problem solving and decision making in healthcare

The Value of Critical Thinking in Nursing

• How Nurses Use Critical Thinking
• How to Improve Critical Thinking
• Common Mistakes

Some experts describe a person’s ability to question belief systems, test previously held assumptions, and recognize ambiguity as evidence of critical thinking. Others identify specific skills that demonstrate critical thinking, such as the ability to identify problems and biases, infer and draw conclusions, and determine the relevance of information to a situation.

Nicholas McGowan, BSN, RN, CCRN, has been a critical care nurse for 10 years in neurological trauma nursing and cardiovascular and surgical intensive care. He defines critical thinking as “necessary for problem-solving and decision-making by healthcare providers. It is a process where people use a logical process to gather information and take purposeful action based on their evaluation.”

“This cognitive process is vital for excellent patient outcomes because it requires that nurses make clinical decisions utilizing a variety of different lenses, such as fairness, ethics, and evidence-based practice,” he says.

How Do Nurses Use Critical Thinking?

Successful nurses think beyond their assigned tasks to deliver excellent care for their patients. For example, a nurse might be tasked with changing a wound dressing, delivering medications, and monitoring vital signs during a shift. However, it requires critical thinking skills to understand how a difference in the wound may affect blood pressure and temperature and when those changes may require immediate medical intervention.

Nurses care for many patients during their shifts. Strong critical thinking skills are crucial when juggling various tasks so patient safety and care are not compromised.

Jenna Liphart Rhoads, Ph.D., RN, is a nurse educator with a clinical background in surgical-trauma adult critical care, where critical thinking and action were essential to the safety of her patients. She talks about examples of critical thinking in a healthcare environment, saying:

“Nurses must also critically think to determine which patient to see first, which medications to pass first, and the order in which to organize their day caring for patients. Patient conditions and environments are continually in flux, therefore nurses must constantly be evaluating and re-evaluating information they gather (assess) to keep their patients safe.”

The COVID-19 pandemic created hospital care situations where critical thinking was essential. It was expected of the nurses on the general floor and in intensive care units. Crystal Slaughter is an advanced practice nurse in the intensive care unit (ICU) and a nurse educator. She observed critical thinking throughout the pandemic as she watched intensive care nurses test the boundaries of previously held beliefs and master providing excellent care while preserving resources.

“Nurses are at the patient’s bedside and are often the first ones to detect issues. Then, the nurse needs to gather the appropriate subjective and objective data from the patient in order to frame a concise problem statement or question for the physician or advanced practice provider,” she explains.

Top 5 Ways Nurses Can Improve Critical Thinking Skills

We asked our experts for the top five strategies nurses can use to purposefully improve their critical thinking skills.

Case-Based Approach

Slaughter is a fan of the case-based approach to learning critical thinking skills.

In much the same way a detective would approach a mystery, she mentors her students to ask questions about the situation that help determine the information they have and the information they need. “What is going on? What information am I missing? Can I get that information? What does that information mean for the patient? How quickly do I need to act?”

Consider forming a group and working with a mentor who can guide you through case studies. This provides you with a learner-centered environment in which you can analyze data to reach conclusions and develop communication, analytical, and collaborative skills with your colleagues.

Practice Self-Reflection

Rhoads is an advocate for self-reflection. “Nurses should reflect upon what went well or did not go well in their workday and identify areas of improvement or situations in which they should have reached out for help.” Self-reflection is a form of personal analysis to observe and evaluate situations and how you responded.

This gives you the opportunity to discover mistakes you may have made and to establish new behavior patterns that may help you make better decisions. You likely already do this. For example, after a disagreement or contentious meeting, you may go over the conversation in your head and think about ways you could have responded.

It’s important to go through the decisions you made during your day and determine if you should have gotten more information before acting or if you could have asked better questions.

During self-reflection, you may try thinking about the problem in reverse. This may not give you an immediate answer, but can help you see the situation with fresh eyes and a new perspective. How would the outcome of the day be different if you planned the dressing change in reverse with the assumption you would find a wound infection? How does this information change your plan for the next dressing change?

Develop a Questioning Mind

McGowan has learned that “critical thinking is a self-driven process. It isn’t something that can simply be taught. Rather, it is something that you practice and cultivate with experience. To develop critical thinking skills, you have to be curious and inquisitive.”

To gain critical thinking skills, you must undergo a purposeful process of learning strategies and using them consistently so they become a habit. One of those strategies is developing a questioning mind. Meaningful questions lead to useful answers and are at the core of critical thinking .

However, learning to ask insightful questions is a skill you must develop. Faced with staff and nursing shortages , declining patient conditions, and a rising number of tasks to be completed, it may be difficult to do more than finish the task in front of you. Yet, questions drive active learning and train your brain to see the world differently and take nothing for granted.

It is easier to practice questioning in a non-stressful, quiet environment until it becomes a habit. Then, in the moment when your patient’s care depends on your ability to ask the right questions, you can be ready to rise to the occasion.

Practice Self-Awareness in the Moment

Critical thinking in nursing requires self-awareness and being present in the moment. During a hectic shift, it is easy to lose focus as you struggle to finish every task needed for your patients. Passing medication, changing dressings, and hanging intravenous lines all while trying to assess your patient’s mental and emotional status can affect your focus and how you manage stress as a nurse .

Staying present helps you to be proactive in your thinking and anticipate what might happen, such as bringing extra lubricant for a catheterization or extra gloves for a dressing change.

By staying present, you are also better able to practice active listening. This raises your assessment skills and gives you more information as a basis for your interventions and decisions.

Use a Process

As you are developing critical thinking skills, it can be helpful to use a process. For example:

• Ask questions.
• Gather information.
• Implement a strategy.
• Evaluate the results.
• Consider another point of view.

These are the fundamental steps of the nursing process (assess, diagnose, plan, implement, evaluate). The last step will help you overcome one of the common problems of critical thinking in nursing — personal bias.

Common Critical Thinking Pitfalls in Nursing

Your brain uses a set of processes to make inferences about what’s happening around you. In some cases, your unreliable biases can lead you down the wrong path. McGowan places personal biases at the top of his list of common pitfalls to critical thinking in nursing.

“We all form biases based on our own experiences. However, nurses have to learn to separate their own biases from each patient encounter to avoid making false assumptions that may interfere with their care,” he says. Successful critical thinkers accept they have personal biases and learn to look out for them. Awareness of your biases is the first step to understanding if your personal bias is contributing to the wrong decision.

New nurses may be overwhelmed by the transition from academics to clinical practice, leading to a task-oriented mindset and a common new nurse mistake ; this conflicts with critical thinking skills.

“Consider a patient whose blood pressure is low but who also needs to take a blood pressure medication at a scheduled time. A task-oriented nurse may provide the medication without regard for the patient’s blood pressure because medication administration is a task that must be completed,” Slaughter says. “A nurse employing critical thinking skills would address the low blood pressure, review the patient’s blood pressure history and trends, and potentially call the physician to discuss whether medication should be withheld.”

Fear and pride may also stand in the way of developing critical thinking skills. Your belief system and worldview provide comfort and guidance, but this can impede your judgment when you are faced with an individual whose belief system or cultural practices are not the same as yours. Fear or pride may prevent you from pursuing a line of questioning that would benefit the patient. Nurses with strong critical thinking skills exhibit:

• Learn from their mistakes and the mistakes of other nurses
• Look forward to integrating changes that improve patient care
• Treat each patient interaction as a part of a whole
• Evaluate new events based on past knowledge and adjust decision-making as needed
• Solve problems with their colleagues
• Are self-confident
• Acknowledge biases and seek to ensure these do not impact patient care

An Essential Skill for All Nurses

Critical thinking in nursing protects patient health and contributes to professional development and career advancement. Administrative and clinical nursing leaders are required to have strong critical thinking skills to be successful in their positions.

By using the strategies in this guide during your daily life and in your nursing role, you can intentionally improve your critical thinking abilities and be rewarded with better patient outcomes and potential career advancement.

Frequently Asked Questions About Critical Thinking in Nursing

How are critical thinking skills utilized in nursing practice.

Nursing practice utilizes critical thinking skills to provide the best care for patients. Often, the patient’s cause of pain or health issue is not immediately clear. Nursing professionals need to use their knowledge to determine what might be causing distress, collect vital information, and make quick decisions on how best to handle the situation.

How does nursing school develop critical thinking skills?

Nursing school gives students the knowledge professional nurses use to make important healthcare decisions for their patients. Students learn about diseases, anatomy, and physiology, and how to improve the patient’s overall well-being. Learners also participate in supervised clinical experiences, where they practice using their critical thinking skills to make decisions in professional settings.

Do only nurse managers use critical thinking?

Nurse managers certainly use critical thinking skills in their daily duties. But when working in a health setting, anyone giving care to patients uses their critical thinking skills. Everyone — including licensed practical nurses, registered nurses, and advanced nurse practitioners —needs to flex their critical thinking skills to make potentially life-saving decisions.

Meet Our Contributors

Crystal Slaughter, DNP, APRN, ACNS-BC, CNE

Crystal Slaughter is a core faculty member in Walden University’s RN-to-BSN program. She has worked as an advanced practice registered nurse with an intensivist/pulmonary service to provide care to hospitalized ICU patients and in inpatient palliative care. Slaughter’s clinical interests lie in nursing education and evidence-based practice initiatives to promote improving patient care.

Jenna Liphart Rhoads, Ph.D., RN

Jenna Liphart Rhoads is a nurse educator and freelance author and editor. She earned a BSN from Saint Francis Medical Center College of Nursing and an MS in nursing education from Northern Illinois University. Rhoads earned a Ph.D. in education with a concentration in nursing education from Capella University where she researched the moderation effects of emotional intelligence on the relationship of stress and GPA in military veteran nursing students. Her clinical background includes surgical-trauma adult critical care, interventional radiology procedures, and conscious sedation in adult and pediatric populations.

Nicholas McGowan, BSN, RN, CCRN

Nicholas McGowan is a critical care nurse with 10 years of experience in cardiovascular, surgical intensive care, and neurological trauma nursing. McGowan also has a background in education, leadership, and public speaking. He is an online learner who builds on his foundation of critical care nursing, which he uses directly at the bedside where he still practices. In addition, McGowan hosts an online course at Critical Care Academy where he helps nurses achieve critical care (CCRN) certification.

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Open Access

Peer-reviewed

Research Article

Helping patients help themselves: A systematic review of self-management support strategies in primary health care practice

Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Current address: Graduate School of Health, University of Technology Sydney, Ultimo, NSW, Australia

Affiliation Graduate School of Health, University of Technology Sydney, Sydney, Australia

Roles Conceptualization, Methodology, Supervision, Validation, Writing – review & editing

Roles Conceptualization, Supervision, Writing – review & editing

Roles Conceptualization, Methodology, Supervision, Writing – review & editing

Affiliation Emeritus Professor, University of Sydney, Sydney, Australia

• Sarah Dineen-Griffin, 
• Victoria Garcia-Cardenas, 
• Kylie Williams, 
• Shalom I. Benrimoj

• Published: August 1, 2019
• https://doi.org/10.1371/journal.pone.0220116
• Reader Comments

Primary health professionals are well positioned to support the delivery of patient self-management in an evidence-based, structured capacity. A need exists to better understand the active components required for effective self-management support, how these might be delivered within primary care, and the training and system changes that would subsequently be needed.

(1) To examine self-management support interventions in primary care on health outcomes for a wide range of diseases compared to usual standard of care; and (2) To identify the effective strategies that facilitate positive clinical and humanistic outcomes in this setting.

A systematic review of randomized controlled trials evaluating self-management support interventions was conducted following the Cochrane handbook & PRISMA guidelines. Published literature was systematically searched from inception to June 2019 in PubMed, Scopus and Web of Science. Eligible studies assessed the effectiveness of individualized interventions with follow-up, delivered face-to-face to adult patients with any condition in primary care, compared with usual standard of care. Matrices were developed that mapped the evidence and components for each intervention. The methodological quality of included studies were appraised.

6,510 records were retrieved. 58 studies were included in the final qualitative synthesis. Findings reveal a structured patient-provider exchange is required in primary care (including a one-on-one patient-provider consultation, ongoing follow up and provision of self-help materials). Interventions should be tailored to patient needs and may include combinations of strategies to improve a patient’s disease or treatment knowledge; independent monitoring of symptoms, encouraging self-treatment through a personalized action plan in response worsening symptoms or exacerbations, psychological coping and stress management strategies, and enhancing responsibility in medication adherence and lifestyle choices. Follow-up may include tailored feedback, monitoring of progress with respect to patient set healthcare goals, or honing problem-solving and decision-making skills. Theoretical models provided a strong base for effective SMS interventions. Positive outcomes for effective SMS included improvements in clinical indicators, health-related quality of life, self-efficacy (confidence to self-manage), disease knowledge or control. An SMS model has been developed which sets the foundation for the design and evaluation of practical strategies for the construct of self-management support interventions in primary healthcare practice.

Conclusions

These findings provide primary care professionals with evidence-based strategies and structure to deliver SMS in practice. For this collaborative partnership approach to be more widely applied, future research should build on these findings for optimal SMS service design and upskilling healthcare providers to effectively support patients in this collaborative process.

Citation: Dineen-Griffin S, Garcia-Cardenas V, Williams K, Benrimoj SI (2019) Helping patients help themselves: A systematic review of self-management support strategies in primary health care practice. PLoS ONE 14(8): e0220116. https://doi.org/10.1371/journal.pone.0220116

Editor: Christophe Leroyer, Universite de Bretagne Occidentale, FRANCE

Received: November 13, 2018; Accepted: July 9, 2019; Published: August 1, 2019

Copyright: © 2019 Dineen-Griffin 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.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: The authors received no specific funding for this work.

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

Introduction

Internationally, healthcare systems are challenged with the rising rates of chronic and complex illness and the clinical and economic burden associated represents a major challenge to the optimal provision of healthcare [ 1 ]. Health systems need to accommodate changes to meet the increasing need for health services. Evidence suggests that leveraging the potential of people to care for themselves and involving patients in decisions affecting their health is beneficial, particularly on the increasing rates of primary care consultations and health system pressures [ 2 ]. A key issue that needs to be addressed is how primary health care professionals (HCPs) can support self-management in an evidence-based, structured way and how self-management processes can be integrated into clinical practice, as models of care evolve to deliver a person-centred approach. Patient participation is suggested to narrow the gap between the dichotomous roles of patient and HCP [ 3 ]. Patient participation involves being engaged in the planning of care and exchanging knowledge, setting own goals and carrying out self-management activities [ 3 ]. This partnership has been suggested as valuable in the support of the management and control of symptoms, particularly for patients with chronic health conditions [ 4 ]. Self-management strategies are increasingly recognized as an essential component of chronic disease management and secondary prevention [ 5 ], individually tailored to patient preferences, prior knowledge and circumstances, supporting patient participation in their care [ 6 ].

Self-management support (SMS) is viewed in two ways: (1) as a portfolio of techniques and tools that help patients choose healthy behaviours, and (2) as a fundamental transformation of the patient-professional relationship into a collaborative partnership [ 7 ]. SMS encompasses more than a didactic, instructional program and goes beyond simple dissemination of information or disease state management. The pivotal objective of SMS is to change behaviour within a collaborative arrangement to produce sustainable effects. This can be achieved by increasing patients’ skills and confidence in managing their disease state through regular assessment of progress and problems, goal setting, and problem-solving support [ 8 ]. Simply put, patients and HCPs work to develop tangible and realistic healthcare goals, while HCPs can assist with the development of the skill set necessary to achieve these goals and monitor for improvements in patient health [ 9 ]. Lorig and Holman [ 10 ] identify a generic set of skills proven successful for effective self-management, including (1) problem-solving; (2) decision-making; (3) resource utilization; (4) forming a patient-health care provider partnership; and (5) taking action. Acquisition of these skills leads to increased self-efficacy. Self-efficacy refers to beliefs in one’s capabilities to execute a behaviour or course of action necessary to reach a desired goal [ 10 , 11 ].

There is a growing body of evidence that shows supporting people to self-manage their health and care can lead to improvements in clinical and humanistic outcomes [ 12 – 18 ], reducing the economic impact of chronic disease and a means of contributing to the sustainability of the global healthcare system. Supporting people to self-manage has resulted in reduced use of general practitioners, reduced admissions to hospital, significant gains in health status and increased symptom control [ 19 , 20 ]. Interventions have targeted patients with arthritis [ 21 ], asthma [ 22 ], chronic heart failure (CHF) [ 23 ], chronic obstructive pulmonary disease (COPD) [ 24 ], type 2 diabetes mellitus (T2DM) [ 25 , 26 ], hypertension (HT) [ 27 ] and patients on oral anticoagulation [ 28 ]. Self-management support interventions vary in the literature with increasing evaluations of peer-led, lay-led, or non-health professional-led, web-based and group-based interventions. For example, the generic Chronic Disease Self-Management Program, a non-health professional group-delivered intervention remains the most widely adopted self-management support program internationally [ 29 ].

Primary HCPs are typically an individuals’ first point of contact with the health system [ 30 ], and are continuing contacts for people with chronic disease. This opens up substantial opportunities to effect sustainable changes through supporting self-management and delivery of more personalized healthcare services. There is an increasing number and uptake of primary care services which require HCPs to be patient-oriented however none of the education provided appears to include any theoretical framework or evidence-based structure for providers to effectively support self-management and facilitate patient behaviour change. Importantly, HCPs need to acquire the competencies not only to identify the techniques and tools for specific patients but to ensure that patients acquire the skills to self-manage. Kennedy et al. recommends a whole systems approach, which integrates SMS at the level of the patient, HCP, and service organizations, which has proven effective in improving outcomes for patients [ 31 ]. Effective implementation is profoundly important to ensure viability and sustainability, and potential scale-up. In some countries, governments have developed health policy and funding alignment for self-management support with the aim of improving health outcomes and alleviating pressures on the wider health system [ 32 ].

While the role of primary HCPs in delivering SMS is highlighted in the literature, there remains a gap in research regarding the specific strategies and active components of interventions used by providers resulting in better health outcomes for patients. A need exists to better understand how these might be delivered within primary care, what outcomes can be achieved, and the training and system changes needed as a result. This gap increases the challenge of providing consistent SMS in primary care, and enabling the appropriate evaluation of SMS trials. Therefore, the objective of this systematic review is to summarize the evidence of effectiveness for SMS interventions delivered face-to-face in primary care practice, and identify evidence-based strategies with active components facilitating positive clinical and humanistic patient outcomes.

A systematic review of randomized controlled trials evaluating SMS interventions was conducted following the Cochrane Handbook for Systematic Reviews of Interventions. We have reported the review according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines [ 33 , 34 ]. Details of the protocol for this systematic review can be found in the PROSPERO international prospective register of systematic reviews database (registration CRD42017062639).

