing affordable care and are less likely to have a usual source of care that is readily accessible. 51 People who are unwell and have low incomes are also more likely to experience poverty. 51

In 2018, the measure with the second largest income disparities among all income groups was people without a usual source of care who indicated a financial or insurance reason for not having a source of care.

People without a usual source of care who indicated a financial or insurance reason for not having a source of care, 2018 (lower rates are better).

• In 2018, the percentage of people without a usual source of care who indicated a financial or insurance reason for not having a source of care was higher for poor, low-income, and middle-income people compared with high-income people (23.6%, 25.9%, and 16.1%, respectively, vs. 7.2%) ( Figure 53 ).

High Family Medical Expenditures

The most prominent barriers to healthcare coverage include affordability, eligibility for public coverage in a person’s state, immigration status, and lack of familiarity with signup procedures. 55 Poor health may require a family to spend more on healthcare, resulting in less income. Costs will vary based on each person or family’s needs and may inhibit a family’s ability to reach other goals. 51

In 2018, the measure with the third largest income disparities among middle-income people was people under age 65 whose family’s health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income

People under age 65 whose family’s health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income, 2018 (lower rates are better).

• In 2018, the percentage of people under age 65 whose family’s health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income was higher for middle-income people compared with high-income people (21.9% vs. 10.7%) ( Figure 54 ).

Childhood Vaccinations

Childhood vaccinations are an important part of preventing disease. Consistently high childhood immunization rates have greatly reduced the rates of death, disability, and illness from communicable diseases such as chicken pox, diphtheria, measles, meningococcal meningitis, mumps, polio, rubella, tetanus, and whooping cough.

In the decade before the measles vaccine became available, an average of 549,000 measles cases and 495 measles deaths were reported annually in the United States. Of the reported cases, approximately 48,000 people were hospitalized from measles and each year, 1,000 people developed chronic disability from acute encephalitis caused by measles. 56

Mumps complications include orchitis, oophoritis, mastitis, meningitis, encephalitis, pancreatitis, and hearing loss. 57

Before the rubella vaccine became available, one noted outbreak infected 12.5 million people, 11,000 pregnant women lost their babies, 2,100 newborns died, and 20,000 babies were born with congenital rubella syndrome . 58

Children ages 19–35 months who received 1 or more doses of measles-mumps-rubella vaccine, 2018. Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories are not included in the (more...)

• In 2018, the percentage of children ages 19–35 months who received 1 or more doses of measles-mumps-rubella vaccine was lower for children from poor (90.3%) and low-income (90.3%) families compared with children from high-income families (95.8%) ( Figure 55 ).
• The 2015 achievable benchmark was 96.4%.
• The top 5 states that contributed to the achievable benchmark were Connecticut, Delaware, Iowa, Maine, Nebraska, and Vermont.

Hospital Admissions for Diabetes Complications

More than 100 million people living in the United States have diabetes or are at risk for diabetes. 59 Compared with some other countries, the rate of hospital admissions for short-term complications of diabetes, which include ketoacidosis, hyperosmolarity, and coma, is higher in the United States. 60 Such complications may be related to kidney disease, hypertension, vision problems, pain, or other issues.

Hospital admissions for short-term complications of diabetes per 100,000 population, adults, 2018 (lower rates are better).

• In 2018, the rate of hospital admissions for short-term complications of diabetes was three times as high for adults in the lowest income group (145.3 per 100,000 population) compared with adults in the highest income group (45.0 per 100,000 population) ( Figure 56 ).

Trends in Quality of Care for Income Groups

Poor, low-income, and middle-income people had a higher percentage of improving measures compared with high-income people.

Number and percentage of all quality measures that were improving, not changing, or worsening over time, total and by income group, from 2000 through 2016, 2017, 2018, or 2019. Key: n = number of measures. Note: For each measure with at least four data (more...)

• The percentage of measures that showed improvement was 57% for poor people, low-income people, and middle-income people, and 49% for high-income people ( Figure 57 ).

Changes in Income Disparities

Most disparities by income showed no statistically significant changes over time.

Number and percentage of quality measures with disparity at baseline for which disparities related to income were improving, not changing, or worsening over time, 2000 through 2016, 2017, 2018, or 2019. Key: n = number of measures. Note: Different data (more...)

• Disparities by income were unchanged for about 95% of quality measures ( Figure 58 ).
• Only one measure showed narrowing disparities and five measures showed widening disparities.
• Adolescents ages 16–17 who received 1 or more doses of meningococcal conjugate vaccine (low income).
• Emergency department visits involving opioid-related diagnoses per 100,000 population (first and second quartiles: lowest and second lowest income).
• Hospital inpatient stays involving opioid-related diagnoses per 100,000 population (first, second, and third quartiles: lowest, second lowest, and second highest income).

Adolescent Vaccination

Meningococcal disease refers to any illness caused by bacteria called Neisseria meningitidis , also known as meningococcus. These illnesses are often severe and can be deadly. They include infections of the lining of the brain and spinal cord (meningitis) and bloodstream infections (bacteremia or septicemia). 61

• Meningococcal conjugate or MenACWY vaccines, which help protect against four types of the bacteria that cause meningococcal disease (serogroups A, C, W, and Y).
• Serogroup B meningococcal or MenB vaccines, which help protect against serogroup B meningococcal disease.