Search strategy

The research question (using PICO) and search strategy were developed and reviewed by three authors (SDG, VGC, SB) to identify studies for this review. In a preliminary scoping search of databases, we as a group of authors identified ten key papers which were suitable to be included in the review. In the multiple search strategies all authors were involved. We tested and refined our strategies as a group, which ensured reproducibility of key papers within search results and a robust search strategy. The detailed search strategy for different electronic databases can be found in S1 Table . A comprehensive search was undertaken in three databases using PubMed, Scopus and Web of Science and search strategies were refined for each individual database. Multiple databases were searched to adequately identify all literature relevant to the research question. Published literature was systematically searched from inception to June 2019. Neither publication date nor publication type filters were used. Citation searching was also conducted to find articles cited by other publications. Searches of grey literature and reference lists of previous systematic reviews complemented our literature search to ensure all relevant studies were captured. The complete results from all databases were imported and managed in a unique EndNote X9 library upon search completion and saved without duplication.

Data extraction, management and synthesis

The review team were responsible for assessing the trials’ eligibility using the methods outlined. The lead reviewer (SDG) screened by title and abstract to select relevant publications. A second and third reviewer (VGC, SB) were consulted throughout this process if an article could not be rejected with certainty. Any disagreement among the reviewers throughout this process were resolved by discussion and consensus. All authors (SDG, VGC, KW, SB) agreed on the final texts for inclusion. Full texts were assessed for eligibility according to inclusion and exclusion criteria. Eligible studies were randomized controlled trials (RCTs) and cluster-randomized controlled trials (c-RCTs) assessing SMS interventions with follow-up, delivered by primary HCPs, face-to-face to adult patients with any condition, compared to usual standard of care. The types of interventions included in the review were multicomponent interventions aimed at supporting patient self-management. Jonkman et al’s definition of SMS interventions was applied for the purposes of selection of interventions for inclusion in this review [ 35 ]. This definition includes the wide range of components considered for ‘self-management interventions’. Self-management interventions are defined as [ 35 ]:

“ Interventions that aim to equip patients with skills to actively participate and take responsibility in the management of their chronic condition . This includes knowledge acquisition , and a combination of at least two of the following : (1) stimulation of independent sign and/or symptom monitoring; (2) medication management; (3) enhancing problem-solving and decision-making skills for treatment or disease management; (4) or changing physical activity , dietary and/or smoking behaviour ”.

Excluded studies were: (1) non-randomized controlled study designs; (2) interventions not meeting Jonkman’s definition of self-management support; (3) interventions not delivered face-to-face (i.e. web-based interventions); (4) group-delivered interventions; (5) study populations under 18 years of age; (6) interventions delivered in settings other than primary care; (7) interventions delivered by non-HCPs (i.e. lay, peer-led); (8) studies without usual standard of care as comparator; (9) studies written in a language other than English or Spanish; or (10) non-primary research articles (i.e. literature reviews, study protocols).

Authors kept a record of the number of trials included or excluded from the review at each stage of the assessment process. Multiple papers of the same study were linked together. Study design, setting, methods, participant characteristics, type of intervention, content, duration and intensity of components, follow up, and study findings were extracted using a tailored data extraction form developed for data retrieval using the Cochrane Handbook for Systematic Reviews of Interventions [ 36 ] and the Cochrane Effective Practice and Organisation of Care Group (EPOC) data collection form [ 37 ] and checklist [ 38 ].

Matrices were developed mapping both evidence and active components for each self-management intervention. Outcome indicators were independently extracted, tabulated and grouped using the following categories of outcome measures, including (1) disease specific indicators; (2) self-efficacy; (3) health-related quality of life; (4) functional status and disability; (5) psychological functioning; (6) disease knowledge; (7) behaviours and self-management activities. Components were categorized according to Jonkman’s definition of SMS interventions [ 35 ], including strategies for: (1) condition or treatment knowledge acquisition; (2) active stimulation of symptom monitoring; (3) self-treatment through the use of an action plan; (4) enhancing resource utilization; (5) enhancing problem-solving and/ or decision-making skills; (6) enhancing stress management or emotional coping with condition; (7) enhancing physical activity; (8) enhancing dietary intake; (9) enhancing smoking cessation; and (10) medication management or adherence. Given the heterogeneity of the studies regarding participants, varying healthcare setting, strategies and outcome measures, no formal quantitative synthesis or meta-analysis could be conducted.

Assessment of risk of bias

The methodological quality of studies were appraised using the ‘Suggested risk of bias criteria for EPOC reviews’ tool in accordance with the Cochrane Handbook [ 39 ]. Domains of bias included in the final assessment, were: (1) random sequence generation; (2) allocation concealment; (3) similarities on baseline outcome measurements; (4) similarities on baseline characteristics; (5) completeness of outcome data; (6) blinding (participants, personnel); (7) protection against contamination; (8) selective outcome reporting; and (9) other risks of bias. Studies were assessed by domain as 'low risk' or 'high risk' of bias. Domains were ‘unclear risk’ if too few details were available to make an acceptable judgement of ‘high’ or ‘low’ risk. A second and third reviewer (VGC, SB) were consulted throughout this process if decisions could not be made with certainty. Any disagreement among the reviewers throughout this process were resolved by discussion and consensus. Three categories of study quality were identified by study authors according to each study’s methodological characteristics. In high-quality studies, the majority of criteria were fulfilled and done well (low risk of bias in at least six criterion), while in low-quality studies, the majority of criteria were not done or done poorly (high risk of bias in at least five criterion); other situations were considered medium quality [ 40 ]. No papers were excluded as a result of quality assessment.

Study selection

6,510 citations were retrieved. After the removal of duplicates, 4,831 records were screened by title and abstract. After review of full texts, fifty-eight RCTs/c-RCTs (reported in 80 citations) fulfilled the review criteria and were included in this systematic review (see flow diagram in Fig 1 ). A completed PRISMA checklist can be found in S2 Table . Descriptive characteristics of individual studies are provided in S3 Table .

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https://doi.org/10.1371/journal.pone.0220116.g001

Description of studies

The included studies originated from 18 countries, predominantly the United Kingdom (UK) and the United States (US). The conditions most frequently targeted included T2DM (37.9%; n = 22), COPD (20.7%; n = 12) and depression (13.8%; n = 8) ( Table 1 ). Settings primarily reported were general practice (48.3%; n = 28), primary care clinics (25.9%; n = 15) and community pharmacies (10.3%; n = 6). Interventions were delivered largely by general practitioners or nurses, commonly specialising in areas such as respiratory, diabetes and mental health. SMS interventions in fourteen studies were delivered in primary care teams involving more than one health care professional from different disciplines (24.1%; n = 14).

https://doi.org/10.1371/journal.pone.0220116.t001

Study outcomes

Ninety-three different outcome measures were adopted by studies. Clinical outcome measures associated with a particular condition were typically reported (e.g. clinical outcomes such as changes in blood pressure or HbA1c levels). Humanistic outcomes sought to measure physical, social and psychological functioning and changes in health-related quality of life (HRQOL). Others captured changes in self-efficacy. Results were classified by outcome and method of assessment (summarised in S4 Table relative to key findings).

Impact of interventions on outcomes

The overall impact of interventions on clinical and humanistic outcomes are illustrated in Table 2 .

https://doi.org/10.1371/journal.pone.0220116.t002

Disease specific outcomes.

Forty four RCTs examined the impact of interventions on disease specific outcomes [ 42 – 57 , 60 , 70 , 71 , 76 , 78 , 79 , 82 , 85 – 87 , 102 , 106 , 107 , 109 , 110 , 112 , 114 , 115 , 118 ]. Disease specific outcomes were most commonly reported in studies evaluating interventions targeting patients with T2DM (e.g. changes in HbA1c, weight, blood pressure and lipids), COPD (e.g. changes in Peak Expiratory Flow (PEF)), courses of antibiotics, oral corticosteroids and frequency of exacerbations), asthma (e.g. PEF, symptoms, inhalation technique, number of exacerbations and nocturnal awakenings), binge eating disorders (e.g. frequency of episodes and purging) and osteoarthritis (OA) (e.g. pain intensity, level of fatigue and use of pain medication). Seventeen studies targeting diabetes reported mean changes in HbA1c, with seven reporting significant improvements in the intervention compared to usual care [ 42 , 46 , 47 , 50 , 52 , 53 , 56 , 109 , 112 ]. Goudswaard et al. [ 42 ] reported a decrease in HbA1c at six weeks by 0.7% more (95% CI 0.1, 1.4) in those receiving the intervention when compared with control. The intervention evaluated by Adachi et al. [ 50 ] for patients with T2DM resulted in a 0.7% decrease in HbA1c at six months in the intervention group (n = 100) compared with a 0.2% decrease in the control group (n = 93) (difference −0.5%, 95% CI: -0.2%, −0.8%; p = 0.004).

Three RCTs reported on the level of asthma control and symptoms [ 80 – 82 ]. Mehuys et al. measured the level of asthma control using the Asthma Control Test (ACT), a clinically validated measure [ 81 ]. While mean ACT scores did not change from baseline for both study groups, a subgroup analysis of patients having insufficiently controlled asthma at baseline showed the intervention group had significantly increased ACT scores after six months (mean ACT change from baseline in the intervention group was +2.3 and +0.3 in the control group (mean difference 2.0, 95% CI: 0.1, 3.9; p = 0.038). The need for rescue medication was reduced in both groups from baseline, however a significantly higher reduction in the intervention group (-0.56 and -0.57 inhalations per day at three and six-month follow-up, respectively) was reported against control (-0.03 and -0.43 inhalations per day at three and six-month follow-up, respectively; p = 0.012) [ 81 ]. Six studies reported on COPD-specific outcomes [ 64 , 65 , 68 – 71 , 111 ]. McGeoch et al. [ 64 ] reported no significant change in St. George’s Respiratory Questionnaire (SGRQ) as the primary outcome measure. The intervention also showed no effect on self-reported outcomes including the frequency of use of antibiotic courses and oral corticosteroids over 12 months [ 64 ].

Interventions targeting eating disorders were evaluated in four RCTs [ 41 , 92 , 93 , 97 , 103 , 117 ]. Banasiak et al. [ 97 ] explored primary outcome measures of eating pathology derived from the Eating Disorder Examination Questionnaire (EDE-Q). Intention-to-treat (ITT) analyses revealed significant improvements in psychological symptoms at the end of the intervention compared with control, reduction in mean frequency of binge-eating episodes by 60% in intervention and 6% in control, and remission from all binge-eating and compensatory behaviours in 28% of the intervention and 11% of control. Treatment gains were maintained at three and six-month follow-up [ 97 ].

An intervention targeting patients with OA measured primary outcomes of pain intensity, physical functioning, self-efficacy, psychological distress, use of pain coping strategies, catastrophizing and HRQOL [ 84 ]. ITT analyses were performed on primary outcomes at baseline, post-treatment, 6 and 12 month follow-up which yielded significant group differences, indicating improvement in pain intensity (F(3,233) = 2.75, p = 0.044), physical functioning (F(3,233) = 3.11, p = 0.027), psychological distress (F(3,233) = 2.83, p = 0.039), use of pain coping strategies (F(3,233) = 4.97, p = 0.002), and self-efficacy (F(3,232) = 10.59, p< 0.001) in intervention, compared with control. All outcomes, except for self-efficacy, were maintained at 12-month follow-up while effects on self-efficacy degraded over time [ 84 ].

Health-related quality of life.

Twenty-four RCTs examined the impact of interventions on HRQOL [ 31 , 54 , 56 , 57 , 60 , 61 , 64 – 66 , 69 , 71 , 73 , 74 , 76 , 81 – 84 , 90 – 92 , 94 , 96 , 98 , 101 , 102 , 108 , 113 , 117 ]. The method of assessment varied and included general HRQOL questionnaires such as the SF-12 survey questionnaire and EuroQoL EQ-5D questionnaire. Disease specific QOL measures were also identified including the Arthritis Impact Measurement Scales Short Form questionnaire (AIMS2-SF) [ 119 ], Irritable Bowel Syndrome Quality of Life Questionnaire (IBSQOL) [ 120 ], Audit of Diabetes Dependent Quality of Life (ADDQOL) [ 121 ] and the standardised Asthma Quality of Life Questionnaire (AQLQ) [ 122 ]. Eight studies reported significant improvements in HRQOL [ 56 , 66 , 71 , 82 , 90 – 92 , 96 , 113 , 117 ]. Efraimsson et al. [ 66 ] evaluated the effects of COPD self-management delivered at a nurse-led primary health care clinic. HRQOL, measured using the SGRQ, was improved by an average value of 8.2 units (from 30.6) in the intervention group, whereas no change was noted in control. Differences between groups were clinically relevant and statistically significant (p = 0.00030) [ 66 ]. Heitkemper et al. [ 91 ] examined the effect of an IBS SMS intervention on HRQOL using the Irritable Bowel Syndrome Quality of Life questionnaire (IBSQOL), a 30-item questionnaire. Compared to usual care, participants receiving the intervention demonstrated statistically significant improvements in QOL, increasing by 10.6 units, 12.8 units and 12.2 units at nine weeks, six and twelve-months, respectively. Changes persisted at 12-month follow-up (p<0.001) [ 91 ].

Physical, psychological or social functioning.

Physical, mental or social functioning were measured in 25 RCTs [ 31 , 43 , 44 , 47 , 54 , 56 – 58 , 60 – 64 , 68 , 72 – 76 , 79 , 84 – 97 , 100 , 102 , 108 , 111 – 115 , 117 ]. Psychological symptoms and social functioning using the CORE-OM scale [ 123 ] were measured in three studies [ 74 , 75 , 100 ]. Psychological functioning was measured using the Beck Depression Inventory (BDI) and Beck Depression Inventory-II (BDI-II) scale [ 124 ] in eight studies [ 72 , 75 , 84 , 92 – 94 , 97 , 100 , 108 , 117 ]. Williams et al. [ 75 ] reported lower mean BDI-II scores in the intervention group at four months (2.6 to 7.9; mean difference 5.3 points, p<0.001). At twelve-month follow-up, there were also significantly higher proportions of participants achieving a 50% reduction in BDI-II in the intervention arm compared to control [ 75 ]. The Problem Areas in Diabetes Scale (PAID), a brief self-report scale [ 125 ], was used to evaluate diabetes-related distress. Sturt et al. [ 44 ] reported a reduction by 4.5 points in mean PAID scores at follow-up (95% CI: −8.1, −1.0), indicating lowered diabetes-related distress after a nurse-delivered intervention compared with control (p = 0.012), however this difference was considered a small effect [ 44 ]. Physical functioning was assessed with the SF-36PF scale [ 126 ] by Friedberg et al. [ 94 , 108 ] evaluating a chronic fatigue self-management intervention. No significant changes in scores by time, treatment group, or diagnostic group were revealed (p>0.05) [ 94 , 108 ].

Patient self-efficacy.

Self-efficacy was assessed using a number of validated instruments including the General Self Efficacy Scale (GSES-12) [ 127 ], Diabetes Management Self Efficacy Scale (DMSE) [ 128 ] and the Arthritis Self Efficacy Scale (an eight item scale measuring patients’ perceived ability to perform specific behaviours aimed at controlling arthritis pain and disability) [ 129 ], the COPD self-efficacy scale (CSES) [ 130 ], among others. Self-management and patient enablement were measured by the Patient Enablement Instrument (PEI) [ 87 ]. Changes in perceived self-efficacy were reported in 14 studies [ 31 , 44 , 54 , 57 , 68 , 69 , 73 , 76 – 78 , 84 , 87 , 98 , 99 , 102 , 104 , 110 , 111 , 116 ]. Sturt et al. showed self-efficacy scores were 11.2 points higher on the DMSE (95% CI: 4.4, 18.0) in the intervention group compared with the control group following a structured intervention delivered by practice nurses in the UK (p = 0.0014) [ 44 ]. Broderick et al. [ 84 ] reported significant improvement in self-efficacy (F(3,232) = 10.59, p = 0.001) following a nurse-practitioner delivered intervention for OA patients, however this was not maintained at 12-month follow up (p = 0.158). Seven RCTs reported non-significant improvements in self-efficacy [ 54 , 57 , 59 , 68 , 69 , 77 , 78 , 98 , 102 , 105 , 110 , 111 , 116 ]. Bischoff et al. found no statistically significant changes in CSES scores at 24 months [ 69 ]. Smit et al. [ 77 , 116 ] assessed self-efficacy in controlling depressive symptoms and preventing future episodes, using the Depression Self-Efficacy Scale (DSES) [ 131 ]. No statistically significant differences between groups were revealed at 12-month follow-up [ 77 , 116 ]. Eikelenboom et al. reported no significant difference in PAM-13 scores (measure of patient activation [ 132 ]) between control and intervention arms at six-month follow-up [ 59 , 105 ].

Self-management behaviours.

Behaviours commonly measured were diet, physical activity, medication adherence and smoking. Five studies reported on level of physical activity [ 41 , 59 , 83 , 88 , 103 , 105 ]. A range of measures included the International Physical Activity Questionnaire short form (IPAQ-SF) [ 133 ], Rapid Assessment of Physical Activity questionnaire (RAPA) [ 134 ] and The Physician-based Assessment and Counselling for Physical Activity (PACE) questionnaire [ 135 ]. No significant between group differences were reported for physical activity in 4 RCTs [ 41 , 59 , 65 , 83 , 103 , 105 ]. There was evidence in one study to suggest self-reported exercise participation was higher 1-week post-intervention (p<0.001) however differences were no longer significant at seven-week follow-up [ 88 ]. Self-care activities within 7 days were measured in 4 RCTs [ 41 , 52 , 54 , 60 , 102 , 103 ] using the Summary of Diabetes Self-Care Activities (SDSCA) questionnaire, a brief self-report instrument for measuring levels of self-management in diabetes (‘general diet’, ‘specific diet’, ‘physical exercise’, ‘foot care’ and ‘smoking’) [ 136 ]. Mehuys et al. reported significant improvements in self-management activities in the domains of ‘specific diet’ (+0.5 day/week, p = 0.008), ‘physical exercise’ (+0.4 day/week, p = 0.006), and ‘foot care’ (+1.0 day/week, p<0.001) for intervention patients. There were significant between-study group differences in the domains ‘physical exercise’ (p = 0.045) and ‘foot care’ (p<0.001), however the between-group difference for ‘specific diet’ were non-significant [ 52 ].

Disease knowledge.

Nine studies reported disease knowledge as an outcome [ 52 , 66 – 68 , 71 , 81 , 82 , 88 , 93 , 111 ]. Two RCTs [ 67 , 68 , 111 ], measured COPD disease knowledge using the Bristol COPD Knowledge Questionnaire (BCKQ) [ 137 ]. Hill et al. reported the results of the BCKQ for each domain in both groups. Compared with baseline measures, the total Bristol COPD knowledge Questionnaire score increased from 27.6 ± 8.7 to 36.5 ± 7.7 points (p<0.001) in the intervention group, and unchanged in the control group (29.6 ± 7.9 to 30.2 ± 7.2; p = 0.51) [ 67 ].

Intervention components and theoretical underpinnings

Each of the studies described interventions including multiple core components (see S5 Table for full component breakdown). Providing knowledge about the condition or treatment (100%; n = 58), enhancing patients role in making lifestyle changes (71.9%; n = 41), development of a self-management or action plan (45.6%; n = 26), keeping logs of self-monitoring (43.9%; n = 25), strategies for psychological coping with conditions (43.9%; n = 25), enhancing problem-solving and/or decision-making skills (42.1%; n = 24) and medication adherence or management (36.8%; n = 21) were most prominently detected ( Table 3 ). Interventions targeting heart disease, irritable bowel disease (IBD) and asthma reported the highest number of self-management components. Self-treatment through the use of an action plan, enhancing medication adherence and smoking cessation components were frequently seen in studies evaluating interventions targeting COPD. Similarly, SMS components targeting T2DM commonly included strategies to stimulate symptom monitoring, making positive lifestyle improvements with physical activity or dietary improvements. In contrast, interventions for depression included components focusing on patients’ role in managing stress, problem-solving and strategies for coping with conditions.

https://doi.org/10.1371/journal.pone.0220116.t003

Overall, sixteen studies explicitly reported a theoretical framework underpinning the intervention (28.1%; n = 16) including Cognitive Behavioural Theory (17.5%; n = 10) [ 58 , 74 , 75 , 84 , 90 – 94 , 100 ], Social Cognitive Theory (3.5%; n = 2) [ 79 , 104 ], Prochaska and DiClementes’ Transtheoretical model of the Stages of Change (3.5%; n = 2) [ 51 , 55 , 66 , 82 ], Social Learning Theory (1.8%, n = 1) [ 44 ], Normalization Process Theory [ 31 ] and Implementation Intention Theory (1.8%; n = 1) [ 104 ]. Intervention fidelity was reported in 21 studies (27.6%; n = 16).

Training of primary care provider to deliver SMS.

70.7% (n = 41) of studies included upskilling of HCPs to deliver the intervention. Training aimed at enhancing aspects of patient self-efficacy including mastery achievements, positive learning, adjustment to stress, verbal encouragement and outcome expectations. Intervention approaches were underpinned by the use of core communication skills to build trust and rapport in the patient-provider relationship, and as such providers were trained in areas including active listening, non-verbal communication, reflection, empathy and affirmation. Studies reported the provision of HCP resources to support self-management, e.g. written material or manuals, feedback on care reports, video demonstrations or case studies, and tools to assess patient support needs and priorities (PRISMS).

Interventions reporting positive findings for clinical and humanistic measures

Thirteen RCTs targeting a range of conditions including asthma, T2DM, COPD, recurrent binge eating, chronic fatigue, major depression, low self-esteem, IBS and depression reported positive findings for all clinical and humanistic outcome measures ( Table 4 ) [ 42 , 66 , 67 , 72 , 75 , 80 , 91 , 92 , 95 , 100 , 117 ].

https://doi.org/10.1371/journal.pone.0220116.t004

A mean of five self-management components (SD 1.7) were included in effective interventions. Elements most frequently reported to enhance the patient’s role in self-management included information provision (100.0%; n = 13), enhancing problem-solving or decision-making skills (76.9%; n = 10), active stimulation of symptom monitoring (46.2%; n = 6), medication management or adherence (46,2%; n = 6), strategies for stress or psychological management of condition (46.2%; n = 6) or enhancing dietary intake (46.2%; n = 6). The total duration of interventions ranged from 4 to 52 weeks. Initial consultations were on average 62 minutes (SD 13.8). Follow-up was delivered face-to-face in 11 interventions (84.6%; n = 11), and two studies reported telephone follow up (15.4%; n = 2). Studies reported mean of five follow-up sessions (SD 3.6) on average, ranging from 1 to 12 sessions. Mean duration of follow up sessions were 57 minutes (SD 18.5). Individuals were provided self-help support materials or resources in majority of interventions (92.3%; n = 12). Accompanying patient materials provided in addition to face-to-face sessions included manuals, information or educational booklets to work through at home, personalized treatment or action plans, devices and diaries for self-monitoring, goal setting forms or individualized dietary plans. Six RCTs incorporated a theoretical underpinning in their intervention: cognitive behavioral theory (30.8%; n = 4) and Prochaska and DiClementes’ transtheoretical model of the stages of change (15.4%; n = 2). Five integrated cognitive behavioral therapy (CBT) into their intervention (38.5%; n = 5).

Barbanel et al. [ 80 ] and Goudswaard et al. [ 42 ] targeted asthma and T2DM respectively and produced positive improvements in clinical outcomes. The SMS intervention evaluated by Barbanel et al. [ 80 ] examined the impact of a self-management program delivered by community pharmacists on asthma control. Intervention participants received self-management support from the pharmacist with weekly telephone follow-up for 3 months. This included a review of inhaler technique, skills including monitoring of peak flow, and a personalized action plan for worsening symptoms or exacerbations. Symptom scores improved in the intervention group and marginally worsened in the control group to 20.3 (4.2) and 28.1 (3.5), respectively (p<0.001; adjusted difference = 7.0 (95% CI: 4.4, 9.5). Goudswaard et al. [ 42 ] evaluated long-term effects of nurse-delivered self-management education in type 2 diabetics. The intervention focused on medication adherence, enhancing physical exercise, dietary intake and self-monitoring blood glucose at home. Six sessions were provided at intervals of 3–6 weeks, resulting in contact time of approximately 2.5 hours with HCPs over 6 months. HbA1c levels improved from 8.2% to 7.2% in the intervention group and 8.8% to 8.4% in usual care at 6 weeks, however this result was not sustained at 18 months [ 42 ].

Efraimsson et al. [ 66 ] examined effects of nurse-led COPD intervention. Patients received education on self-care ability to cope with disease and treatment. Patients were scheduled for two visits with nurses lasting 60 minutes during a 5-month period. A statistically significant increase was noted in the intervention group on QOL, the proportion of patients who ceased smoking, and patients’ knowledge about COPD at 3–5 month follow up, compared with usual care. Heitkemper et al. [ 91 ] examined an intervention delivered to women with IBS. Women in the intervention received eight weekly 1-hour individual sessions. The intervention included education, dietary counselling, symptom monitoring, relaxation training and cognitive-behavioral strategies including anger management, cognitive restructuring, assertiveness and social skills training [ 91 ]. Hill et al. [ 67 ] examined an intervention in people with COPD. Intervention participants attended two one-to-one 60-minute sessions, focusing on enhancing self-efficacy. Sessions were accompanied by a written manual adapted from the "Living Well with COPD" program. COPD knowledge increased from 27.6 (+/- 8.7) to 36.5 (+/- 7.7) in the intervention group, which was greater than any difference seen in the control group. Waite et al. [ 100 ] examined an individualized intervention for patients with low self-esteem. This included goal setting, learning skills to re-evaluate anxious and self-critical thoughts and beliefs through cognitive techniques. All participants were given a three-part self-help workbook in addition to individual treatment sessions. The intervention showed significantly better functioning than control on measures of overall functioning and depression and had fewer psychiatric diagnoses at the end of treatment. All treatment gains were maintained at follow-up assessment. Williams et al. [ 75 ] evaluated a guided self-help intervention for depression in primary care. The first appointment focused on an introduction to the use of the self-help materials. Three additional face-to-face support sessions of approximately 40 minutes were provided on a weekly or fortnightly basis. Mean Beck Depression Inventory (BDI-II) scores were lower in the intervention group at 4 months by 5.3 points, compared with control (2.6 to 7.9, p = 0.001). There were also significantly higher proportions of intervention participants achieving a 50% reduction in BDI-II scores at 4 and 12 months.

McLean et al. [ 82 ] involved a pharmacist-delivered intervention for asthma self-management. The intervention involved education surrounding the basic concepts of disease, medications, trigger identification and avoidance, and an asthma action plan. Patients were taught to use a peak flow meter, spacer devices, calendars/diaries were provided and asked to record peak expiratory flow rates (PEFRs) regularly for the course of the study period. Patients received appointments of approximately one hour in length with a pharmacist in a private counselling area every two to three weeks for at least three appointments, and then follow-up appointments at least quarterly for 12 months [ 82 ]. Symptom scores decreased by 50% (p<0.05) and peak flow readings increased by 11% (p = 0.0002) for intervention patients, compared to those receiving usual care. Chalder et al. [ 95 ] evaluated the efficacy of a self‐help booklet and advice delivered by a nurse in reducing chronic fatigue in adult patients. The intervention reiterated self-monitoring and maintaining symptom diaries. Basic cognitive techniques such as identifying and challenging unhelpful thoughts were also introduced. The self‐help group showed significantly greater improvements in fatigue (p = 0.01) and psychological distress (p<0.01) than controls. Striegel-Moore et al. [ 92 , 117 ] evaluated cognitive behavioural guided self-help for the treatment of recurrent binge eating. Intervention participants received 8 sessions over 12 weeks. The primary focus of this intervention was on developing a regular pattern of moderate eating using self-monitoring and problem-solving. The main outcome, abstinence from binge eating differed significantly between the groups: the initial improvement in abstinence from baseline was greater for the intervention group than usual care (p<0.001). Watkins et al. [ 72 ] evaluated guided self-help concreteness training as an intervention for major depression. During the initial session of the self-help intervention, psycho-education and training exercises were provided. During the follow-up telephone sessions, feedback, guidance and encouragement was provided to ensure accurate use of exercises, and progress monitored. The intervention resulted in significantly fewer depressive symptoms post-treatment, relative to treatment as usual (ITT, p = 0.006, effect size d for change in Hamilton Rating Scale for Depression (HAMD) = 0.76; PP, p<0.0001, d = 1.06).

Quality risk of bias assessment of individual studies

The overall methodological quality was considered high (lower risk of bias) in 41.4% of studies (n = 24 RCTs), and of medium quality in 58.6% of studies (n = 34 RCTs). The domains considered lowest risk of bias were selective reporting (96.6%; n = 56), baseline outcome measures (84.5%; n = 49), random sequence generation (79.3%; n = 46) and baseline characteristics (79.3%; n = 46). The domains with higher risk of bias were ‘blinding of outcome assessment’ (25.9% of studies; n = 15). Reporting bias was judged low for more than 95% of studies. Half of studies (51.7%; n = 30) presented low risk for the domain ‘other bias’. Reasons for other risk of bias included not meeting recruitment targets for assumed power. Fig 2 shows aggregate appraisal of risk of bias of included studies and visual representation of each domain.

https://doi.org/10.1371/journal.pone.0220116.g002

This systematic review has synthesized evidence from 58 randomized controlled trials examining the effectiveness of primary HCP delivered self-management support interventions for adult patients, with any condition, compared to usual standard of care. We describe effective SMS interventions and have highlighted their active elements, identified trends in combinations of intervention strategies, range of outcomes measured and the magnitude of effect size. This review demonstrates that SMS interventions delivered face-to-face by primary HCPs, which are multicomponent and tailored to explicitly enhance patient self-management skill set can lead to improvements in clinical and humanistic outcomes. The various tools and strategies that provide a structure to interventions delivered face-to-face include adapting interventions according to patients’ readiness to change, action planning and goal setting by collaboratively breaking down individual health goals into small achievable actions. The effectiveness of multicomponent SMS interventions is not surprising. But it raises the question of how to focus efforts on the best combination of active components within interventions. The variation in context, outcome measures, training methodology used across the 58 studies, in addition to the high degree of autonomy given to providers, deem the evaluation of SMS interventions more difficult.

Ninety-three different outcome measures were adopted to demonstrate evaluated impact of the various interventions and presumably were selected to reflect expected outcomes or processes of self-management. These include different measures of health-related quality of life, overall functioning, self-efficacy, health behaviours, disease knowledge, symptoms and disease control. Disease specific clinical indicators were mostly included as primary outcomes, and QoL indicators generally served as secondary or ancillary outcomes to primary outcome criteria. Generic HRQOL measures varied across different types of diseases, interventions and groups (i.e. EQ5D, SF-12), and specific HRQOL disease measures were also utilized. (i.e. IBSQOL questionnaire was used to measure changes in HRQOL for IBS patients). Further examination of studies producing positive improvements in HRQOL revealed use of disease specific measures (i.e. Ferrone et al. [ 71 ] reported positive changes in HRQOL using the Clinical COPD Questionnaire (CCQ)—a 10-item, health-related quality of life questionnaire). Interestingly, studies using more generic HRQOL measures (i.e. EQ5D, SF scales) mostly reported insignificant differences in their interventions. S4 Table provides a summary of the various instruments used in studies.

Our findings reveal a structured patient-provider exchange is required in primary care (including a one-on-one patient-provider consultation, ongoing follow up and provision of self-help materials). A systematic and tailored patient-primary care provider exchange is needed to provide individuals with the portfolio of techniques and tools to effectively self-manage. Various combinations of strategies were used to achieve this and adapted to the individuals’ condition, health literacy, skills and confidence in managing their own health. Strategies containing several interacting components and varying dimensions of complexity produce favourable effects when tailored to the individual. No one intervention solution is suitable for all patient groups and the selection of combinations of strategies should support patients’ needs relevant to both primary care and HCP. The strategy of enhancing the patient’s decision-making skills or ability to problem-solve was reported in the highest percentage of studies (53.8%) with positive results, after knowledge acquisition. Active stimulation of symptom monitoring (46.2%) and having specific, clear and accepted treatment or healthcare goals was also commonly identified. This involved setting measurable, clear and accepted treatment or healthcare goals on a per patient basis with a specific action or self-management plan detailing these. Tailored, written information and care plans that are mutually agreed upon have previously been identified as helpful [ 138 ]. Strategies to improve responsibility in medication adherence and lifestyle choices were also reported within effective interventions.

Interestingly, strategies for stress or psychological coping of conditions (46.2%) were commonly identified in effective interventions. Changing the patient’s cognitive approach to their illness was commonly incorporated into the intervention to deal with the physical and emotional symptoms resulting from a chronic illness. Effective interventions integrated cognitive behavioral therapy (CBT) into the intervention in 40% of studies. Multiple cognitive strategies were raised, such as identifying and challenging unhelpful thoughts [ 95 ], relaxation training and cognitive-behavioral strategies including anger management, cognitive restructuring, assertiveness and social skills training [ 91 ]. A 2014 systematic review of qualitative literature identified patients often express difficulties in dealing with the physical and emotional symptoms of their chronic conditions [ 138 ]. As such, undesirable physical and emotional symptoms and impaired physical functioning can directly prevent patients from carrying out normal daily activities, including tasks required to appropriately and successfully self-manage [ 139 – 141 ]. Self-management of chronic conditions should therefore be examined not only from the clinical perspective, but also the patient perspective with a focus on humanistic outcomes. Importantly, the theory of SMS drawn for effective studies included Cognitive Behavioral Theory and Prochaska and DiClementes’ transtheoretical model of the stages of change. Follow-up by HCPs included tailored feedback, monitoring of progress with respect to patient set healthcare goals, or honing problem-solving and decision-making skills. Self-help tools and assistance with locating resources were commonly provided during the patient-provider exchange.

The scope of the terms ‘self-management’, ‘self-management support’ and ‘self-management support interventions’ in literature and the large heterogeneity in terminology has repeatedly been highlighted in previous systematic reviews and meta-analyses [ 27 , 142 – 144 ]. This is a key limitation, as very broad or very narrow definitions of what constitutes “self-management support” have been applied. Lorig and Holman [ 10 ] previously underlined the need to explore interventions beyond the label of self-management to define if interventions actually address the necessary support strategies required to change behaviour. Subtle variations in self-management definitions can result in substantial differences in selected studies. Using Jonkman’s operational definition [ 35 ] to define our interventions has shown highly important in distinguishing self-management interventions from other types of interventions (ie. patient education or disease management) without being too restrictive. The definition clearly defines the elements or strategies that constitute a self-management support intervention, with the pivotal objective of changing behaviour. This has guided the selection of studies on which our review conclusions have been based.

A notable gap identified in the literature was a lack of focus on multimorbidity. This is understood to pose challenges for self-management, as many individuals have more than one health condition [ 138 ]. The effects of multimorbidity on a person are not always linear. Interestingly enough, some studies have found that patients with multimorbidity consider themselves better at self-management because they had already developed skills such as self-monitoring and self-advocacy [ 145 ].

In acknowledging that SMS is a multidimensional topic, we aimed to create a broader picture of the landscape of SMS in primary care. This was achieved by evaluating the patterns of intervention components comprehensively across all conditions, by not limiting our research to a clinical condition, or specific intervention strategies. Although including different clinical conditions in the review may be considered as a drawback due the potential heterogeneity induced, in our research, there was a clear distinction of strategies across the conditions studied. Findings from this review add further detail to this body of knowledge, while providing HCPs with a number of evidence-based strategies that can be utilized in practice. These findings pave the way to explore further SMS strategies targeting patient’s behaviour change, effective patterns of strategies, and develop a more evidence-based model for optimum SMS service design. Primary care providers (e.g. general practitioners, nurses, pharmacists) can play a foundational role in supporting patient self-management, especially for people with multiple chronic conditions. Fig 3 sets the foundation for an evidence-based SMS primary care model for face-to-face interventions, allowing for a more efficient and effective process to evaluate and implement SMS interventions in primary care.

Modelled on the definition of self-management interventions by Jonkman et al. 2016 [ 35 ].

https://doi.org/10.1371/journal.pone.0220116.g003

For this collaborative partnership approach to be more widely applied, there should be a strong focus on upskilling primary care providers to deliver SMS strategies in health care, which are both integrated and coordinated to improve the patient-provider encounter in practice [ 5 ]. The total duration of the intervention and the correlation of intervention duration with the number of strategies delivered are important aspects when considering the sustainability within primary care. Policy and funding alignment will also be a major determinant for future sustainability. Therefore, we must determine where the best compromise in SMS interventions lie for cost-effective and resource-limited approaches. Future high-quality evaluations of consistent interventions will be of value to practitioners, policy-makers and researchers in terms of collecting clinical, humanistic and economic outcome measures to generate a robust evidence base of primary care providers impact in the area. This will also allow determination of ineffective combinations of strategies.

Future research efforts should continue to expand on this landscape to (1) examine the patterns of strategies within effective multicomponent interventions for various conditions; (2) examine the weighting of each strategy (ie. determine intervention components which are more or less effective) within effective multicomponent interventions; (3) determine if certain types of patient populations could be targeted most effectively by certain combinations of strategies; (4) develop a core SMS outcome set in primary care; (5) examine the patient’s ability to self-manage over time as well as aiming to achieve the goal of long-term sustainability for improved self-management; and (6) determine training requirements for the upskilling of health care providers for sustained patient behaviour change.