According to CDC, all children ages 11 to 12 years old should get a meningococcal conjugate vaccine, with a booster dose at 16 years old. 62

Adolescents ages 16–17 who received 1 or more doses of meningococcal conjugate vaccine, 2008–2018. Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories are not included (more...)

• In 2008, 31.9% of low-income adolescents ages 16–17 received 1 or more doses of meningococcal conjugate vaccine, and by 2018, the percentage had increased to 86.4% ( Figure 59 ).
• From 2008 to 2018, the percentage of high-income adolescents ages 16–17 who received 1 or more doses of meningococcal conjugate vaccine increased from 46.8% to 89.8%.
• Data from 2008 to 2018 show that disparities between adolescents in high-income households and in poor households were narrowing over time and both populations were improving.
• The 2015 achievable benchmark was 96.2%. At the current rate of increase, the benchmark could be achieved in 2 years for all income groups.
• The top 5 states that contributed to the achievable benchmark were Indiana, Michigan, New Jersey, Pennsylvania, and Rhode Island.

Emergency Department Visits Involving Opioids

The U.S. opioid overdose epidemic continues to evolve. In 2016, 66.4% of the 63,632 drug overdose deaths involved an opioid. In 2017, among 70,237 drug overdose deaths, 47,600 (67.8%) involved opioids, with increases across age groups, racial and ethnic groups, county urbanization levels, and multiple states. From 2013 to 2017, synthetic opioids contributed to increases in drug overdose death rates in several states. From 2016 to 2017, synthetic opioid-involved overdose death rates increased 45.2%. 63

Emergency department visits related to opioid use per 100,000 population, 2005–2018. Key: 1 st Quartile = <$48000, 2 nd Quartile = $48,000–$60,999, 3 rd Quartile = $61,000–$81,999, and 4 th Quartile = >$82,000. Note: (more...)

• In 2005, the rate of emergency department visits involving opioid-related diagnoses among people in the lowest income group was 104.9 per 100,000 population, and by 2018, the rate had increased to 348.1 per 100,000 population ( Figure 60 ).
• In 2005, the rate of emergency department visits involving opioid-related diagnoses among people in the second lowest income group was 90.2 per 100,000 population, and by 2018, the rate had increased to 231 per 100,000 population.
• In 2005, the rate of emergency department visits involving opioid-related diagnoses among people in the third income group was 83.2 per 100,000 population, and by 2018, the rate had increased to 195.7 per 100,000 population.
• In 2005, the rate of emergency department visits involving opioid-related diagnoses among people in the highest income group was 65.5 per 100,000 population, and by 2018, the rate had increased to 146.8 per 100,000 population.
• Data from 2005 to 2018 show that disparities between high-income and poor and low-income people were widening over time and both populations were worsening.
• The 2015 achievable benchmark was 65.2 per 100,000. No income group showed progress toward the benchmark.
• The top 10% of states contributing to the achievable benchmark were Iowa, Kansas, Nebraska, and South Dakota.

Hospital Stays Involving Opioids

Increased availability and overuse of opioid medications have contributed to adverse outcomes for patients, including increased risk of opioid use disorder, misuse of medication, and overdoses. 64 The National Survey on Drug Use and Health shows that in 2020, nearly 9.5 million people age 12 and over misused opioids in the past year. 65 This treatment measure examines inpatient stays associated with opioid-related diagnoses.

Hospital inpatient stays involving opioid-related diagnoses per 100,000 population, 2005–2018. Key: 1 st Quartile = <$48000, 2 nd Quartile = $48,000–$60,999, 3 rd Quartile = $61,000–$81,999, and 4 th Quartile = >$82,000. (more...)

• In 2005, the rate of hospital inpatient stays involving opioid-related diagnoses among people in the lowest income group was 179.6 per 100,000 population, and by 2018, the rate had increased to 382.1 per 100,000 population ( Figure 61 ).
• In 2005, the rate of hospital inpatient stays involving opioid-related diagnoses among people in the second lowest income group was 125.5 per 100,000 population, and by 2018, the rate had increased to 288.7 per 100,000 population.
• In 2005, the rate of hospital inpatient stays involving opioid-related diagnoses among people in the second highest income group was 117.2 per 100,000 population, and by 2018, the rate had increased to 252.1 per 100,000 population.
• In 2005, the rate of hospital inpatient stays involving opioid-related diagnoses among people in the highest income group was 98.1 per 100,000 population, and by 2018, the rate had increased to 191.6 per 100,000 population.
• Data from 2005 to 2018 show that disparities between people in the highest quartile and people in the other three quartiles were widening over time and all populations were worsening.
• The 2015 achievable benchmark was 102.9 per 100,000. There is no evidence of progress toward the benchmark.
• The top 10% of states that contributed to the achievable benchmark were Georgia, Iowa, Nebraska, Texas, and Wyoming.
• Disparities by Insurance Status
• Increased financial security,
• Access to primary care,
• Adherence to prescription medications,
• Screening for treatable health conditions (such as diabetes, cholesterol, HIV, and breast, prostate, and colon cancer),
• Improved perceptions of health,
• Reduced depression symptoms, and
• Earlier detection of cancer. 66 , 67

This section examines disparities and trends by insurance status among people ages 0–64 years. It focuses on people less than age 65 years because more than 98% of Americans 65 years and over have Medicare. 68 Thus, almost no older adults lack insurance coverage since almost all are covered, at minimum, by public insurance (Medicare).

• Private Insurance : Person has access to insurance from a private insurer.
• Public Insurance : Person receives insurance from one or more government-sponsored sources, including Medicaid, State Children’s Health Insurance Program (S-CHIP), state-sponsored or other government-sponsored health plans, Medicare, and military and veteran health plans.
• Uninsured : Person does not have any health insurance.

It should be noted that the Indian Health Service (IHS) is not considered a health plan for this report. IHS is a healthcare system, which offers comprehensive healthcare services to AI/AN individuals. Currently, IHS serves 2.7 million AI/AN people who belong to 574 federally recognized tribes in 37 states. Non-IHS data sources, including CDC’s National Center for Health Statistics, also track disparities for AI/AN populations and are the source of data for health disparities for this population.

The bar chart ( Figure 62 ) summarizes comparisons between people with private health insurance (the reference group) and people with public health insurance or no insurance for 69 quality of care measures for which data by insurance status are available.

Quality of care for uninsured people was better than quality for those with private insurance on only 7% of measures.

Number and percentage of quality measures for which insurance groups experienced better, same, or worse quality of care compared with reference group (privately insured), 2016, 2017, or 2018. Key: n = number of measures. Note: The difference between two (more...)

• Compared with those with private insurance, people with public insurance experienced better quality care for 10% of measures. Uninsured people experienced better quality care for 7% of measures ( Figure 62 ).
• People under age 65 whose family’s health insurance premium and out-of-pocket medical expenditures were more than 10% of total family income.
• Deaths per 1,000 adult hospital admissions with heart failure.
• Deaths per 1,000 adult hospital admissions with pneumonia.
• Compared with people with private insurance, people with public insurance had worse quality care for 39% of measures, and uninsured people had worse quality care for 61% of measures.

The measures with the largest disparities between people with public health insurance and people with private insurance reflect differences in access to care and in quality of care experienced by patients. The measures with the largest disparities between people with no insurance and those with private insurance reflect differences in access to primary care providers and the routine healthcare services they deliver.

Largest Disparities for People With Public Insurance

Among different public insurance programs, Medicaid and S-CHIP alone cover approximately one-fourth of Americans, 69 of whom nearly two-thirds are seniors, children, or disabled people. 70 While outcomes are often worse for people with public insurance, some of the differences in health outcomes may be explained by factors other than public insurance. For example, injuries, disabilities, and preexisting illnesses that can contribute to negative health outcomes are also reasons many people qualify for public health insurance. 71 Thus, on average, people with public insurance begin with worse baseline health than people with no insurance or those with private insurance. Public insurance serves as a safety net for people with limited options after experiencing disabling injury or illness.

• Women under age 70 treated for breast cancer with breast-conserving surgery who received radiation therapy to the breast within 1 year of diagnosis.
• Adults who had a doctor’s office or clinic visit in the last 12 months whose health providers sometimes or never showed respect for what they had to say.

Having a usual primary care provider is associated with higher likelihood of receiving appropriate care, including preventive care services. Patients with a usual source of care also report better provider-patient communication and increased trust in the provider, both of which are linked to treatment adherence and better health. 72

• In 2018, the percentage of people without a usual source of care who indicated a financial or insurance reason for not having a source of care was more than twice as high for adults with public insurance (17.9%) compared with adults with private insurance (8.7%) ( Figure 63 ).
• In 2018, the percentage of people without a usual source of care who indicated a financial or insurance reason for not having a source of care was more than 5 times as high for uninsured adults (43.8%) compared with adults with private insurance (8.7%).

Receiving Appropriate Treatment After Lumpectomy for Breast Cancer

When women with early stage breast cancer undergo breast-conserving surgery (also called lumpectomy), combining surgical treatment with radiation therapy improves outcomes. 73 Observational studies have reported that adding radiation therapy reduces the risk of recurrence by half and reduces the risk of death from breast cancer by a sixth. 74

Women under age 70 treated for breast cancer with breast-conserving surgery who received radiation therapy to the breast within 1 year of diagnosis, 2017.

• In 2017, the percentage of women who underwent breast-conserving surgery for breast cancer and received radiation therapy within 1 year of surgery was significantly lower for women with public insurance (83.2%) than for women with private insurance (91.3%) ( Figure 64 ).
• The percentage of women who underwent breast-conserving surgery for breast cancer and received radiation therapy within 1 year of surgery was also lower for women with no insurance (88.7%) than for women with private insurance (91.3%).

Providers Who Showed Respect for What Patients Had to Say

Patient-centered care encompasses qualities of compassion, empathy, and responsiveness to the needs, values, and preferences of individuals. It is linked to greater patient participation in their care, lower risk of misdiagnosis due to poor communication, and better patient outcomes. 75 , 76

Adults who had a doctor’s office or clinic visit in the last 12 months whose health providers sometimes or never showed respect for what they had to say, 2017 (lower rates are better).

• In 2017, the percentage of adults who had a doctor’s office or clinic visit in the last 12 months who reported their health providers sometimes or never showed respect for what they had to say was nearly twice as high for people with public insurance (12.2%) compared with people with private insurance (6.4%) ( Figure 65 ).
• The percentage of adults who had a doctor’s office or clinic visit in the last 12 months who reported their health providers sometimes or never showed respect for what they had to say was also higher for people without health insurance (13.3%) than for people with private insurance (6.4%).