Furthermore, sustainability of improved SMS first requires an understanding of the implementation of SMS enhancing interventions [ 146 ]. Sustainability can be challenging if not embedded into everyday clinical practice [ 31 ], and achieving the potential of primary care as a platform to effectively deliver SMS and achieve the stated outcomes means overcoming known barriers, such as limited time, skills and confidence among health professionals [ 31 , 147 ]. We know changes in health care professional practice requires exhaustive planning and testing to increase the probability that they are successfully and sustainably implemented. The adoption of Intervention Mapping has been widely used in health care settings to plan changes in the behaviour and practice of health care professionals, and should be applied to ensure SMS interventions are both effective and successfully implemented in practice [ 148 ].

There are limitations to this review. A number of studies did not report sufficient detail to their interventions which hampered the assessment of possible effective combinations of strategies being evaluated. The methodological quality domains of the included trials were in a lot of cases unclear, with a lack of poor description of the study methodology and intervention fidelity in evaluations. This was mitigated by contacting authors for further relevant information, searching for study protocols or further examining supplementary data online. With the growing recognition of the importance of assessing treatment fidelity in multicomponent interventions [ 149 – 151 ] (ie. compliance to treatment protocols by HCPs, or compliance to treatment by patients), it is important to note most trials (72%) did not include this in their design and few provided data on treatment fidelity to the intervention. Only 38% of effective interventions reported an assessment of intervention fidelity. The methodological quality domains of the included trials were in a lot of cases unclear. Four high-quality studies provided positive evidence that SMS interventions delivered in primary care dominate usual standard of care, by improving patients’ clinical outcomes, HRQOL or psychological functioning [ 72 , 91 , 92 , 100 ]. Similar trends have been found in existing literature in several contexts that self-management is essential to optimizing clinical and humanistic outcomes for patients with chronic conditions [ 13 , 15 , 18 , 152 – 155 ].

Although multiple databases were extensively searched using clear, specific and appropriate terms, the search may not have yielded all published relevant studies given the ambiguity of what constitutes “self-management support” and the variation in terminology for “self-management” identified in the literature. Unsurprisingly, with the rising burden of chronic disease, the nomenclature of “self-management” has become more prevalent in both published and grey literature. We recognize the use of different search terms and definitions to guide the development of the search strategy may lead to variation in the identification of studies, and affect a review's conclusions. This is identified as a limitation of our review. Search terms were sourced from previous systematic reviews, primary studies and grey literature. Our search included general terms for “self-management” and was not limited to specific illnesses or outcomes.

Systematic reviews are at risk for bias from a number of sources [ 156 ]. We sought to reduce potential sources of bias within the inclusion and synthesis of studies. One of our main goals was developing inclusion criteria to minimize ambiguity and reduce bias in study selection decisions. We have defined our inclusion and exclusion criteria by PICO clearly and have documented and reported all decisions made in the study selection process for transparency. Since we restricted our review to face-to-face interventions, there may be other SMS interventions that may be effective that are not covered by this review. We decided to categorize the comparator as usual standard of care and understand the definition of usual standard of care may vary by country or healthcare system.

In conclusion, this review highlights core components of successful interventions showing positive clinical and/or humanistic outcomes. Whilst it was difficult to directly correlate individual strategies to outcomes and effectiveness, there was a clear distinction of strategies across the conditions studied. This review provides encouraging groundwork for the design and evaluation of practical strategies for evidence-based practice and the construction of self-management support processes in primary healthcare practice. This review may assist in determining the breadth and focus of the support primary care professionals provide. Application of a theoretical perspective provides a strong base for the development of SMS interventions. The developed model sets the foundation for the design and evaluation of practical strategies for the construct of self-management support in primary healthcare practice. These results may be used to justify additional research investigating self-management interventions delivered in the primary care setting. In response, primary care providers can begin to deeply reflect on current practice and become involved in a dialogue to improve self-management support. Critically, these results should stimulate informed discussion for the future delivery of self-management support in primary care and the requirements for upskilling healthcare providers to effectively support patients in this collaborative process.

Supporting information

S1 data. database..

https://doi.org/10.1371/journal.pone.0220116.s001

S1 Table. Search strategy.

https://doi.org/10.1371/journal.pone.0220116.s002

S2 Table. PRISMA checklist.

https://doi.org/10.1371/journal.pone.0220116.s003

S3 Table. Descriptive characteristics of included studies.

https://doi.org/10.1371/journal.pone.0220116.s004

S4 Table. Summary of findings and extracted outcomes.

https://doi.org/10.1371/journal.pone.0220116.s005

S5 Table. Mapping of intervention components.

https://doi.org/10.1371/journal.pone.0220116.s006

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Clinical problem solving and diagnostic decision making: selective review of the cognitive literature

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This article has a correction. Please see:

• Clinical problem solving and diagnostic decision making: selective review of the cognitive literature - November 02, 2006
• Arthur S Elstein , professor ( aelstein{at}uic.edu ) ,
• Alan Schwarz , assistant professor of clinical decision making.
• Department of Medical Education, University of Illinois College of Medicine, Chicago, IL 60612-7309, USA
• Correspondence to: A S Elstein

This is the fourth in a series of five articles

This article reviews our current understanding of the cognitive processes involved in diagnostic reasoning in clinical medicine. It describes and analyses the psychological processes employed in identifying and solving diagnostic problems and reviews errors and pitfalls in diagnostic reasoning in the light of two particularly influential approaches: problem solving 1 , 2 , 3 and decision making. 4 , 5 , 6 , 7 , 8 Problem solving research was initially aimed at describing reasoning by expert physicians, to improve instruction of medical students and house officers. Psychological decision research has been influenced from the start by statistical models of reasoning under uncertainty, and has concentrated on identifying departures from these standards.

Summary points

Problem solving and decision making are two paradigms for psychological research on clinical reasoning, each with its own assumptions and methods

The choice of strategy for diagnostic problem solving depends on the perceived difficulty of the case and on knowledge of content as well as strategy

Final conclusions should depend both on prior belief and strength of the evidence

Conclusions reached by Bayes's theorem and clinical intuition may conflict

Because of cognitive limitations, systematic biases and errors result from employing simpler rather than more complex cognitive strategies

Evidence based medicine applies decision theory to clinical diagnosis

Problem solving

Diagnosis as selecting a hypothesis.

The earliest psychological formulation viewed diagnostic reasoning as a process of testing hypotheses. Solutions to difficult diagnostic problems were found by generating a limited number of hypotheses early in the diagnostic process and using them to guide subsequent collection of data. 1 Each hypothesis can be used to predict what additional findings ought to be present if it were true, and the diagnostic process is a guided search for these findings. Experienced physicians form hypotheses and their diagnostic plan rapidly, and the quality of their hypotheses is higher than that of novices. Novices struggle to develop a plan and some have difficulty moving beyond collection of data to considering possibilities.

It is possible to collect data thoroughly but nevertheless to ignore, to misunderstand, or to misinterpret some findings, but also possible for a clinician to be too economical in collecting data and yet to interpret accurately what is available. Accuracy and thoroughness are analytically separable.

Pattern recognition or categorisation

Expertise in problem solving varies greatly between individual clinicians and is highly dependent on the clinician's mastery of the particular domain. 9 This finding challenges the hypothetico-deductive model of clinical reasoning, since both successful and unsuccessful diagnosticians use hypothesis testing. It appears that diagnostic accuracy does not depend as much on strategy as on mastery of content. Further, the clinical reasoning of experts in familiar situations frequently does not involve explicit testing of hypotheses. 3 10 , 11 , 12 Their speed, efficiency, and accuracy suggest that they may not even use the same reasoning processes as novices. 11 It is likely that experienced physicians use a hypothetico-deductive strategy only with difficult cases and that clinical reasoning is more a matter of pattern recognition or direct automatic retrieval. What are the patterns? What is retrieved? These questions signal a shift from the study of judgment to the study of the organisation and retrieval of memories.

Problem solving strategies

Hypothesis testing

Pattern recognition (categorisation)

By specific instances

By general prototypes

Viewing the process of diagnosis assigning a case to a category brings some other issues into clearer view. How is a new case categorised? Two competing answers to this question have been put forward and research evidence supports both. Category assignment can be based on matching the case to a specific instance (“instance based” or “exemplar based” recognition) or to a more abstract prototype. In the former, a new case is categorised by its resemblance to memories of instances previously seen. 3 11 This model is supported by the fact that clinical diagnosis is strongly affected by context—for example, the location of a skin rash on the body—even when the context ought to be irrelevant. 12

The prototype model holds that clinical experience facilitates the construction of mental models, abstractions, or prototypes. 2 13 Several characteristics of experts support this view—for instance, they can better identify the additional findings needed to complete a clinical picture and relate the findings to an overall concept of the case. These features suggest that better diagnosticians have constructed more diversified and abstract sets of semantic relations, a network of links between clinical features and diagnostic categories. 14

The controversy about the methods used in diagnostic reasoning can be resolved by recognising that clinicians approach problems flexibly; the method they select depends upon the perceived characteristics of the problem. Easy cases can be solved by pattern recognition: difficult cases need systematic generation and testing of hypotheses. Whether a diagnostic problem is easy or difficult is a function of the knowledge and experience of the clinician.

The strategies reviewed are neither proof against error nor always consistent with statistical rules of inference. Errors that can occur in difficult cases in internal medicine include failure to generate the correct hypothesis; misperception or misreading the evidence, especially visual cues; and misinterpretations of the evidence. 15 16 Many diagnostic problems are so complex that the correct solution is not contained in the initial set of hypotheses. Restructuring and reformulating should occur as data are obtained and the clinical picture evolves. However, a clinician may quickly become psychologically committed to a particular hypothesis, making it more difficult to restructure the problem.

Decision making

Diagnosis as opinion revision.

From the point of view of decision theory, reaching a diagnosis means updating opinion with imperfect information (the clinical evidence). 8 17 The standard rule for this task is Bayes's theorem. The pretest probability is either the known prevalence of the disease or the clinician's subjective impression of the probability of disease before new information is acquired. The post-test probability, the probability of disease given new information, is a function of two variables, pretest probability and the strength of the evidence, measured by a “likelihood ratio.”

Bayes's theorem tells us how we should reason, but it does not claim to describe how opinions are revised. In our experience, clinicians trained in methods of evidence based medicine are more likely than untrained clinicians to use a Bayesian approach to interpreting findings. 18 Nevertheless, probably only a minority of clinicians use it in daily practice and informal methods of opinion revision still predominate. Bayes's theorem directs attention to two major classes of errors in clinical reasoning: in the assessment of either pretest probability or the strength of the evidence. The psychological study of diagnostic reasoning from this viewpoint has focused on errors in both components, and on the simplifying rules or heuristics that replace more complex procedures. Consequently, this approach has become widely known as “heuristics and biases.” 4 19

Errors in estimation of probability

Availability —People are apt to overestimate the frequency of vivid or easily recalled events and to underestimate the frequency of events that are either very ordinary or difficult to recall. Diseases or injuries that receive considerable media attention are often thought of as occurring more commonly than they actually do. This psychological principle is exemplified clinically in the overemphasis of rare conditions, because unusual cases are more memorable than routine problems.

Representativeness —Representativeness refers to estimating the probability of disease by judging how similar a case is to a diagnostic category or prototype. It can lead to overestimation of probability either by causing confusion of post-test probability with test sensitivity or by leading to neglect of base rates and implicitly considering all hypotheses equally likely. This is an error, because if a case resembles disease A and disease B equally, and A is much more common than B, then the case is more likely to be an instance of A. Representativeness is associated with the “conjunction fallacy”—incorrectly concluding that the probability of a joint event (such as the combination of findings to form a typical clinical picture) is greater than the probability of any one of these events alone.

Heuristics and biases

Availability

Representativeness

Probability transformations

Effect of description detail

Conservatism

Anchoring and adjustment

Order effects

Decision theory assumes that in psychological processing of probabilities, they are not transformed from the ordinary probability scale. Prospect theory was formulated as a descriptive account of choices involving gambling on two outcomes, 20 and cumulative prospect theory extends the theory to cases with multiple outcomes. 21 Both prospect theory and cumulative prospect theory propose that, in decision making, small probabilities are overweighted and large probabilities underweighted, contrary to the assumption of standard decision theory. This “compression” of the probability scale explains why the difference between 99% and 100% is psychologically much greater than the difference between, say, 60% and 61%. 22

Support theory

Support theory proposes that the subjective probability of an event is inappropriately influenced by how detailed the description is. More explicit descriptions yield higher probability estimates than compact, condensed descriptions, even when the two refer to exactly the same events. Clinically, support theory predicts that a longer, more detailed case description will be assigned a higher subjective probability of the index disease than a brief abstract of the same case, even if they contain the same information about that disease. Thus, subjective assessments of events, while often necessary in clinical practice, can be affected by factors unrelated to true prevalence. 23

Errors in revision of probability

In clinical case discussions, data are presented sequentially, and diagnostic probabilities are not revised as much as is implied by Bayes's theorem 8 ; this phenomenon is called conservatism. One explanation is that diagnostic opinions are revised up or down from an initial anchor, which is either given in the problem or subjectively formed. Final opinions are sensitive to the starting point (the “anchor”), and the shift (“adjustment”) from it is typically insufficient. 4 Both biases will lead to collecting more information than is necessary to reach a desired level of diagnostic certainty.

It is difficult for everyday judgment to keep separate accounts of the probability of a disease and the benefits that accrue from detecting it. Probability revision errors that are systematically linked to the perceived cost of mistakes show the difficulties experienced in separating assessments of probability from values, as required by standard decision theory. There is a tendency to overestimate the probability of more serious but treatable diseases, because a clinician would hate to miss one. 24

Bayes's theorem implies that clinicians given identical information should reach the same diagnostic opinion, regardless of the order in which information is presented. However, final opinions are also affected by the order of presentation of information. Information presented later in a case is given more weight than information presented earlier. 25

Other errors identified in data interpretation include simplifying a diagnostic problem by interpreting findings as consistent with a single hypothesis, forgetting facts inconsistent with a favoured hypothesis, overemphasising positive findings, and discounting negative findings. From a Bayesian standpoint, these are all errors in assessing the diagnostic value of clinical evidence—that is, errors in implicit likelihood ratios.

Educational implications

Two recent innovations in medical education, problem based learning and evidence based medicine, are consistent with the educational implications of this research. Problem based learning can be understood as an effort to introduce the formulation and testing of clinical hypotheses into the preclinical curriculum. 26 The theory of cognition and instruction underlying this reform is that since experienced physicians use this strategy with difficult problems, and since practically any clinical situation selected for instructional purposes will be difficult for students, it makes sense to provide opportunities for students to practise problem solving with cases graded in difficulty. The finding of case specificity showed the limits of teaching a general problem solving strategy. Expertise in problem solving can be separated from content analytically, but not in practice. This realisation shifted the emphasis towards helping students acquire a functional organisation of content with clinically usable schemas. This goal became the new rationale for problem based learning. 27

Evidence based medicine is the most recent, and by most standards the most successful, effort to date to apply statistical decision theory in clinical medicine. 18 It teaches Bayes's theorem, and residents and medical students quickly learn how to interpret diagnostic studies and how to use a computer based nomogram to compute post-test probabilities and to understand the output. 28

We have selectively reviewed 30 years of psychological research on clinical diagnostic reasoning. The problem solving approach has focused on diagnosis as hypothesis testing, pattern matching, or categorisation. The errors in reasoning identified from this perspective include failure to generate the correct hypothesis; misperceiving or misreading the evidence, especially visual cues; and misinterpreting the evidence. The decision making approach views diagnosis as opinion revision with imperfect information. Heuristics and biases in estimation and revision of probability have been the subject of intense scrutiny within this research tradition. Both research paradigms understand judgment errors as a natural consequence of limitations in our cognitive capacities and of the human tendency to adopt short cuts in reasoning.

Both approaches have focused more on the mistakes made by both experts and novices than on what they get right, possibly leading to overestimation of the frequency of the mistakes catalogued in this article. The reason for this focus seems clear enough: from the standpoint of basic research, errors tell us a great deal about fundamental cognitive processes, just as optical illusions teach us about the functioning of the visual system. From the educational standpoint, clinical instruction and training should focus more on what needs improvement than on what learners do correctly; to improve performance requires identifying errors. But, in conclusion, we emphasise, firstly, that the prevalence of these errors has not been established; secondly, we believe that expert clinical reasoning is very likely to be right in the majority of cases; and, thirdly, despite the expansion of statistically grounded decision supports, expert judgment will still be needed to apply general principles to specific cases.

Series editor J A Knottnerus

Preparation of this review was supported in part by grant RO1 LM5630 from the National Library of Medicine.

Competing interests None declared.

“The Evidence Base of Clinical Diagnosis,” edited by J A Knottnerus, can be purchased through the BMJ Bookshop ( http://www.bmjbookshop.com/ )

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• Open access
• Published: 29 March 2022

A framework of evidence-based decision-making in health system management: a best-fit framework synthesis

• Tahereh Shafaghat 1 , 2   na1 ,
• Peivand Bastani   ORCID: orcid.org/0000-0002-0412-0267 1 , 3   na1 ,
• Mohammad Hasan Imani Nasab 4 ,
• Mohammad Amin Bahrami 1 ,
• Mahsa Roozrokh Arshadi Montazer 5 ,
• Mohammad Kazem Rahimi Zarchi 2 &
• Sisira Edirippulige 6  

Archives of Public Health volume  80 , Article number:  96 ( 2022 ) Cite this article

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Scientific evidence is the basis for improving public health; decision-making without sufficient attention to evidence may lead to unpleasant consequences. Despite efforts to create comprehensive guidelines and models for evidence-based decision-making (EBDM), there isn`t any to make the best decisions concerning scarce resources and unlimited needs . The present study aimed to develop a comprehensive applied framework for EBDM.

This was a Best-Fit Framework (BFF) synthesis conducted in 2020. A comprehensive systematic review was done via six main databases including PUBMED, Scopus, Web of Science, Science Direct, EMBASE, and ProQuest using related keywords. After the evidence quality appraisal, data were extracted and analyzed via thematic analysis. Results of the thematic analysis and the concepts generated by the research team were then synthesized to achieve the best-fit framework applying Carroll et al. (2013) approach.

Four thousand six hundred thirteen studies were retrieved, and due to the full-text screening of the studies, 17 final articles were selected for extracting the components and steps of EBDM in Health System Management (HSM). After collecting, synthesizing, and categorizing key information, the framework of EBDM in HSM was developed in the form of four general scopes. These comprised inquiring, inspecting, implementing, and integrating, which included 10 main steps and 47 sub-steps.

Conclusions

The present framework provided a comprehensive guideline that can be well adapted for implementing EBDM in health systems and related organizations especially in underdeveloped and developing countries where there is usually a lag in updating and applying evidence in their decision-making process. In addition, this framework by providing a complete, well-detailed, and the sequential process can be tested in the organizational decision-making process by developed countries to improve their EBDM cycle.