Largest Disparities for Uninsured People

• People without a usual source of care who indicated a financial or insurance reason for not having a source of care ( Figure 63 ).
• Children ages 0–17 with a wellness checkup in the past 12 months.
• Adults who received a blood pressure measurement in the last 2 years.

Wellness Visits for Children

Wellness visits are important opportunities to assess the physical, emotional, and social development of children and adolescents, screen for health risks, and influence health behaviors, such as eating habits and physical activity, which often extend into adulthood. 78 Having health insurance facilitates access to providers for recommended well-child visits.

Children ages 0–17 with wellness checkup in the past 12 months, by insurance status, 2019.

• In 2019, children with no insurance (74.1%) were less likely to receive a wellness visit in the preceding 12 months than children with either public (95.2%) or private (94.6%) insurance ( Figure 66 ).

Blood Pressure Screening

Hypertension, also called high blood pressure , affects about one-third of U.S. adults. It can damage the heart, blood vessels, kidneys, and other parts of the body over time, but it is often asymptomatic until complications, such as stroke, heart attack, heart failure, and chronic kidney disease, develop. If hypertension is identified early, providers can offer patients a range of treatment that lowers the risk for complications. 79

Adults without hypertension who had their blood pressure measured in the last 2 years, 2019.

• In 2019, uninsured adults (75.6%) were less likely to receive screening for high blood pressure in the last 2 years than adults covered by public (94.4%) or private (94.1%) insurance ( Figure 67 ).

Changes in Quality of Care by Insurance Status

More than half of quality measures for those with private and public insurance were improving but only one-third of quality measures for uninsured people showed improvement.

Number and percentage of all quality measures that were improving, not changing, or worsening, total and by insurance status, from 2000 through 2015, 2017, 2018, or 2019. Key: n = number of measures. Note: For each measure with at least four data points (more...)

• From 2000 through 2019, for people with private insurance, 54% of measures were improving, 43% of measures were not changing, and 3% of measures were worsening ( Figure 68 ).
• For people with public insurance, 57% of measures were improving, 37% of measures were not changing, and 6% of measures were worsening.
• For people with no insurance, 32% of measures were improving, 62% of measures were not changing, and 6% of measures were worsening.
• Adults who had a doctor’s office or clinic visit in the last 12 months whose health providers always asked them to describe how they will follow the instructions.
• Infants born in the calendar year who received breastfeeding exclusively through 3 months.
• Children who had their height and weight measured by a health provider within the past 2 years.
• Children 41–80 lb for whom a health provider gave advice within the past 2 years about using a booster seat when riding in the car.
• People with a usual source of care who usually asks about prescription medications and treatments from other doctors.
• Adults ages 18 and over who received influenza vaccination in the last flu season.
• Children ages 6 months to 17 years who received influenza vaccination in the last flu season.
• Children ages 2–17 who had a dental visit in the calendar year.
• Children ages 2–17 who received a preventive dental service in the calendar year.
• Adults age 40 and over with diagnosed diabetes who received a flu vaccination in the calendar year.

Changes in Disparities by Insurance

Although many measures of healthcare quality improved over time, disparities between groups by health insurance status changed for only one measure ( Figure 69 ).

Number and percentage of quality measures with disparity at baseline for which disparities related to insurance were improving, not changing, or worsening, 2000 through 2017, 2018, or 2019. Key: n = number of measures.

• Disparities by insurance status for most quality measures did not change ( Figure 69 ).
• Only one measure showed improvement over time in disparities between uninsured people and people with private insurance: Adults age 40 and over with diagnosed diabetes who received a flu vaccination in the calendar year.

Receipt of Flu Vaccine by Patients With Diabetes

The disparity reduction for this measure reflects stagnant outcomes for patients with private insurance while outcomes for uninsured patients showed improvement.

Adults age 40 and over with diagnosed diabetes who received a flu vaccination in the calendar year, 2008–2018. Note: Data for uninsured people did not meet criteria for statistical reliability in 2017 and 2018.

• The percentage of uninsured adults age 40 and over with diabetes who received a flu vaccine increased from 36.7% in 2008 to 49.7% in 2016.
• The percentage of adults with diabetes and public or private insurance who received a flu vaccine showed no statistically significant changes ( Figure 70 ).

CDC has prepared several patient and provider resources, including a web page on flu and diabetes .

• Disparities by Residence Location

Where people live affects their access to healthcare and the quality of services they receive. Research shows that healthcare disparities by residence location exist for both adults and children. 81 , 82 , 83 , 84 , 85 , 86 Socioeconomic differences may contribute to the disparities: residents of inner-city and rural communities are more likely to live in poverty, more likely to engage in unhealthy behaviors (e.g., smoking), and less likely to have health insurance than people who live in suburbs. 87

Differences in population density may also contribute to disparities that are specific to each location. Inner-city residents may live in crowded or inadequate housing that exposes them to higher levels of environmental pollutants, contagious vectors, mental distress, and violence compared with people who live in suburban and rural communities. 88 By contrast, reduced economies of scale, longer travel times to access goods and services, and decreased opportunities for social contact in rural communities may limit the availability of healthcare services and increase risk for diseases related to social isolation. 89 , 90

This section examines disparities in quality of care by residence location.

Residence Location Groups

The analyses in this section use the 2013 National Center for Health Statistics (NCHS) classification, 91 which are the most recent categories used by NCHS.

• That contain the entire population of the largest principal city of the MSA, or
• Whose entire population is contained within the largest principal city of the MSA, or
• That contain at least 250,000 residents of any principal city in the MSA.
• Large Fringe Metropolitan: Counties in MSAs of 1 million or more population that do not qualify as large central areas. xxiii Large Fringe Metropolitan areas are also described as suburban areas. Examples of Large Fringe Metro areas are San Bernardino County, California; Broward County, Florida; and Bergen County, New Jersey.
• Medium Metropolitan: Counties in MSAs of 250,000 to 999,999 population. Examples of Medium Metro areas are Scott County, Kentucky; York County, Maine; and Douglas County, Nebraska.
• Small Metropolitan: Counties in MSAs of less than 250,000 population. Examples of Small Metro areas are Baldwin County, Alabama; Wayne County, North Carolina; and Allen County, Ohio.
• Micropolitan: Nonmetropolitan counties in a “micropolitan statistical area,” which are defined as counties that are less densely populated than MSAs and centered around smaller urban clusters with 2,500–49,999 inhabitants. Examples of Micropolitan areas are Woodward County, Oklahoma; Cherokee County, South Carolina; and Harrison County, West Virginia.
• Noncore: Nonmetropolitan counties that are outside of a micropolitan statistical area. Noncore counties are also described as rural. Examples of Noncore areas are Wallowa County, Oregon; Bedford County, Pennsylvania; and Crane County, Texas.

When examining trends, it is important to recognize that the key differences between the 2013 NCHS Urban-Rural Classification scheme and the earlier 2006 version are in how it describes small metropolitan, micropolitan, and noncore areas. The 2013 classification broadens the inclusion criteria for each of these residence locations. All other definitions are unchanged ( Table 1 ). 92

NCHS Urban-Rural Classification Scheme, 2006 vs. 2013.

Figure 71 shows a map of U.S. county classifications according to the 2013 NCHS Urban-Rural Classification system.

Map showing 2013 NCHS Urban-Rural County Classifications in the United States.

The NHQDR uses the NCHS classification to analyze performance of quality measures that have data available by residence location. Data on state-based performance metrics are also available through the NHQDR State View. 93

With the State View tool, users can explore the quality of their state’s healthcare and compare their state’s data with national data or data from the best performing states. Users can access a state dashboard showing performance compared with benchmarks for more than 80 measures. Some of these measures are also stratified by subpopulations to show disparities.

Overview of Disparities by Residence Location

In the most recent data year, 34% of measures had better performance in large fringe metro areas than in other locations while only 4% of measures showed worse performance ( Figure 72 ). Relative to large fringe metro counties, nonmetropolitan (i.e., micropolitan and noncore) areas had the largest number of measures that showed worse quality care, followed by small metro and large central metro areas. Large central metro and noncore areas had the largest number of measures that showed better quality care.

Nonmetropolitan areas had the largest number of measures showing worse quality care compared with large fringe metropolitan areas, followed by small metropolitan and large central metropolitan areas.

Number and percentage of quality measures for which residents of selected locations experienced better, same, or worse quality of care compared with large fringe metropolitan areas, 2017, 2018, or 2019. Key: n = number of measures. Note: Definitions of (more...)

• Nonmetropolitan (micropolitan and noncore) areas showed worse quality care than large fringe metro areas on 45% and 37% of measures, respectively, and better quality care on 3% and 7% of measures for which data are available by location of residence ( Figure 72 ).
• Large central metro areas showed worse quality care than large fringe metro areas on 22% of measures and better quality care for 5% of measures.

Examining the specific measures where nonmetropolitan areas and large central metro areas experienced better or worse care relative to large fringe metro areas highlights issues where these locations share similar concerns and where they differ. Large central metro, micropolitan, and noncore areas overlapped on six quality of care measures, where all three experienced worse quality than large fringe metro areas. However, they did not overlap in any of the measures for which they experienced better quality of care. Instead, measures where a residence location at one end of the urban-rural spectrum experienced better quality care were frequently the same measure where the residence location at the other end of the spectrum experienced worse quality care.

• Adults who had a doctor’s office or clinic visit in the last 12 months whose health providers sometimes or never listened carefully to them.
• Children over 80 lb for whom a health provider gave advice within the past 2 years about using lap or shoulder belts when riding in a car.
• Hospital admissions for short-term complications of diabetes per 100,000 population, adults.
• Hospital admissions for lower extremity amputations per 1,000 population, adults age 18 and over with diabetes.
• Reclosure of postoperative abdominal wound dehiscence per 1,000 abdominopelvic-surgery admissions of length 2 or more days, adults.
• Emergency department visits with a principal diagnosis related to substance use disorder only, per 100,000 population.
• Hospital admissions for asthma per 100,000 population, adults ages 18–39.
• Hospital admissions for asthma per 100,000 population, children ages 2–17.
• Hospital admissions for community-acquired pneumonia per 100,000 population, adults age 18 and over.
• Lung cancer deaths per 100,000 population per year.
• Suicide deaths among people age 12 and over per 100,000 population.

The three measures with the largest disparities between large fringe metro areas and other locations vary. The differences may reflect differing healthcare needs for each location. In the most recent available data years, the three measures with the largest disparities relative to large fringe metro areas follow for each location.