Peer Review reports

Globally, there is a growing interest in using the research evidence in public health policy-making [ 1 , 2 ]. Public health systems are diverse and complex, and health policymakers face many challenges in developing and implementing policies and programs that are required to be efficient [ 1 , 3 ]. The use of scientific evidence is considered to be an effective approach in the decision-making process [ 3 , 4 , 5 ]. Due to the lack of sufficient resources, evidence-based decision-making ( EBDM) is regarded as a way to optimize costs and prevent wastes [ 6 ]. At the same time, the direct consequence of ignoring evidence is poorer health for the community [ 7 ].

Evidence suggests that health systems often fail to exploit research evidence properly, leading to inefficiencies, death or reduced quality of citizens’ lives, and a decline in productivity [ 8 ]. Decision-making in the health sector without sufficient attention to evidence may lead to a lack of effectiveness, efficiency, and fairness in health systems [ 9 ]. Instead, the advantages of EBDM include adopting cost-effective interventions, making optimal use of limited resources, increasing customer satisfaction, minimizing harm to individuals and society, achieving better health outcomes for individuals and society [ 10 , 11 ], as well as increasing the effectiveness and efficiency of public health programs [ 12 ].

Using the evidence in health systems’ policymaking is a considerable challenging issue that many developed and developing countries are facing nowadays. This is particularly important in the latter, where their health systems are in a rapid transition [ 13 ]. For instance, although in 2012, a study in European Union countries showed that health policymakers rarely had necessary structures, processes, and tools to exploit research evidence in the policy cycle [ 14 ], the condition can be worse among the developing and the underdeveloped ones. For example, evidence-based policy-making in developing countries like those located in the Middle East can have more significant impacts [ 15 , 16 ]. In such countries resources are generally scarce, so the policymakers' awareness of research evidence becomes more important [ 17 ]. In general, low and middle-income countries have fewer resources to deal with health issues and need quality evidence for efficient use of these resources [ 7 ].

Since the use of EBDM is fraught with the dilemma of most pressing needs and having the least capacity for implementation especially in developing countries [ 16 ], efforts have been made to create more comprehensive guidelines for EBDM in healthcare settings, in recent years [ 18 ]. Stakeholders are significantly interested in supporting evidence-based projects that can quickly prioritize funding allocated to health sectors to ensure the effective use of their financial resources [ 19 , 20 , 21 ]. However, it is unlikely that the implementation of EBDM in Health System Management (HSM) will follow the evidence-based medicine model [ 10 , 22 ]. On the other hand, the capacity of organizations to facilitate evidence utilization is complex and not well understood [ 22 ], and the EBDM process is not usually institutionalized within the organizational processes [ 10 ]. A study in 2005 found that few organizations support the use of research evidence in health-related decisions, globally [ 23 ]. Weis et al. (2012) also reported there is insufficient information on EBDM in local health sectors [ 12 ]. In general, it can be emphasized that relatively few organizations hold themselves accountable for using research evidence in developing health policies [ 24 ]. To the best of our knowledge, there isn`t any comprehensive global and practical model developed for EBDM in health systems/organizations management. Accordingly, the present study aimed to develop a comprehensive framework for EBDM in health system management. It can shed the light on policymakers to access a detailed practical model and enable them to apply the model in actual conditions.

This was a Best Fit Framework (BFF) synthesis conducted in 2020 to develop a comprehensive framework for EBDM in HSM. Such a framework synthesis is achieved as a combination of the relevant framework, theory, or conceptual models and particularly is applied for developing a priori framework based on deductive reasoning [ 25 ]. The BFF approach is appropriate to create conceptual models to describe or express the decisions and behaviors of individuals and groups in a particular domain. This is distinct from other methods of evidence synthesis because it employs a systematic approach to create an initial framework for synthesis based on existing frameworks, models, or theories [ 25 ] for identifying and adapting theories systematically with the rapid synthesis of evidence [ 25 , 26 ]. The initial framework can be derived from a relatively well-known model in the target field, or be formed by the integration of several existing models. The initial framework is then reduced to its key components that have shaped its concepts [ 25 ]. Indeed, the initial framework considers as the basis and it can be rebuilt, extended, or reduced based on its dimensions [ 26 ]. New concepts also emerge based on the researchers' interpretation of the evidence and ongoing comparisons of these concepts across studies [ 25 ]. This approach of synthesis possesses both positivist and interpretative perspectives; it provides the simultaneous use of the well-known strengths of both framework and evidence synthesis [ 27 ].

In order to achieve this aim the following methodological steps were conducted as follows:

Searching and selection of studies

In this step, we aimed to look for the relevant models and frameworks related to evidence-based decision-making in health systems management. The main research question was “what is the best framework for EBDM in health systems?” after defining the research question, the researchers searched for published studies on EBDM in HSM in different scientific databases with relevant keywords and constraints as inclusion and exclusion criteria from 01.01.2000 to 12.31.2020 (Table 1 ).

Inclusion and exclusion criteria

Inclusion criteria were determined as the studies that identify the components or develop a model or framework of EBDM in health organization in the form of original or review articles or dissertations, which were published in English and had a full text. The studies like book reviews, opinion articles, and commentaries that lacked a specific framework for conducting our review were excluded. During the search phase of the study, we attempted as much as possible to access studies that were not included in the search process or gray literature by reviewing the references lists of the retrieved studies or by contacting the authors of the articles or experts and querying them, as well as manually searching the related sites (Fig.  1 ).

The PRISMA flowchart for selection of the studies in scoping review

Quality appraisal

The quality of the obtained studies was investigated using three tools for assessing the quality of various types of studies considering types and methods of the final include studies in systematic review. These tools were including Critical Appraisal Skills Program (CASP) for assessing the quality of qualitative researches [ 28 ], Scale for the Assessment of Narrative Review Articles (SANRA) [ 29 ], and The Mixed Methods Appraisal Tool (MMAT) version 2018 for information professionals and researchers [ 30 ] (Table 3- Appendix ).

Data extraction

After searching the studies from all databases and removing duplicates, the studies were independently reviewed and screened by two members (TS and MRAM) of the research team in three phases by the title, abstract, and then the full text of the articles. At each stage of the study, the final decision to enter the study to the next stage was based on agreement and, in case of disagreement, the opinion of the third person from the research team was asked (PB). Mendeley reference manager software was used to systematically search and screen relevant studies. The data from the included studies were extracted based on the study questions and accordingly, a form of the studies’ profile including the author's name, publication year, country, study title, type of study, and its conditions were prepared in Microsoft Excel software (Table 4- Appendix ).

Synthesis and the conceptual model

In this step, a thematic analysis approach was applied to extract and analyze the data. For this purpose, first, the texts of the selected studies were read several times, and the initial qualitative codes or thematic concepts, according to the determined keywords and based on the research question, were found and labeled. Then these initial thematic codes were reviewed to achieve the final codes and they were integrated and categorized to achieve the final main themes and sub-themes, eventually. The main and the sub-themes are representative of the main and sub-steps of EBDM. At the last stage of the synthesis, the thematic analysis was finalized with 8 main themes and all the main and the sub-themes were tabulated (Table 5- Appendix ).

Creation of a new conceptual framework

For BFF synthesis in the present study, we compared the existing models and tried to find a model that fits the best. Three related models that appeared to be relatively well-suited to the purpose of this study to provide a complete, comprehensive, and practical EBDM model in HSM were found. According to the BFF instruction in Carroll et al. (2013) study [ 25 ], we decided to use all three models as the basis for the best fit because any of those models were not complete enough and we could give no one an advantage over others. Consequently, the initial model or the BFF basis was formed and the related thematic codes were classified according to the category of this basis as the main themes/steps of EBDM in HSM (Table 5- Appendix ). Then, the additional founded thematic codes were added and incorporated to this basis as the other main steps and the sub-steps of the EBDM in HSM according to the research team and some details in the form of sub-steps were added by the research team to complete the synthesized framework. Eventually, a comprehensive practical framework consisting of 10 main steps and 47 sub-steps was created with the potentiality of applying and implementing EDBM in HSM that we categorized them into four main phases (Table 6- Appendix ).

Testing the synthesis: comparison with the a priori models, dissonance and sensitivity

In order to assess the differences between the priori framework and the new conceptual framework, the authors tried to ask some experts’ opinions about the validity of the synthesized results. The group of experts has included eight specialists in the field of health system management or health policy-making. These experts have been chosen considering their previous research or experience in evidence-based decision/policy making performance/management (Table 2 ). This panel lasted in two three-hour sessions. The finalized themes and sub-themes (Table 6- Appendix ) and the new generated framework (Fig.  3 ) were provided to them before each session so that they could think and then in each meeting they discussed them. Finally, all the synthesized themes and sub-themes resulted were reviewed and confirmed by the experts.

Ethical considerations

To prevent bias, two individuals carried out all stages of the study such as screening, data extraction, and data analysis. The overall research project related to this manuscript was approved by the medical ethics conceal of the research deputy of Shiraz University of Medical Sciences with approval number IR.SUMS.REC.1396–01-07–14184, too.

The initial search across six electronic databases and the Cochrane library yielded 4613 studies. After removing duplicates, 2416 studies were assessed based on their titles. According to the abstract screening of the 1066 studies that remained after removing the irrelevant titles, 291 studies were selected and were entered into the full-text screening phase. Due to full-text screening of the studies, 17 final studies were selected for extracting the components and steps of EBDM in HSM (Fig.  1 ). The features of these studies were summarized in Table 4- Appendix (see supplementary data). Furthermore, according to the quality appraisal of the included studies, the majority of them had an acceptable level of quality. These results have been shown in Table 3- Appendix .

Results of the thematic analysis of the evidence (Table 5- Appendix ) along with the concepts proposed and added by the research team according to the focus-group discussion of the experts were shown in Table 6- Appendix . Accordingly, the main steps and related sub-steps of the EBDM process in HSM were defined and categorized.

After collecting, synthesizing, and categorizing thematic concepts, incorporating them with the initial models, and adding the additional main steps and sub-steps to the basic models, the final synthesized framework as a best-fit framework for EBDM in HSM was developed in the form of four general phases of inquiring, inspecting, implementing, and integrating and 10 main steps (Fig.  2 ). For better illustration, this framework with all the main steps and 47 sub-steps has been shown in Fig.  3 , completely.

The final synthesized framework of evidence-based decision-making in health system management

The main steps and sub-steps of the framework of EBDM in health system management

In the present study, a comprehensive framework for EBDM in HSM was developed. This model has different distinguishing characteristics than the formers. First of all, this is a comprehensive practical model that combined the strengths and the crucial components of the limited number of previous models; second, the model includes more details and complementary steps and sub-steps for full implementation of EBDM in health organizations and finally, the model is benefitted from a cyclic nature that has a priority than the linear models. Concerning the differences between the present framework and other previous models in this field, it must be said that most of the previous models related to EBDM were presented in the scope of medicine (that they were excluded from our SR according to the study objectives and exclusion criteria). A significant number of those models were proposed for the scope of public health and evidence-based practice, and only a limited number of them focused exactly on the scope of management and policy/decision making in health system organizations.

Given that the designed model is a comprehensive 10-step model, it can be used in some way at all levels of the health system and even in different countries. However, there will be a difference here, given that this framework provides a practical guide and a comprehensive guideline for applying evidence-based decision-making approach in health systems organizations, at each level of the health system in each country, this management approach can be applied depending on their existing infrastructure and the processes that are already underway (such as capacity building, planning, data collection, etc.), and at the same time, with a general guide, they can provide other infrastructure as well as the prerequisites and processes needed to make this approach much more possible and applicable.

It is true that evidence-based management is different from evidence-based medicine and even more challenging (due to lack of relevant data, greater sensitivity in data collection and their accuracy, lack of consistency and lack of transparency in the implementation of evidence-based decision-making in management rather than evidence-based medicine, etc.). Still, the general framework provided in this article can be used to help organizations that really want to act and move forward through this approach.

Furthermore, based on the findings, most of the previous studies only referred to some parts of the components and steps of the EBDM in health organizations and neglected the other parts or they were not sufficiently comprehensive [ 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. Most of the previous models did not mention the necessary sub-steps, tools, and practical details for accurate and complete implementation of the EBDM, which causes the organizations that want to use these models, will be confused and cannot fully implement and complete the EBDM cycle. Among the studies that have provided a partly complete model than the other studies, were the studies by Brownson (2009), Yost (2014), and Janati (2018) [ 3 , 41 , 42 ]. Consequently, the combination of these three studies has been used as the initial framework for the best-fit synthesis in the present study.

Likewise, the models presented by Brownson (2009) and Janati (2018) were only limited to the six or seven key steps of the EBDM process, and they did not mention the details required for doing in each step, too [ 3 , 4 , 42 ]. Also, the model presented in the study of Janati (2018) was linear, and the relationships between the EBDM components were not well considered [ 42 , 43 ]; however, the model presented in this study was recursive. Also, in Yost's study (2014), despite the 7 main steps of EBDM and some details of each of the steps, the proposed process was not schematically drawn in the form of a framework and therefore the relationships between steps and sub-steps were not clear [ 41 ]. According to what was discussed, the best-fit framework makes the possibility of concentrating the fragmented models to a comprehensive one that can be fully applied and evaluated by the health systems policymakers and managers.

In the present study, the framework of EBDM in HSM was developed in the form of four general scopes of inquiring, inspecting, implementing, and integrating including 10 main steps and 47 sub-steps. These scopes were discussed as follows:

In the first step, “situation analysis and priority setting”, the most frequently cited sub-step was identifying and prioritizing the problem. Accordingly, Falzer (2009), emphasized the importance of identifying the decision-making conditions and the relevant institutions and determining their dependencies as the first steps of EBDM [ 44 ]. Aas (2012) has also cited the assessment of individuals and problem status and problem-finding as the first steps of EBDM [ 34 ]. Moreover, the necessity of identifying the existing situation and issues and prioritizing them has been emphasized as the initial steps in most management models such as environmental analysis in strategic planning [ 45 ].

Despite considering the opinions and experience of experts and managers as one of the important sources of evidence for decision-making [ 42 , 46 , 47 , 48 , 49 , 50 ], many studies did not mention this sub-step in the EBDM framework. Hence, the present authors added the acquisition of experts’ opinions as a sub-step of the first step because of its important role in achieving a comprehensive view of the overall situation.

In the second step, “quantifying the issue and developing a statement”, “Developing the conceptual model for the issue” was more addressed [ 37 , 41 , 47 ]. In addition, the authors to complete this step added the fourth sub-step, “Defining the main statement of issue”. This is because that most of the problems in health settings may have a similar value for managers and decision-makers and quantifying them can be used as a criterion for more attention or selecting the problem as the main issue to solve.

The third step, “Capacity building and setting objectives”, was not seen in many other included studies as a main step in EBDM, however, the present authors include this as a main step because without considering the appropriate objectives and preparing necessary capacities and infrastructures, entering to the next steps may become problematic. Moreover, in numerous studies, factors such as knowledge and skills of human resources, training, and the availability of the essential structures and infrastructures have been identified as facilitators of EBDM [ 51 , 52 , 53 , 54 , 55 ]. According to this justification, they are included in the present framework as sub-steps of the third step.

Considering the third step and based on the knowledge extracted from the previous studies, the three sub-steps of “understanding context and Building Culture” [ 56 , 57 ], “gaining the support and commitment of leaders” [ 39 , 57 , 58 ], and “identifying the capabilities required by employees and their skills weaknesses” [ 58 , 59 , 60 ] were the most important sub-steps in this step of EBDM framework. In this regard, Dobrow (2004) has also stated that the two essential components of any EBDM are the evidence and context of its use [ 32 ]. Furthermore, Isfeedvajani (2018) stated that to overcome barriers and persuade hospital managers and committees to apply evidence-based management and decision-making, first and foremost, creating and promoting a culture of "learning through research" was important [ 61 ].

The present findings showed that in the fourth main step, “evidence acquisition and integration”, the most important sub-step was “finding the sources for seeking the evidence” [ 39 , 40 , 41 , 60 , 62 , 63 ]. Concerning the sources for the use of evidence in decision-making in HSM, studies have cited numerous sources, most notably scientific and specialized evidence such as research, articles, academic reports, published texts, books, and clinical guidelines [ 39 , 64 , 65 ]. After scientific evidence, using the opinions and experiences of experts, colleagues, and managers [ 42 , 46 , 49 , 66 ] as well as the use of census and local level data [ 49 , 66 , 67 ], and other sources such as financial [ 67 ], political [ 42 , 49 ] and evaluations [ 49 , 68 ] data were cited.

The fifth step of the present framework, “evidence appraising”, was emphasized by previous literature; for instance, Pierson (2012) pointed to the use of library services in EBDM [ 69 ]. Appraising and selecting the evidence according to appropriate appraisal tools/methods was cited the most. International and local evidence is confirmed that ignoring these criteria can lead to serious faults in the process of decision and policy-making [ 70 , 71 ].

Furthermore, the sixth step, “analysis, synthesis, and interpretation of data”, was mentioned in many included studies [ 36 , 39 , 41 , 42 , 57 , 59 , 72 ]. This step emphasized the role of analysis and synthesis of data in the process of generation applied and useful information. It is obvious that the local interpretation according to different contexts may lead to achieving such kind of knowledge that can be used as a basis for local EBDM in HSM.

Implementing

The third scope consisted of the seventh and eighth steps of the EBDM process in HSM. In the seventh step, “developing evidence-based alternatives”, the issue of involving stakeholders in decision-making and subsequently, planning to design and implementation of the process and evaluation strategies had been focused by the previous studies [ 58 , 60 , 62 , 63 , 73 ]. Studies by Belay (2009) and Armstrong (2014) had also emphasized the need to use stakeholder and public opinion as well as local and demographic data in decision-making [ 49 , 67 ].

“Pilot-implementation of selected alternatives” was the eighth step of the framework. Some key sub-steps of this step were resources allocation [ 58 ], Pre-implementation and pilot change in practice and assessing barriers and enablers for implementation [ 40 ] that indicated the significance of testing the strategies in a pilot stage as a pre- requisition of implementing the whole alternatives. It is obvious that without attention to the pilot stage, adverse and unpleasant outcomes may occur that their correction process imposes many financial, organizational, and human costs on the originations. In addition, a study explained that one of the strategies of the decision-makers to measure the feasibility of the policy options was piloting them, which had a higher chance of being approved by the policymakers. Also, pilot implementation in smaller scales has been recommended in public health in cases of lack of sufficient evidence [ 74 ].

Integrating

This last scope consists of the ninth and tenth steps. The main sub-step of the ninth step, “evaluating alternatives”, was to evaluating process and outcomes and revise. After a successful implementation of the pilot, this step can be assured that the probable outcomes may be achieved and this evaluation will help the decision and policymakers to control the outcomes, effectively. Also, it impacts the whole target program and proposes some correcting plans through an accurate feedback process, too. Pagoto (2007) explained that a facilitator for EBDM would be an efficient and user-friendly system to assess utilization, outcomes, and perceived benefits [ 55 ].