• HIV infection deaths per 100,000 population
• Hospital admissions for asthma per 100,000 population, children ages 2–17
• Emergency department visits with a principal diagnosis related to substance use disorder only, per 100,000 population
• Hospital admissions for short-term complications of diabetes per 100,000 population, children ages 6–17
• Adults who received a blood cholesterol measurement in the last 5 years
• Infant mortality per 1,000 live births, birth weight 2,500 grams or more
• Children ages 3–5 who ever had their vision checked by a health provider
• Hospitalizations and emergency department encounters for heart failure
• Emergency department visits with a principal diagnosis related to dental conditions
• Hospital admissions for community-acquired pneumonia per 100,000 population, adults age 18 and over
• Deaths per 1,000 hospital admissions with expected low mortality

The following figures these measures in detail.

New HIV diagnoses and HIV prevalence are concentrated primarily in large U.S. metropolitan areas, with Atlanta, Baton Rouge, Miami, New Orleans, and Orlando leading the list of areas with the highest rate of new diagnoses. Atlanta, Baton Rouge, Miami, New Orleans, and New York lead the list of areas with the highest rates of people living with HIV. 94

HIV infection deaths per 100,000 population, 2018 (lower rates are better). Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories are not included in the calculations. Some benchmarks (more...)

• In 2018, the death rate from HIV infections was higher in large central metro areas (2.3 per 100,000 population) compared with the rate in large fringe metro areas (1.1 per 100,000 population) ( Figure 73 ).
• The 2015 achievable benchmark was 0.75 per 100,000 population. At the current rate of increase, overall, the benchmark could be achieved in 4 years for large central metro areas and in 2 years for large fringe metro areas (trend data not shown).

An HHS initiative to eliminate new HIV infections is underway. The goal is “to reduce new HIV infections in the United States by 75 percent in five years and by 90 percent by 2030.” 95 Federal efforts to reduce HIV-related mortality include the promotion of treatment therapies such as antiretroviral therapy, as well as pre-exposure prophylaxis and postexposure prophylaxis. 96

Several HHS agencies provide a federal response to the HIV epidemic, including HRSA’s HIV/AIDS Bureau, which administers the Ryan White HIV/AIDS Program (RWHAP). RWHAP is the largest federal program focused exclusively on providing HIV care and treatment to patients with inadequate or no insurance. Through RWHAP’s partnerships, more than 512,000 people receive care annually.

Hospital Admissions for Asthma

Asthma is the most common chronic lung condition among children under 17 years in the United States. 97 Children with asthma may experience debilitating exacerbations triggered by environmental exposures, such as fumes, airborne viruses, and cold air, but appropriate treatment in ambulatory care settings can reduce patients’ risk for exacerbations. 98 , 99

Research has linked access to primary care, continuity of care by a provider, and adherence to preventive care plans to improved quality of care and fewer hospital admissions for chronic conditions such as asthma. 100

Hospital admissions for asthma per 100,000 population, children ages 2–17, 2018 (lower rates are better).

• In 2018, the rate of hospital admissions for children ages 2–17 with asthma was more than 60% higher in large central metro areas (116.3 per 100,000 population) than in large fringe metro areas (71.3 per 100,000 population) ( Figure 74 ).

Emergency Department Visits for Substance Use

Illicit drug use and subsequent overdose deaths have risen in both metropolitan and nonmetropolitan areas over the past two decades. Overdose death rates in rural areas exceeded rates in urban areas between 2007 and 2015, 101 overlapping with the second wave of opioid overdose deaths. 102 However, more recent data show that overdose death rates in the third wave of opioid overdose deaths are highest in urban communities. 103

Emergency department visits with a principal diagnosis related to substance use disorder only per 100,000 population, 2018 (lower rates are better).

• In 2018, the rate of adult emergency department visits with a principal diagnosis related to substance use disorder was 42% higher in large central metro areas (642.8 per 100,000 population) than in large fringe metro areas (452.7 per 100,000 population) ( Figure 75 ).

Hospital Admissions for Short-Term Complications of Diabetes

Type 1 diabetes is one of the most common chronic diseases in childhood. It is caused by insulin deficiency, resulting from an autoimmune reaction that destroys insulin-producing beta-cells in the pancreas. In children and adolescents, the most common complications of diabetes are short-term problems that result from blood sugars going too low or too high: hypoglycemia, ketoacidosis, and diabetic coma. 104 Access to healthcare providers who can prescribe medications and teach patients how to self-manage their health can reduce risks for short-term complications and prevent emergency visits and hospitalizations. 105

Hospital admissions for short-term complications of diabetes per 100,000 population, children 6–17, 2018 (lower rates are better).

• In 2018, the rate of hospitalizations among children ages6–17 years due to short-term complications of diabetes mellitus was 36% higher in medium metro areas (32.1 per 100,000 population) than in large fringe metro areas (23.6 per 100,000 population) ( Figure 76 ).

Cholesterol Check

Medications and lifestyle modifications that lower cholesterol reduce the risk of heart attacks and strokes in people who may have underlying atherosclerosis (i.e., cardiovascular disease). 106 Intermittent laboratory testing for cholesterol by a healthcare provider can identify atherosclerosis in otherwise healthy people and help them make informed treatment decisions to lower their risk of heart attacks and strokes. Thus, access to screening for cholesterol is an important component of efforts to improve cardiovascular health. 107

Adults who received a blood cholesterol measurement in the last 5 years, 2019.