Also, the tenth step, “integrating and maintaining change in practice”, was not considered as a major step in previous models, too, while it is important to maintain and sustain positive changes in organizational performance. In this regard, Ward (2011) also suggested several steps to maintain and sustain the widespread changes in the organization, including increasing the urgency and speed of action, forming a team, getting the right vision, negotiating for buy-in, empowerment, short-term success, not giving up and help to make a change stick [ 35 ]. Finally, the most important sub-steps that could be mentioned in this step were the dissemination of evidence results to decision-makers and the integration of changes made to existing standards and performance guidelines. Liang (2012) had also emphasized the importance of translating existing evidence into useful practices as well as disseminating them [ 47 ]. In addition, the final sub-step, “feedback and feedforward towards the EBDM framework”, was explained by the authors to complete the framework.

Some previous findings showed that about half and two-thirds of organizations do not regularly collect related data about the use of evidence, and they do not systematically evaluate the usefulness or impact of evidence use on interventions and decisions [ 75 ]. The results of a study conducted on healthcare managers at the various levels of an Iranian largest medical university showed that the status of EBDM is not appropriate. This problem was more evident among physicians who have been appointed as managers and who have less managerial and systemic attitudes [ 76 ]. Such studies, by concerning the shortcomings of current models for EBDM in HSM or even lack of a suitable and usable one, have confirmed the necessity of developing a comprehensive framework or model as a practical guide in this field. Consequently, existing and presenting such a framework can help to institutionalize the concept of EBDM in health organizations.

In contrast, results of Lavis study (2008) on organizations that supported the use of research evidence in decision-making reported that more than half of the organizations (especially institutions of health technology assessment agencies) may use the evidence in their process of decision-making [ 75 ], so applying the present framework for these organizations can be recommended, too.

Limitations

One of the limitations of the present study was the lack of access to some studies (especially gray literature) related to the subject in question that we tried to access them by manual searching and asking from some articles’ authors and experts. In addition, most of the existing studies on EBDM were limited to examining and presenting results on influencing, facilitating, or hindering factors or they only mentioned a few components in this area. Consequently, we tried to search for studies from various databases and carefully review and screen them to make sure that we did not lose any relevant data and thematic code. Also, instead of one model, we used four existing models as a basis in the BFF synthesis so that we can finally, by adding additional codes and themes obtained from other studies as well as expert opinions, provide a comprehensive model taking into account all the required steps and details. Also, the framework developed in this study is a complete conceptual model made by BFF synthesis; however, it may need some localization, according to the status and structure of each health system, for applying it.

The present framework provides a comprehensive guideline that can be well adapted for implementing EBDM in health systems and organizations especially in underdeveloped and developing countries where there is usually a lag in updating and applying evidence in their decision-making process. In addition, this framework by providing a complete, well-detailed, sequential and practical process including 10 steps and 56 sub-steps that did not exist in the incomplete related models, can be tested in the organizational decision-making process or managerial tasks by developed countries to improve their EBDM cycle, too.

Availability of data and materials

All data in a form of data extraction tables are available from the corresponding author on a reasonable request.

Abbreviations

• Evidence-based decision-making

Health System Management

Best-Fit Framework

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Acknowledgements

This research, derived from Proposal No. 96-01-07-14184, was conducted by Mrs. Tahereh Shafaghat as part of the activities required for a Ph.D. degree in health care management at the Shiraz University of Medical Sciences. The authors wish to express their sincere gratitude to the research administration of Shiraz University of Medical Sciences for its financial and administrative support and to the English editorial board of Research Editor Institution for improving the native English language of this work.

As the overall study was an approved research project of Shiraz University of Medical Sciences and it was conducted by Mrs. Tahereh Shafaghat as part of the activities required for a Ph.D. degree in the health care management field, the Shiraz University of Medical Sciences supported this study. This study was sponsored by Shiraz University of Medical Sciences under code (96‑01‑07‑14184). The funding body was not involved in the design of the study, data collection, analysis, and interpretation, as well as in writing the manuscript.

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School of Management and Medical Informatics, Health Human Recourses Research Center, Shiraz University of Medical Sciences, Shiraz, Iran

Tahereh Shafaghat, Peivand Bastani & Mohammad Amin Bahrami

Department of Health Care Management, School of Public Health, Health Policy and Management Research Center, Shahid Saoughi University of Medical Sciences, Yazd, Iran

Tahereh Shafaghat & Mohammad Kazem Rahimi Zarchi

Faculty of Health and Behavioral Sciences, School of Dentistry, University of Queensland, QLD, 4072, Brisbane, Australia

Peivand Bastani

Social Determinants of Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran

Mohammad Hasan Imani Nasab

Student Research Committee, School of Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran

Mahsa Roozrokh Arshadi Montazer

Faculty of Medicine, Center for Health Services Research, The University of Queensland, Brisbane, Australia

Sisira Edirippulige

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PB and TSH designed the study and its overall methodology. BP also edited and finalized the article. TSH searched all the databases, with the help of MRAM retrieved the sources, scanned, and screened all the articles in 3 phases. TSH also prepared the draft of the article. MAB and MKRZ contributed to data analysis and synthesis. Also, the study was under consultation and supervision by ZK and MHIN as advisors. All the authors have read and approved the final manuscript.

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Correspondence to Peivand Bastani .

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Since at this study a scoping review was conducted and then the best-fit framework synthesis was used for developing a comprehensive EBDM framework in HSM, there was no human or animal participant in this study. However, the overall research project related to this manuscript was approved by the medical ethics conceal of the research deputy of Shiraz University of Medical Sciences with approval number IR.SUMS.REC.1396–01-07–14184.

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Shafaghat, T., Bastani, P., Nasab, M.H.I. et al. A framework of evidence-based decision-making in health system management: a best-fit framework synthesis. Arch Public Health 80 , 96 (2022). https://doi.org/10.1186/s13690-022-00843-0

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Impact of social problem-solving training on critical thinking and decision making of nursing students

• Soleiman Ahmady 1 &
• Sara Shahbazi   ORCID: orcid.org/0000-0001-8397-6233 2 , 3  

BMC Nursing volume  19 , Article number:  94 ( 2020 ) Cite this article

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The complex health system and challenging patient care environment require experienced nurses, especially those with high cognitive skills such as problem-solving, decision- making and critical thinking. Therefore, this study investigated the impact of social problem-solving training on nursing students’ critical thinking and decision-making.

This study was quasi-experimental research and pre-test and post-test design and performed on 40 undergraduate/four-year students of nursing in Borujen Nursing School/Iran that was randomly divided into 2 groups; experimental ( n  = 20) and control (n = 20). Then, a social problem-solving course was held for the experimental group. A demographic questionnaire, social problem-solving inventory-revised, California critical thinking test, and decision-making questionnaire was used to collect the information. The reliability and validity of all of them were confirmed. Data analysis was performed using SPSS software and independent sampled T-test, paired T-test, square chi, and Pearson correlation coefficient.

The finding indicated that the social problem-solving course positively affected the student’ social problem-solving and decision-making and critical thinking skills after the instructional course in the experimental group ( P  < 0.05), but this result was not observed in the control group ( P  > 0.05).

Conclusions

The results showed that structured social problem-solving training could improve cognitive problem-solving, critical thinking, and decision-making skills. Considering this result, nursing education should be presented using new strategies and creative and different ways from traditional education methods. Cognitive skills training should be integrated in the nursing curriculum. Therefore, training cognitive skills such as problem- solving to nursing students is recommended.

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Continuous monitoring and providing high-quality care to patients is one of the main tasks of nurses. Nurses’ roles are diverse and include care, educational, supportive, and interventional roles when dealing with patients’ clinical problems [ 1 , 2 ].

Providing professional nursing services requires the cognitive skills such as problem-solving, decision-making and critical thinking, and information synthesis [ 3 ].

Problem-solving is an essential skill in nursing. Improving this skill is very important for nurses because it is an intellectual process which requires the reflection and creative thinking [ 4 ].

Problem-solving skill means acquiring knowledge to reach a solution, and a person’s ability to use this knowledge to find a solution requires critical thinking. The promotion of these skills is considered a necessary condition for nurses’ performance in the nursing profession [ 5 , 6 ].

Managing the complexities and challenges of health systems requires competent nurses with high levels of critical thinking skills. A nurse’s critical thinking skills can affect patient safety because it enables nurses to correctly diagnose the patient’s initial problem and take the right action for the right reason [ 4 , 7 , 8 ].

Problem-solving and decision-making are complex and difficult processes for nurses, because they have to care for multiple patients with different problems in complex and unpredictable treatment environments [ 9 , 10 ].

Clinical decision making is an important element of professional nursing care; nurses’ ability to form effective clinical decisions is the most significant issue affecting the care standard. Nurses build 2 kinds of choices associated with the practice: patient care decisions that affect direct patient care and occupational decisions that affect the work context or teams [ 11 , 12 , 13 , 14 , 15 , 16 ].

The utilization of nursing process guarantees the provision of professional and effective care. The nursing process provides nurses with the chance to learn problem-solving skills through teamwork, health management, and patient care. Problem-solving is at the heart of nursing process which is why this skill underlies all nursing practices. Therefore, proper training of this skill in an undergraduate nursing program is essential [ 17 ].

Nursing students face unique problems which are specific to the clinical and therapeutic environment, causing a lot of stresses during clinical education. This stress can affect their problem- solving skills [ 18 , 19 , 20 , 21 ]. They need to promote their problem-solving and critical thinking skills to meet the complex needs of current healthcare settings and should be able to respond to changing circumstances and apply knowledge and skills in different clinical situations [ 22 ]. Institutions should provide this important opportunity for them.

Despite, the results of studies in nursing students show the weakness of their problem-solving skills, while in complex health environments and exposure to emerging diseases, nurses need to diagnose problems and solve them rapidly accurately. The teaching of these skills should begin in college and continue in health care environments [ 5 , 23 , 24 ].

It should not be forgotten that in addition to the problems caused by the patients’ disease, a large proportion of the problems facing nurses are related to the procedures of the natural life of their patients and their families, the majority of nurses with the rest of health team and the various roles defined for nurses [ 25 ].

Therefore, in addition to above- mentioned issues, other ability is required to deal with common problems in the working environment for nurses, the skill is “social problem solving”, because the term social problem-solving includes a method of problem-solving in the “natural context” or the “real world” [ 26 , 27 ]. In reviewing the existing research literature on the competencies and skills required by nursing students, what attracts a lot of attention is the weakness of basic skills and the lack of formal and systematic training of these skills in the nursing curriculum, it indicates a gap in this area [ 5 , 24 , 25 ]. In this regard, the researchers tried to reduce this significant gap by holding a formal problem-solving skills training course, emphasizing the common social issues in the real world of work. Therefore, this study was conducted to investigate the impact of social problem-solving skills training on nursing students’ critical thinking and decision-making.

Setting and sample

This quasi-experimental study with pretest and post-test design was performed on 40 undergraduate/four-year nursing students in Borujen nursing school in Shahrekord University of Medical Sciences. The periods of data collection were 4 months.

According to the fact that senior students of nursing have passed clinical training and internship programs, they have more familiarity with wards and treatment areas, patients and issues in treatment areas and also they have faced the problems which the nurses have with other health team personnel and patients and their families, they have been chosen for this study. Therefore, this study’s sampling method was based on the purpose, and the sample size was equal to the total population. The whole of four-year nursing students participated in this study and the sample size was 40 members. Participants was randomly divided in 2 groups; experimental ( n  = 20) and control (n = 20).

The inclusion criteria to take part in the present research were students’ willingness to take part, studying in the four-year nursing, not having the record of psychological sickness or using the related drugs (all based on their self-utterance).

Intervention

At the beginning of study, all students completed the demographic information’ questionnaire. The study’s intervening variables were controlled between the two groups [such as age, marital status, work experience, training courses, psychological illness, psychiatric medication use and improving cognitive skills courses (critical thinking, problem- solving, and decision making in the last 6 months)]. Both groups were homogeneous in terms of demographic variables ( P  > 0.05). Decision making and critical thinking skills and social problem solving of participants in 2 groups was evaluated before and 1 month after the intervention.

All questionnaires were anonymous and had an identification code which carefully distributed by the researcher.

To control the transfer of information among the students of two groups, the classification list of students for internships, provided by the head of nursing department at the beginning of semester, was used.

Furthermore, the groups with the odd number of experimental group and the groups with the even number formed the control group and thus were less in contact with each other.

The importance of not transferring information among groups was fully described to the experimental group. They were asked not to provide any information about the course to the students of the control group.

Then, training a course of social problem-solving skills for the experimental group, given in a separate course and the period from the nursing curriculum and was held in 8 sessions during 2 months, using small group discussion, brainstorming, case-based discussion, and reaching the solution in small 4 member groups, taking results of the social problem-solving model as mentioned by D-zurilla and gold fried [ 26 ]. The instructor was an assistant professor of university and had a history of teaching problem-solving courses. This model’ stages are explained in Table  1 .

All training sessions were performed due to the model, and one step of the model was implemented in each session. In each session, the teacher stated the educational objectives and asked the students to share their experiences in dealing to various workplace problems, home and community due to the topic of session. Besides, in each session, a case-based scenario was presented and thoroughly analyzed, and students discussed it.

Instruments

In this study, the data were collected using demographic variables questionnaire and social problem- solving inventory – revised (SPSI-R) developed by D’zurilla and Nezu (2002) [ 26 ], California critical thinking skills test- form B (CCTST; 1994) [ 27 , 28 ] and decision-making questionnaire.

SPSI-R is a self - reporting tool with 52 questions ranging from a Likert scale (1: Absolutely not – 5: very much).

The minimum score maybe 25 and at a maximum of 125, therefore:

The score 25 and 50: weak social problem-solving skills.

The score 50–75: moderate social problem-solving skills.

The score higher of 75: strong social problem-solving skills.

The reliability assessed by repeated tests is between 0.68 and 0.91, and its alpha coefficient between 0.69 and 0.95 was reported [ 26 ]. The structural validity of questionnaire has also been confirmed. All validity analyses have confirmed SPSI as a social problem - solving scale.

In Iran, the alpha coefficient of 0.85 is measured for five factors, and the retest reliability coefficient was obtained 0.88. All of the narratives analyzes confirmed SPSI as a social problem- solving scale [ 29 ].

California critical thinking skills test- form B(CCTST; 1994): This test is a standard tool for assessing the basic skills of critical thinking at the high school and higher education levels (Facione & Facione, 1992, 1998) [ 27 ].

This tool has 34 multiple-choice questions which assessed analysis, inference, and argument evaluation. Facione and Facione (1993) reported that a KR-20 range of 0.65 to 0.75 for this tool is acceptable [ 27 ].

In Iran, the KR-20 for the total scale was 0.62. This coefficient is acceptable for questionnaires that measure the level of thinking ability of individuals.

After changing the English names of this questionnaire to Persian, its content validity was approved by the Board of Experts.

The subscale analysis of Persian version of CCTST showed a positive high level of correlation between total test score and the components (analysis, r = 0.61; evaluation, r = 0.71; inference, r = 0.88; inductive reasoning, r = 0.73; and deductive reasoning, r = 0.74) [ 28 ].

A decision-making questionnaire with 20 questions was used to measure decision-making skills. This questionnaire was made by a researcher and was prepared under the supervision of a professor with psychometric expertise. Five professors confirmed the face and content validity of this questionnaire. The reliability was obtained at 0.87 which confirmed for 30 students using the test-retest method at a time interval of 2 weeks. Each question had four levels and a score from 0.25 to 1. The minimum score of this questionnaire was 5, and the maximum score was 20 [ 30 ].

Statistical analysis

For analyzing the applied data, the SPSS Version 16, and descriptive statistics tests, independent sample T-test, paired T-test, Pearson correlation coefficient, and square chi were used. The significant level was taken P  < 0.05.

The average age of students was 21.7 ± 1.34, and the academic average total score was 16.32 ± 2.83. Other demographic characteristics are presented in Table  2 .

None of the students had a history of psychiatric illness or psychiatric drug use. Findings obtained from the chi-square test showed that there is not any significant difference between the two groups statistically in terms of demographic variables.

The mean scores in social decision making, critical thinking, and decision-making in whole samples before intervention showed no significant difference between the two groups statistically ( P  > 0.05), but showed a significant difference after the intervention ( P  < 0.05) (Table  3 ).

Scores in Table  4 showed a significant positive difference before and after intervention in the “experimental” group ( P  < 0.05), but this difference was not seen in the control group ( P  > 0.05).

Among the demographic variables, only a positive relationship was seen between marital status and decision-making skills (r = 0.72, P  < 0.05).

Also, the scores of critical thinking skill’ subgroups and social problem solving’ subgroups are presented in Tables  5 and 6 which showed a significant positive difference before and after intervention in the “experimental” group (P < 0.05), but this difference was not seen in the control group ( P  > 0.05).

In the present study conducted by some studies, problem-solving and critical thinking and decision-making scores of nursing students are moderate [ 5 , 24 , 31 ].

The results showed that problem-solving skills, critical thinking, and decision-making in nursing students were promoted through a social problem-solving training course. Unfortunately, no study has examined the effect of teaching social problem-solving skills on nursing students’ critical thinking and decision-making skills.

Altun (2018) believes that if the values of truth and human dignity are promoted in students, it will help them acquire problem-solving skills. Free discussion between students and faculty on value topics can lead to the development of students’ information processing in values. Developing self-awareness increases students’ impartiality and problem-solving ability [ 5 ]. The results of this study are consistent to the results of present study.

Erozkan (2017), in his study, reported there is a significant relationship between social problem solving and social self-efficacy and the sub-dimensions of social problem solving [ 32 ]. In the present study, social problem -solving skills training has improved problem -solving skills and its subdivisions.

The results of study by Moshirabadi (2015) showed that the mean score of total problem-solving skills was 89.52 ± 21.58 and this average was lower in fourth-year students than other students. He explained that education should improve students’ problem-solving skills. Because nursing students with advanced problem-solving skills are vital to today’s evolving society [ 22 ]. In the present study, the results showed students’ weakness in the skills in question, and holding a social problem-solving skills training course could increase the level of these skills.

Çinar (2010) reported midwives and nurses are expected to use problem-solving strategies and effective decision-making in their work, using rich basic knowledge.

These skills should be developed throughout one’s profession. The results of this study showed that academic education could increase problem-solving skills of nursing and midwifery students, and final year students have higher skill levels [ 23 ].

Bayani (2012) reported that the ability to solve social problems has a determining role in mental health. Problem-solving training can lead to a level upgrade of mental health and quality of life [ 33 ]; These results agree with the results obtained in our study.

Conducted by this study, Kocoglu (2016) reported nurses’ understanding of their problem-solving skills is moderate. Receiving advice and support from qualified nursing managers and educators can enhance this skill and positively impact their behavior [ 31 ].

Kashaninia (2015), in her study, reported teaching critical thinking skills can promote critical thinking and the application of rational decision-making styles by nurses.

One of the main components of sound performance in nursing is nurses’ ability to process information and make good decisions; these abilities themselves require critical thinking. Therefore, universities should envisage educational and supportive programs emphasizing critical thinking to cultivate their students’ professional competencies, decision-making, problem-solving, and self-efficacy [ 34 ].

The study results of Kirmizi (2015) also showed a moderate positive relationship between critical thinking and problem-solving skills [ 35 ].

Hong (2015) reported that using continuing PBL training promotes reflection and critical thinking in clinical nurses. Applying brainstorming in PBL increases the motivation to participate collaboratively and encourages teamwork. Learners become familiar with different perspectives on patients’ problems and gain a more comprehensive understanding. Achieving these competencies is the basis of clinical decision-making in nursing. The dynamic and ongoing involvement of clinical staff can bridge the gap between theory and practice [ 36 ].

Ancel (2016) emphasizes that structured and managed problem-solving training can increase students’ confidence in applying problem-solving skills and help them achieve self-confidence. He reported that nursing students want to be taught in more innovative ways than traditional teaching methods which cognitive skills training should be included in their curriculum. To this end, university faculties and lecturers should believe in the importance of strategies used in teaching and the richness of educational content offered to students [ 17 ].

The results of these recent studies are adjusted with the finding of recent research and emphasize the importance of structured teaching cognitive skills to nurses and nursing students.

Based on the results of this study on improving critical thinking and decision-making skills in the intervention group, researchers guess the reasons to achieve the results of study in the following cases:

In nursing internationally, problem-solving skills (PS) have been introduced as a key strategy for better patient care [ 17 ]. Problem-solving can be defined as a self-oriented cognitive-behavioral process used to identify or discover effective solutions to a special problem in everyday life. In particular, the application of this cognitive-behavioral methodology identifies a wide range of possible effective solutions to a particular problem and enhancement the likelihood of selecting the most effective solution from among the various options [ 27 ].

In social problem-solving theory, there is a difference among the concepts of problem-solving and solution implementation, because the concepts of these two processes are different, and in practice, they require different skills.

In the problem-solving process, we seek to find solutions to specific problems, while in the implementation of solution, the process of implementing those solutions in the real problematic situation is considered [ 25 , 26 ].

The use of D’zurilla and Goldfride’s social problem-solving model was effective in achieving the study results because of its theoretical foundations and the usage of the principles of cognitive reinforcement skills. Social problem solving is considered an intellectual, logical, effort-based, and deliberate activity [ 26 , 32 ]; therefore, using this model can also affect other skills that need recognition.

In this study, problem-solving training from case studies and group discussion methods, brainstorming, and activity in small groups, was used.

There are significant educational achievements in using small- group learning strategies. The limited number of learners in each group increases the interaction between learners, instructors, and content. In this way, the teacher will be able to predict activities and apply techniques that will lead students to achieve high cognitive taxonomy levels. That is, confront students with assignments and activities that force them to use cognitive processes such as analysis, reasoning, evaluation, and criticism.

In small groups, students are given the opportunity to the enquiry, discuss differences of opinion, and come up with solutions. This method creates a comprehensive understanding of the subject for the student [ 36 ].

According to the results, social problem solving increases the nurses’ decision-making ability and critical thinking regarding identifying the patient’s needs and choosing the best nursing procedures. According to what was discussed, the implementation of this intervention in larger groups and in different levels of education by teaching other cognitive skills and examining their impact on other cognitive skills of nursing students, in the future, is recommended.

Social problem- solving training by affecting critical thinking skills and decision-making of nursing students increases patient safety. It improves the quality of care because patients’ needs are better identified and analyzed, and the best solutions are adopted to solve the problem.

In the end, the implementation of this intervention in larger groups in different levels of education by teaching other cognitive skills and examining their impact on other cognitive skills of nursing students in the future is recommended.

Study limitations

This study was performed on fourth-year nursing students, but the students of other levels should be studied during a cohort from the beginning to the end of course to monitor the cognitive skills improvement.

The promotion of high-level cognitive skills is one of the main goals of higher education. It is very necessary to adopt appropriate approaches to improve the level of thinking. According to this study results, the teachers and planners are expected to use effective approaches and models such as D’zurilla and Goldfride social problem solving to improve problem-solving, critical thinking, and decision-making skills. What has been confirmed in this study is that the routine training in the control group should, as it should, has not been able to improve the students’ critical thinking skills, and the traditional educational system needs to be transformed and reviewed to achieve this goal.

Availability of data and materials

The datasets used and analyzed during the present study are available from the corresponding author on reasonable request.

Abbreviations

California critical thinking skills test

Social problem-solving inventory – revised

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Acknowledgments

This article results from research project No. 980 approved by the Research and Technology Department of Shahrekord University of Medical Sciences. We would like to appreciate to all personnel and students of the Borujen Nursing School. The efforts of all those who assisted us throughout this research.

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Soleiman Ahmady

Virtual School of Medical Education and management, Shahid Beheshty University of Medical Sciences, Tehran, Iran

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Community-Oriented Nursing Midwifery Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran

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Contributions

SA and SSH conceptualized the study, developed the proposal, coordinated the project, completed initial data entry and analysis, and wrote the report. SSH conducted the statistical analyses. SA and SSH assisted in writing and editing the final report. All authors read and approved the final manuscript.

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Correspondence to Sara Shahbazi .

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This study was reviewed and given exempt status by the Institutional Review Board of the research and technology department of Shahrekord University of Medical Sciences (IRB No. 08–2017-109). Before the survey, students completed a research consent form and were assured that their information would remain confidential. After the end of the study, a training course for the control group students was held.

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Ahmady, S., Shahbazi, S. Impact of social problem-solving training on critical thinking and decision making of nursing students. BMC Nurs 19 , 94 (2020). https://doi.org/10.1186/s12912-020-00487-x

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9 Problem-Solving and Decision-Making Skills for Public Health Practice

• Published: October 2023
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This chapter provides an initial definition of problem-solving and the components of the problem-solving process. It identifies common mistakes early in the process and their implications. It explains that the first step toward successful problem-solving is thoroughly and accurately defining the problem and acknowledging that multiple solutions must be considered. It explores multiple approaches to problem-solving, such as rational problem-solving and organic problem-solving, as well as a type of organic problem-solving called appreciative inquiry. The chapter also explores seven decision-making styles and elaborates on common mistakes made during the process, as well as how to overcome them.

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Critical Thinking and Decision-Making Skills