• In 2019, the percentage of adults who received a blood cholesterol measurement in the last 5 years was lower in micropolitan (83.5%) and medium metropolitan areas (88.1%) than in large fringe metro areas (91.0%) ( Figure 77 ).

Infant Mortality

Infant mortality is the death of infants before their first birthday. It is a key health indicator that reflects baseline maternal and infant health, as well as healthcare services delivered before, during, and immediately after an infant’s birth. In 2018, the five leading causes of infant death were birth defects, preterm birth and low birth weight, injuries (e.g., suffocation), sudden infant death syndrome, and maternal pregnancy complications. 108

Infant mortality per 1,000 live births, birth weight 2,500 grams or more, 2017 (lower rates are better).

• In 2017, the percentage of infant deaths among live births weighing 2,500 grams or more was significantly higher in medium metro (2.2%), small metro (2.4%), micropolitan (2.6%), and noncore (2.9%) areas than in large fringe metro areas (1.7%) ( Figure 78 ).

Pediatric Vision Exams

Pediatric vision screenings are efficient eye examinations that primary care providers, trained laypeople (e.g., in schools), and eye care specialists perform to detect issues that warrant a more comprehensive eye examination by a specialist. They are crucial for identifying conditions that could lead to blindness, life-threatening illness, and problems with school performance if left untreated. 109

Research shows that periodic vision screening in early childhood reduces the risk of vision loss at age 7 years by more than 50%. 110 Thus, access to vision screening throughout childhood is important to ensure children’s health.

Children ages 3–5 who ever had their vision checked by a health provider, 2018. Note: Data for noncore areas are not shown because the data were statistically unreliable.

• In 2018, the percentage of children ages 3–5 years who had their vision checked by a health provider was lower in micropolitan (58.9%) and small metropolitan areas (62.0%) than in large fringe metro areas (77.3%) ( Figure 79 ).

Hospital and Emergency Visits for Heart Failure

Heart failure is an important cause of morbidity and mortality in the United States, accounting for 379,800 deaths in 2018. 111 , 112 It is also the most common and expensive reason for preventable hospitalizations, with more than 1 million admissions and $11.2 billion in total costs in 2017. Access to appropriate treatment in ambulatory care settings can help patients safely avoid emergency visits and hospital admissions for this condition. 113

Hospitalizations and emergency department encounters for heart failure per 100,000 population, 2018 (lower rates are better).

• In 2018, the rate of emergency department visits and hospitalizations per 100,000 population for heart failure was significantly higher in micropolitan (663.6 visits) and noncore (713.3 visits) areas than in large fringe metro areas (434.9 visits) ( Figure 80 ).

Emergency Department Visits for Dental Conditions

Oral health is a vital component of a person’s overall health and well-being. Untreated oral disease can affect appetite, leading to nutritional problems; cause chronic pain, interfering with sleep and work; and has been associated with diabetes, heart and lung disease, stroke, and poor birth outcomes. 114

Preventive dental care, including early detection, treatment, and management of problems, promotes good oral health. When people lack access to a usual source of dental care, they often will seek relief in emergency departments, which are equipped to meet only emergency dental care needs. 115

Emergency department visits with a principal diagnosis related to dental conditions per 100,000 population, 2018 (lower rates are better).

• In 2018, the rate of ED visits related to dental conditions in micropolitan and noncore areas combined (459.7 per 100,000 population) was more than twice the rate in large fringe metro areas (210.3 per 100,000 population) ( Figure 81 ).

Hospital Admissions for Pneumonia

Community-acquired pneumonia (CAP) is an acute lung infection acquired outside of a hospital setting. A person with CAP may present with symptoms that range from mild fever and productive cough to severe infection and inability to breathe without mechanical ventilation. 116

CAP results in substantial morbidity, mortality, and costs in the United States. As the fourth leading reason for hospitalizations in 2018, it accounted for 740,700 admissions and $7.7 billion in healthcare costs. 117 In 2019, it was the underlying cause of death in 43,881 individuals (13.4 deaths per 100,000 population). 118

CAP hospitalizations are often avoidable. Administering pneumococcal vaccines to high-risk groups can prevent infections, and early evaluation and treatment by a healthcare provider can prevent hospitalizations.

Hospital admissions for community-acquired pneumonia per 100,000 population, adults age 18 and over, 2018 (lower rates are better).

• In 2018, the rate of hospital admissions for CAP was nearly twice as high in noncore areas (330.2 per 100,000 population) as in large fringe metro areas (171.2 per 100,000 population) ( Figure 82 ).

Unexpected Deaths After Hospital Admission

Death during a hospital admission may indicate that patients received unsafe or inappropriate care, particularly if a patient dies while being treated for problems with low mortality risk.

Deaths per 1,000 hospital admissions with expected low mortality, 2018 (lower rates are better).

• In 2018, the death rate for conditions with expected low mortality was nearly twice as high in noncore areas (0.81 per 1,000 admission) as in large fringe metro areas (0.45 per 1,000 admission) ( Figure 83 ).

Changes in Quality of Care by Residence Location

The bar chart in Figure 84 summarizes trends in 45 quality of care measures for which data are available by geographic location.

Among the six geographic locations, noncore areas had the fewest improving trends and the most worsening trends.

Number and percentage of all quality measures that were improving, not changing, or worsening, total and by residence location, from 2002 through 2010, 2011, 2013, 2016, 2017, 2018, or 2019. Key: n = number of measures. Note: For each measure with at (more...)

• Noncore areas had the fewest measures with improving trends (33%) and the most measures with worsening trends (14%) ( Figure 84 ).
• Among the remaining geographic locations, large central metro and large fringe metro areas had the most measures with improving trends (51% and 50%, respectively). Large central metro and micropolitan areas had the fewest measures with worsening trends (7%).

Changes in Disparities by Residence Location

The bar chart in Figure 85 summarizes trends in disparities between large fringe metro areas and other locations for 13 measures for which data are available by geographic location. Overall, disparities between large fringe metropolitan counties and other areas did not change during the most recent data year available. The only measure that showed narrowing disparities was “hospital inpatient stays involving opioid-related diagnoses,” which resulted from worsening opioid-related hospitalization rates in large fringe metro areas, instead of improving trends in other locations.

The only disparity that improved was due to a worsening trend for large fringe metropolitan counties instead of improvement in other locations.

In the 2019 NHQDR, two other measures had similarly shown narrowing disparities due to worsening trends in large fringe metro areas: “people unable to get or delayed in getting needed medical care due to financial or insurance reasons” and “people unable to get or delayed in getting needed prescription medicines due to financial or insurance reasons.” These measures are not reported this year due to lack of data availability.

Number and percentage of quality measures with disparity at baseline for which disparities related to residence location were improving or not changing, 2002 through 2015, 2016, 2017, or 2018. Key: n = number of measures. Note: A total of 13 measures (more...)

• Disparities by residence location remained unchanged for most quality measures ( Figure 85 ).

Inpatient Stays Due to Opioid Use

The opioid epidemic constitutes a continuing public health emergency 119 that affects the entire United States. The 2020 National Survey on Drug Use and Health estimates that nearly 9.5 million people misused opioids in the past year, 65 and data from the Centers for Disease Control and Prevention (CDC) indicate that rates of nonfatal and fatal overdose continue to rise in multiple states and territories.

CDC estimates that 49,860 of 70,630 drug overdose deaths (70.6%) involved opioids in 2019, affecting multiple age groups, racial and ethnic groups, and geographic regions. 120 Rising rates of hospital admissions for opioid-related diagnoses echo this trend. They also indicate that narrowing disparities between geographic locations represent worsening trends in large fringe metro areas instead of improving trends in large central metro areas.

Hospital inpatient stays involving opioid-related diagnoses per 100,000 population, 2005–2018 (lower rates are better). Note: The benchmark calculation takes the average of the top 10% of states with statistically reliable data. U.S. territories (more...)

• From 2005 to 2018, the gap in opioid-related hospitalization rates in large central metro areas and in large central fringe metro areas narrowed ( Figure 86 ). However, the reduced disparity was due to rates of opioid-related hospitalizations rising faster in large fringe metro areas. This undesirable trend began to plateau in 2016 but remains well above the 2015 achievable benchmark of 102.9 hospitalizations per 100,000 population. (For this measure, a low value is more desirable, so rates above the achievable benchmark indicate suboptimal quality of care.)
• In 2005, the rate was 111.5 per 100,000 population in large fringe metro areas vs. 195.8 per 100,000 population in large central metro areas. In 2017, rates in both geographic areas had risen to peak 288.4 admissions per 100,000 population in large fringe metro areas and 314.6 admissions per 100,000 population in large central metro areas.
• In 2018, the most recent year for which data are available, hospitalization rates for opioid-related disorders had plateaued at 268.7 per 100,000 population in large fringe metro areas and 307.3 per 100,000 population in large central metro areas, approximately 3 times as high as the achievable benchmark of 102.9 per 100,000 population.
• The top 10% of states that contributed to the achievable benchmark were Georgia, Iowa, Nebraska, Texas, and Wyoming. In 2016–2017, no state reached the benchmark.

In 2017, HHS launched a departmentwide initiative with a five-point strategy to combat the opioid epidemic. Many agencies supported this initiative by establishing specific research opportunities, resources, and data to support providers, patients, and researchers. More information is available at https://www.hhs.gov/opioids/ . Other federal resources are discussed in detail in the Quality of Care – Trends in Effective Treatment section of this report.

Due to a change in the Healthcare Cost and Utilization Project (HCUP) data, the same measures reported in past reports are not represented in this report. HCUP converted all measures from International Classification of Diseases, Ninth Revision (ICD-9) to Tenth Revision (ICD-10) codes in October 2015, thus changing the outcomes of these measures. Therefore, trend data are not directly comparable at this time.

Due to a change in the Healthcare Cost and Utilization Project (HCUP) data, the same measures reported in past reports are not represented in this report. HCUP converted all measures from International Classification of Diseases, Ninth Revision (ICD-9) to Tenth Revision (ICD-10) codes in October 2015, thus changing the outcomes of these measures. Therefore, trend data are not available at this time.

For comparisons across residence locations, large fringe MSAs (large city suburbs) are used as the reference group since these counties have the lowest levels of poverty and typically have the best healthcare quality and access to healthcare.

This document is in the public domain and may be used and reprinted without permission. Citation of the source is appreciated.

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