Chapter 4 Critical Thinking and Decision-Making Skills Betsy Frank http://evolve.elsevier.com/Huber/leadership/ In an era of changing reimbursements, value based purchasing, and expanded roles for nursing in the health care delivery system, critical thinking and decision making are important skills for nurses caring for patients and for nurse leaders and managers. Both the American Nurses Association’s (2009) and American Association of Nurse Executives’ (2005) standards for practice for nurse administrators and executives support the fact that in a fast-paced health care delivery environment, staff nurses, leaders, and managers must be able to analyze and synthesize a large array of information, use critical thinking and decision making skills to deliver effective day to day patient care, and solve complex problems that occur in complex health care delivery systems (see Figure 4-1 ). Furthermore, the Magnet Hospital initiative and the Institute of Medicine’s ( Committee on the Robert Wood Johnson Foundation, 2011 ) Future of Nursing report highlight the need for nurses to be able to be fully involved and even take the lead in decision making from the unit level to the larger health care delivery system. FIGURE 4-1 Differences and interactions among critical thinking, problem solving, and decision making. Nurses are a cadre of knowledge workers within the health care system. As such, they need information, resources, and support from their environment. In fact, the nurse manager’s expertise in critical thinking and shared decision making are essential for creating healthy work environments where quality and effective care can be delivered ( Kramer et al., 2010 ; Zori et al., 2010 ). Critical thinking and decision-making competences include analytical skills as well as intuition. Just as intuition is part of expert clinical practice ( Benner, 1984 ), intuition plays an important role in developing managerial and leadership expertise (Shirey, 2007). DEFINITIONS Critical thinking can be defined as a set of cognitive skills including “interpretation, analysis, evaluation, inference, explanation, and self-regulation” ( Facione, 2007 , p. 1). Using these skills, nurses in direct patient care and leaders and managers can reflect analytically, reconceptualize events, and avoid the tendency to make decisions and problem solve hastily or on the basis of inadequate information. Facione also pointed out that critical thinking is not only a skill but also a disposition that is grounded in a strong ethical component. Critical thinking in nursing can be defined as “purposeful, informed, outcomes focused thinking…[that] applies logic, intuition, creativity and is grounded in specific knowledge, skills, and experience” ( Alfaro-LeFevre, 2009 , p. 7). Alfaro-LeFevre noted that outcomes-focused thinking helps to prevent, control, and solve problems. Tanner (2000) noted that critical thinking is much more than just the five steps of the nursing process. Problem solving involves moving from an undesirable to a desirable state ( Chambers, 2009 ). Problem solving occurs in a variety of nursing contexts, including direct client care, team-level leadership, and systems-level leadership. Nurses and nurse managers are challenged to move from step-by-step problem-solving techniques to incorporating creative thinking, which involves considering the context when meeting current and future challenges in health care delivery ( Chambers, 2009 ; Rubenfeld & Scheffer, 2006 ). Decision making is the process of making choices that will provide maximum benefit ( Drummond, 2001 ). Decision making can also be defined as a behavior exhibited in selecting and implementing a course of action from alternative courses of action for dealing with a situation or problem. It may or may not be the result of an immediate problem. Critical thinking and effective decision making are the foundation of effective problem solving. If problems require urgent action, then decisions must be made rapidly; if solutions do not need to be identified immediately, decision making can occur in a more deliberative way. Because problems change over time, decisions made at one point in time may need to be changed ( Choo, 2006 ). For example, decisions about how to staff a unit when a nurse calls in sick have to be made immediately. However, if a unit is chronically short-staffed, a decision regarding long-term solutions will have to be made. The process of selecting one course of action from alternatives forms the basic core of the definition of decision making. Choo (2006) noted that all decisions are bounded by cognitive and mental limits, how much information is processed, and values and assumptions. In other words, no matter the decision-making process, all decisions are limited by a variety of known and unknown factors. In a chaotic health care delivery environment, where regulations and standards of care are always changing, any decision may cause an unanticipated future problem. BACKGROUND Critical Thinking Critical thinking is both an attitude toward handling issues and a reasoning process. Critical thinking is not synonymous with problem solving and decision making ( Figure 4-1 ), but it is the foundation for effective decision making that helps to solve problems ( Fioratou et al., 2011 ). Figure 4-2 illustrates the way obstacles such as poor judgment or biased thinking create detours to good judgment and effective decision making. Critical thinking helps overcome these obstacles. Critical thinking skills may not come naturally. The nurse who is a critical thinker has to be open-minded and have the ability to reflect on present and past actions and to analyze complex information. Nurses who are critical thinkers also have a keen awareness of their surroundings ( Fioratou et al., 2011 ). FIGURE 4-2 Decision-making maze. Critical thinking is a skill that is developed for clarity of thought and improvement in decision-making effectiveness. The roots of the concept of critical thinking can be traced to Socrates, who developed a method of questioning as a way of thinking more clearly and with greater logical consistency. He demonstrated that people often cannot rationally justify confident claims to knowledge. Confused meanings, inadequate evidence, or self-contradictory beliefs may lie below the surface of rhetoric. Therefore it is important to ask deep questions and probe into thinking sequences, seek evidence, closely examine reasoning and assumptions, analyze basic concepts, and trace out implications. Other thinkers, such as Plato, Aristotle, Thomas Aquinas, Francis Bacon, and Descartes, emphasized the importance of systematic critical thinking and the need for a systematic disciplining of the mind to guide it in clarity and precision of thinking. In the early 1900s, Dewey equated critical thinking with reflective thought ( The Critical Thinking Community, 2008 ). Critical thinking, then, is characterized by thinking that has a purpose, is systematic, considers alternative viewpoints, occurs within a frame of reference, and is grounded in information ( The Critical Thinking Community, 2008 ). Questioning is implicit in the critical thinking process. The following are some of the questions to be asked when thinking critically about a problem or issue ( Elder & Paul, n.d. ): •  What is the question being asked? •  Is this the right question? •  Is there another question that must be answered first? •  What information is needed? •  Given the information, what conclusions are justified? •  Are there alternative viewpoints? No matter what questions are asked, critical thinkers need to know the “why” of the thinking, the mode of reasoning (inductive or deductive), what the source and accuracy of the information is, what the underlying assumptions and concepts are, and what might be the outcome of the thinking ( The Critical Thinking Community, 2008 ). Critical Thinking in Nursing Nurses in clinical practice continually make judgments and decisions based on the assessment and diagnosis of client needs and practice problems or situations. Clinical judgment is a complex skill grounded in critical thinking. Clinical judgment results in nursing actions directed toward achieving health outcomes ( Alfaro-LeFevre, 2009 ). Scheffer and Rubenfeld (2000) have stated that habits of the mind that are characteristic of critical thinking by nurses include confidence, contextual perspective, creativity, flexibility, inquisitiveness, intellectual integrity, open-mindedness, perseverance, and reflection. Emphasizing the value of expert experience and holistic judgment ability, Benner (2003) cautioned that clinical judgments must not rely too heavily on technology and that the economic incentives to use technology must not come at the expense of human critical thinking and reasoning in individual cases. Critical thinkers have been distinguished from traditional thinkers in nursing. A traditional thinker, thought to be the norm in nursing, preserves status quo. Critical thinkers go beyond the step-by-step processes outlined in the nursing process and traditional problem solving. A critical thinker challenges and questions the norm and considers in the context of decision making potential unintended consequences. Unlike traditional thinkers, critical thinkers are creative in their thinking and anticipate the consequences of their thinking ( Rubenfeld & Scheffer, 2006 ). Creativity is necessary to deal with the complex twenty-first century health care delivery environment. Nurse leaders and managers have an obligation to create care delivery climates that promote critical thinking, which leads to innovative solutions to problems within the system of care ( Committee on the Robert Wood Johnson Foundation Initiative on the Future of Nursing, at the Institute of Medicine; Institute of Medicine, 2011 ; Porter-O’Grady, 2011 ). Such a climate encourages deep reflection, especially so that nurses feel safe to learn from mistakes, and encourages nurses to ask questions and consider a variety of viewpoints and alternative solutions to problems. What specific strategies can be used to promote a climate in which critical thinking is fostered? First and foremost, the nurse manager/leader, in the role of mentor, coach, or preceptor, should encourage questions such as “Is what you are doing or proposing based on sound evidence?” ( Ignatavicius, 2008 ). However, Snowden and Boone (2007) cautioned that “best practice, by definition is past practice” (p. 71). Therefore use of best practices needs to be examined carefully in order to use them appropriately. Staff nurses and managers must use critical thinking skills in order to determine the appropriateness of implementing recommended practice protocols. As managers, allowing staff and self “think time” is essential for reflection and is a key component of critical thinking ( Zori & Morrison, 2009 ). Nurse managers’ critical thinking abilities promotes a positive practice environment which can lead to better patient outcomes ( Zori, Nosek, & Musil, 2010 ). Coaching new and experienced nurses to develop expertise in clinical judgment is critically important. Many new nurses, in particular, need to further develop their critical thinking skills ( Fero et al., 2008 ; Forneris & Peden-McAlpine, 2009 ). In addition to having preceptors and others ask questions of new nurses, nurse managers and leaders can use other strategies to enhance critical thinking in nursing staff. Developing concept maps is another useful strategy to promote critical thinking. Although typically used in prelicensure programs ( Ellermann et al., 2006 ), nurse managers can encourage their preceptors to use concept maps with orientees ( Toofany, 2008 ). Developing concept maps in concert with others further develops a nurse’s critical thinking through the process of dialogue. Simulations also promote critical thinking or “thinking like a nurse” ( Tanner, 2006 ). According to Tanner, simulations can promote clinical reasoning, which leads to making conclusions in the form of clinical judgments and, thus, effective problem solving. The use of human patient simulators is well known in educational settings. Simulators may also be useful in orienting new graduates to the acute care setting ( Leigh, 2011 ). Pulman and colleagues (2009) have reported on the use of simulators to promote critical thinking role development in inter-professional environments. Decision Making Decision making is the essence of leadership and management. It is what leaders and managers are expected to do ( Keynes, 2008 ). Thus decisions are visible outcomes of the leadership and management process. The effectiveness of decision making is one criterion for evaluating a leader or manager. Yet staff nurses and nurse managers and leaders must make decisions in uncertain and complex environments ( Clancy & Delaney, 2005 ). Within a climate of uncertainty and complexity, nurse managers and leaders must also understand that all decision making involves high-stakes risk taking ( Clancy & Delaney, 2005 ; Keynes, 2008 ). If poor decisions are made, progress can be impeded, resources wasted, harm caused, and a career adversely affected. The results of poor decisions may be subtle and not appear until years later. Take, for instance, a decision to reduce expenses by decreasing the ratio of registered nurses to nurses’ aides. There may be a short-term cost savings, but if not implemented appropriately, this tactic may result in the gradual erosion of patient care over time (Kane et al., 2007). Unintended effects may include higher turnover of experienced nurses, increased adverse events such as medication errors, decreased staff morale, and lower patient satisfaction scores. The long-term outcome of this decision may actually result in increased expenses not reduced expenses. Thus it is vital for nurses to understand decision making and explore styles and strategies to enhance decision-making skills. Decision making, like traditional problem solving, has been traditionally thought of as a process with identifiable steps yet influenced by the context and by whether there is an intuitive grasp of the situation. However, Effken and colleagues (2010) stated that decision making is much more. Expert decision making is a constructive process in which the outcomes are not preplanned or simply pulled out of a memory bank. Instead, expert decision-making activities are creative, innovative, and adapted to uncertainty and the context of the current problem, using learning from prior experience (p. 189). Nurses make decisions in personal, clinical, and organizational situations and under conditions of certainty, uncertainty, and risk. Various decision-making models and strategies exist. Nurses’ control over decision making may vary as to amount of control and where in the process they can influence decisions. Although decision-making is more than a step-by-step process as noted by Effken and colleagues (2010) , awareness of the components, process, and strategies of decision making contributes to effectiveness in nursing leadership and management decision making. The basic elements of decision making, which enhances day to day activities, contributes to strategic planning and solves problems can be summarized into the following two parts: (1) identifying the goal for decision-making, and (2) making the decision. According to Guo (2008, p. 120) , the steps of the decision-making process can be illustrated as follows, using DECIDE: •  D efine the problem and determine why anything should be done about it and explore what could be happening. •  E stablish desirable criteria for what you want to accomplish. What should stay the same and what can be done to avoid future problems? •  C onsider all possible alternative choices that will accomplish the desired goal or criteria for problem solution. •  I dentify the best choice or alternative based on experience, intuition, experimentation. •  D evelop and implement an action plan for problem solution. •  E valuate decision through monitoring, troubleshooting, and feedback. Notice how these steps are analogous to the traditional problem-solving process or nursing process well-known by nurses and nurse managers. Thus decision making is used to solve problems. However, decision making is more than just problem solving. Decision making may also be the result of opportunities, challenges, or more long-term leadership initiatives as opposed to being triggered by an immediate problem. In any case, the processes are virtually the same, but their purposes may be slightly different. Nurse managers use decision making in managing resources and the environment of care delivery. Decision making involves an evaluation of the effectiveness of the outcomes that result from the decision-making process itself. Whether nurse managers are the sole decision makers or facilitate group decision making, all the factors that influence the problem-solving process also impact how decisions are made: who owns the problem that will result in a decision, what is the context of the decision to be made, and what lenses or perspectives influence the decision to be made? For example, the chief executive officer may frame issues as a competitive struggle not unlike a sports event. The marketing staff may interpret problems as military battles that need to be won. Nurse executives may view concerns from a care or family frame that emphasizes collaboration and working together. Learning and understanding which analogies and perspectives offer the best view of a problem or issue are vital to effective decision making. It may be necessary for nurse managers to expand their frame of reference and be willing to consider even the most outlandish ideas. Obviously, it is important to begin the goal definition phase with staff members who are closest to the issue. That includes staff nurses in concert with their managers. Often, decisions can originate within the confines of the shared governance system that may be in place within an organization ( Dunbar et al., 2007 ). It is wise, also, to consider adding individuals who have no connection with the issue whatsoever. Often it is these “unconnected” staff members who bring new decision frames to the meeting and have the most unbiased view of the problem. One of the core competencies for all health professionals is working in interprofessional teams ( Interprofessional Education Collaborative Expert Panel, 2011 ). Therefore using interprofessional teams for problem solving and decision making can be assumed to be more effective than working in disciplinary silos. No matter who is involved in the decision-making process, the basic steps to arrive at a decision to resolve problems remain the same. One critical aspect to note, however, is that in making decisions, nurse managers must have situational awareness ( Sharma & Ivancevic, 2010 ). That is, decision makers must always consider the context in which the outcome of the decision is to occur. A decision that leads to a desired outcome on one patient care unit may lead to undesirable outcomes on another unit because the patient care environment and personnel are different. DECISION OUTCOMES When looking at outcomes, one critical aspect of decision making is to determine the desired outcome. The desired outcome may vary, according to Guo (2008) , from an ideal or short-term resolution to covering up a situation. What is desired may be (1) for a problem to go away forever, (2) to make sure that all involved in this problem are satisfied with the solution and gain some benefit from it, or (3) to obtain an ideal solution. Sometimes a quick decision is desired, and researching different aspects of the problem or allowing for participation in decision making is not appropriate. For example, in disaster management, the nurse leader will use predetermined procedures for determining roles of the various personnel involved (Coyle et al., 2007). Desired decisions can be categorized into two end points: minimal and optimal. A minimal decision results in an outcome that is sufficient, satisfies basic requirements, and minimally meets desired objectives. This is sometimes called a “satisficing” decision . An optimizing decision includes comparing all possible solutions with desired objectives and then selecting the optimal solution that best meets objectives ( Choo, 2006 ; Guo, 2008 ). In addition to these two strategies, Layman (2011) drawing from Etzioni (1986) , discussed two other strategies: mixed scanning and incrementalism. Incrementalism is slow progress toward an optimal course of action. Mixed scanning combines the stringent rationalism of optimizing with the “muddling through” approach of incrementalism to form substrategies. Optimizing has the goal of selecting the course of action with the highest payoff (maximization). Limitations of time, money, or people may prevent the decision maker from selecting the more deliberative and slower process of optimizing. Still, the decision maker needs to focus on techniques that will enhance effectiveness in decision-making situations. Barriers to effective decision making exist and, once identified, can lead to going back through the decision-making process. Flaws in thinking can create hidden traps in decision making. These are common psychological tendencies that create barriers or biases in cognitive reflection and appraisal. Six common distortions are as follows ( Hammond et al., 1998 ; 2006 ): 1.  Anchoring trap: When a decision is being considered, the mind gives a disproportionate weight to the first information it receives. Past events, trends, and numbers outweigh current and future realities. All individuals have preconceived notions and biases that influence decisions in a variety of ways. For instance the Institute of Medicine (IOM, 2001) endorsed the use of c omputerized p hysician o rder e ntry (CPOE) as one solution to reduce medication errors. Furthermore, The Centers for Medicare and Medicaid Services has set forth meaningful use criteria for implementation of CPOE as well as electronic health records (EHR). Despite incentive payments for implementing EHR ( HFMA P & P Board, 2012 ), the financial costs involved, human-factor errors and work-flow issues can hamper successful implementation ( Campbell et al., 2006 ). 2.  Status-quo trap: Decision makers display a strong bias toward alternatives that perpetuate the status quo. In the face or rapid change in the environment, past practices that exhibit any sense of permanence provide managers with a feeling of security. 3.  Sunk-cost trap: Past decisions become sunk costs, and new choices are often made in a way that justifies past choices. This may result in becoming trapped by an escalation of commitment. Because of rapid, ongoing advances in medical technology, managers are frequently pressured to replace existing equipment before it is fully depreciated. If the new equipment provides a higher level of quality at a lower cost, the sunk cost of the existing equipment is irrelevant to the decision-making process. However, managers may delay purchasing new equipment and forgo subsequent savings because the equipment has yet to reach the end of its useful life. 4.  Confirming-evidence trap: Kahneman and colleagues (2011) noted that decision makers also fall into the trap of confirmation bias where contradictory data are ignored. This bias leads people to seek out information that supports an existing instinct or point of view while avoiding contradictory evidence. A typical example is favoring new technology over less glamorous alternatives. A decision maker may become so enamored by technological solutions (and slick vendor demonstrations) that he or she may unconsciously decide in favor of these systems even though strong evidence supports implementing less costly solutions first. 5.  Framing trap: The way a problem is initially framed profoundly influences the choices made. Different framing of the same problem can lead to different decision responses. A decision frame can be viewed as a window into the varied reasons a problem exists. As implied by the word frame , individuals may perceive problems only within the boundaries of their own frame. The human resources director may perceive a staffing shortage as a compensation problem, the chief financial officer as an insurance reimbursement issue, the director of education as a training issue, and the chief nursing officer as a work environment problem. Obviously all these issues may contribute, in part, to the problem; however, each person, in looking through his or her individual frame, sees only that portion with which he or she is most familiar ( Layman, 2011 ). 6.  Estimating and forecasting traps: People make estimates or forecasts about uncertain events, but their minds are not calibrated for making estimates in the face of uncertainty. The notion that experience is the parent of wisdom suggests that mature managers, over the course of their careers, learn from their mistakes. It is reasonable to assume that the knowledge gained from a manager’s failed projects would be applied to future decisions. Whether right or wrong, humans tend to take credit for successful projects and find ways to blame external factors on failed ones. Unfortunately, this form of overconfidence often results in overly optimistic projections in project planning. This optimism is usually buried in the analysis done before ranking alternatives and recommendations. Conversely, excessive cautiousness or prudence may also result in faulty decisions. This is called aversion bias ( Kahneman et al., 2011 ). Dramatic events may overly influence decisions because of recall and memory, exaggerating the probability of rare but catastrophic occurrences. It is important that managers objectively examine project planning assumptions in the decision-making process to ensure accurate projections. Because misperceptions, biases, and flaws in thinking can influence choices, actions related to awareness, testing, and mental discipline can be employed to ferret out errors in thinking before the stage of decision making ( Hammond et al., 1998 ). Data-driven decision making is important ( Dexter et al., 2011 ; Lamont, 2010 ; Mick, 2011 ). The electronic health record can be mined for valuable data, upon which fiscal, human resource, and patient care decisions can be made. However, the data derived can be overwhelming and cause decision makers to make less than optimal decisions. Shared decision making can help ameliorate decision traps ( Kahneman et al., 2011 ) because dissent within the group may help those accountable for the decision to prevent errors that are “motivated by self-interest” (p. 54). More alternatives can be generated by a group and more data can be gathered upon which to base the decision, rather than just using data that is more readily apparent. DECISION-MAKING SITUATIONS The situations in which decisions are made may be personal, clinical, or organizational ( Figure 4-3 ). Personal decision making is a familiar part of everyday life. Personal decisions range from multiple small daily choices to time management and career or life choices. FIGURE 4-3 Decision-making situations. Clinical decision making in nursing relates to quality of care and competency issues. According to Tanner (2006) , decision making in the clinical arena is called clinical judgment . In nursing, as with all health professions, clinical judgments should be patient-centered, use available evidence from research and other sources, and use available informatics tools (IOM, 2003). These crucial judgments should take place within the context of interprofessional collaboration. Within a hospital or other health care agency, a social network forms that is interprofessional ( Tan et al., 2005 ). This social network has to collaborate for positive change within the organization and to make clinical decisions of the highest quality. Nurses manage care and make decisions under conditions of certainty, uncertainty, and risk. For example, if research has shown that, under prescribed conditions, the selection of a specific nursing intervention is highly likely to produce a certain outcome, then the nurse in that situation faces a condition of relative certainty. An example would be the prevention of decubitus ulcers by frequent repositioning. If little knowledge is available or if the specific situation is more complex or variant from the usual, then the nurse faces uncertainty. Risk situations occur when a threat of harm to patients exists. Conditions of risk occur commonly relative to the administration of medications, crisis events, infection control, invasive procedures, and the use of technology in nursing practice. Furthermore, these conditions also apply to the administration of nursing care delivery, in which decision making is a critical function. Conditions of uncertainty and complexity are common in nursing care management. Over time, the complexity of health care processes has increased as a natural outgrowth of innovation and new technology. With computerized integration of billing, physician ordering, results of diagnostic tests, information about medications and their actions and side effects, and critical pathways and computerized charting, complexity increases more. Trying to integrate so many data points in care delivery can overwhelm the care provider who is making clinical judgments. As a result, subtle failures in any part of the information system can go unnoticed and have catastrophic outcomes. For example, if the computer system in the emergency room cannot “talk” to the system in the operating room, then errors in care management, such as giving cephalexin to patient who has an allergy can occur. If a provider fails to input critical information, such as a medication that a patient is taking, a fatal drug interaction could occur when another provider prescribes a new medication. Ready access to the Internet and online library sources can further create complexity in the decision-making process as care providers have access to more information upon which to make decisions. Readily accessible information related to evidence-based practice and information gleaned from human resources records and clinical systems can overwhelm nurse managers and leaders. Nurse leaders are coming to understand that innovation and new technology are the driving forces behind the discovery of new knowledge and improvements in patient care. Overlapping, unclear, and changing roles for nurses as a result of new technology and services create complex decision-making situations and impact the quality of care delivered (IOM, 2003). In addition, workflow interruptions can inhibit critical thinking, particularly in a chaotic environment ( Cornell et al., 2011 ; Sitterding et al., 2012 ). ADMINISTRATIVE AND ORGANIZATIONAL DECISION MAKING According to Choo (2006) , organizations use information to “make decisions that commit resources and capabilities to purposeful action” (p. 1). Nurse managers, for example, make staffing decisions and thus commit financial resources for the purpose of delivering patient care. Hospital administrators may decide to add additional services to keep up with external forces. These decisions subsequently have financial implications related to reimbursement, staffing, and the like. Etzioni (1989) noted that the traditional model for business decisions was rationalism. However, he further asserted that as information flow became more complex and faster-paced, a new decision-making model based on the use of partial information that has not been fully analyzed had begun to evolve. He called this model “humble decision making.” This approach arises in response to the need to make a decision when the amount of data exceeds the time available to analyze it. For instance, predicting the outcome of clinical and administrative decisions in health care is problematic because such processes are collectively defined as c omplex a daptive s ystems (CASs). A CAS is characterized by groups of individuals who act in unpredictable, nonlinear (not cause and effect) ways, such that one person’s actions affect all the others ( Holden, 2005 ). In CASs, humans do behave in unpredictable ways ( Tan et al., 2005 ). Critical thinking can help all health care personnel to examine these complex systems, wherein groups solve problems through complex, continually altering interactions between the environment and all involved in the decision making ( Fioratou et al., 2011 ). Situations within the environment constantly change and decision makers need to reframe their thinking as they broaden their awareness of the context of their decisions ( Sharma & Ivancevic, 2010 ). Having situation awareness is a must ( Fioratou et al., 2011 ; Sitterding et al., 2012 ). Decision makers need to make every effort to forecast unanticipated consequences of their decisions. For example if staffing is cut, what adverse events might occur (Kane et al., 2007)? Decision making is also influenced by the manager’s leadership style. A democratic/collaborative style of leadership and decision making works best in a complex adaptive system, such as a hospital, which is characterized by a large array of social relationships that can have an economic impact on an organization. Staff nurses who are not engaged in shared decision making may experience less job satisfaction and subsequently may leave an organization, leading to loss of expertise in patient care ( Gromley, 2011 ). However, the full array of leadership styles may at some time be used in the decision-making process. Vroom and Yetton (1973) proposed a classic managerial decision-making model that identified five managerial decision styles on a continuum from minimal subordinate involvement to delegation. Their model uses a contingency approach, which assumes that situational variables and personal attributes of the leader influence leader behavior and thus can affect organizational effectiveness. To diagnose the situation, the decision maker examines the following seven problem attributes: 1.  The importance of the quality of the decision 2.  Whether there is sufficient information/expertise 3.  The amount of structure to the problem 4.  The extent to which acceptance/commitment of followers is critical to implementation 5.  The probability that an autocratic decision will be accepted 6.  The motivation of followers to achieve organizational goals 7.  The extent to which conflict over preferred solutions is likely

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American Association of Healthcare Executives

Ethical decision-making for healthcare executives.

Approved by the Board of Governors Dec. 6, 2021.

Statement of the Issue

Ethical decision-making is required when the healthcare executive must address a conflict or uncertainty regarding competing values, such as personal, organizational, professional and societal values. Those involved in this decision-making process must consider ethical principles including justice, autonomy, beneficence and nonmaleficence, as well as professional and organizational ethical standards and codes. Many factors have contributed to the growing concern in healthcare organizations over clinical, organizational and societal ethical issues, including issues of equitable access and affordability, quality, value-based care, patient safety, disclosure of medical errors, allocation of limited resources, mergers and acquisitions, financial and other resource constraints, and advances in medical treatment that complicate decision-making near the end of life. Healthcare executives have a responsibility to recognize and address the growing number of complex ethical dilemmas they are facing, but they cannot and should not make such decisions alone or without a sound decision-making process that considers diverse viewpoints. The application of a systematic decision-making process can serve as a useful tool for leaders, staff and stakeholders in addressing ethically challenging situations.

Healthcare organizations should have resources that may include ethics committees, ethics consultation services, and written policies, procedures, frameworks and guidelines to assist them with the ethics decision-making process. With these organizational resources and guidelines in place, the best interests of patients, families, caregivers, the organization, payers and the community can be thoughtfully and appropriately evaluated in a timely manner.

Policy Position

It is incumbent upon healthcare executives to lead in a manner that promotes an ethical culture, affirms the organization’s mission and values, sets expectations and accountabilities, and models ethical behavior for their organizations. The American College of Healthcare Executives believes education in ethics is an important step in a healthcare executive’s lifelong commitment to high ethical conduct, both personally and professionally. Further, ACHE supports the development of competent organizational resources that enable healthcare executives to address ethical conflicts appropriately and expeditiously. Whereas physicians, nurses and other caregivers may primarily address clinical ethical issues on a case-by-case basis, healthcare executives also have a responsibility to address those issues at broader organizational, community and societal levels through a systematic process. ACHE encourages its members, as leaders in their organizations, to take an active role in the development and demonstration of ethical decision-making.

To this end, healthcare executives should:

• Create an ethical culture grounded in the organization’s mission and values that fosters ethical clinical and administrative practices, policies and decision-making through the application of a systematic ethics decision-making process.
• Communicate the organization’s commitment to the ethical alignment of its mission or value statements.
• Model ethical decision-making and demonstrate the importance of ethics to the organization through their expectations of professional behavior.
• Offer educational programs to boards, senior leadership, staff, physicians and others, including the community, regarding their organization’s ethical standards of practice and on the more global issues necessitating ethical decision-making in today’s healthcare environment. This includes education about cultural sensitivity and avoiding implicit bias when making ethical decisions with patients and their families. Further, healthcare executives should promote learning opportunities, such as those provided through professional societies or academic organizations, that will facilitate informed, thoughtful, respectful and open discussion of ethical issues.
• Ensure that the organizational resources addressing ethics issues are readily available and include individuals who are competent to address ethical concerns. Organizations need mechanisms for addressing both clinical and organizational ethics challenges, which could mean the creation of a separate committee to address the latter. Committees should include members from multiple disciplines including physicians, nurses, managers, administrators, board members, social workers, attorneys, patients and/or the community and clergy. Healthcare executives must act with intentionality to ensure the diverse expertise and experiences of decision-makers appropriately represents populations likely to be impacted by recommendations or policy directives.
• Ensure that ethics resources possess ongoing ethical training and are competent to address a broad range of ethical concerns (e.g., clinical, organizational, business and management).
• Seek assistance from ethics subject matter experts and resources when there is ethical uncertainty. Leaders should consider the benefits of consulting a trained ethicist when needed to address clinical issues. Furthermore, encourage others to use organizational resources to address challenging ethical issues.
• Evaluate and continually refine organizational processes for addressing ethical issues.
•  Promote decision-making that results in the appropriate balance of power with individual, organizational and societal issues. Decision-making processes should identify and safeguard against biases and acknowledge privilege to ensure the interests of vulnerable or underrepresented populations are equitably considered.

Policy created: August 1993 Last revised: November 2016

© 2023 American College of Healthcare Executives

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This one day course will present a clear process and user-friendly techniques for making smart business and personal choices. Using a case study approach, this course offers straightforward, easy-to-follow process designed to improve the way business decisions -- or any decisions that help to reach a goal – are made. This workshop incorporates lecture, group exercises, business examples and coaching in a fun and relaxed atmosphere. Participants learn and practice skills they can apply to make better quality decisions.

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Upon completion of this course, the participant  will increase their ability to:

• Assess their decision making style

• Define clear parameters of decisions

• Collect relevant information and generate creative alternatives

• Hone intuition and incorporate it into decisions

• Define consequences and payoffs

• Analyze risks and define level of risk tolerance

• Avoid common mistakes and psychological traps in the decision making process

• Correlate an appropriate strategy with a specific decision

• Describe the dynamics of group decision making

• Develop clear guidelines on communicating decisions

• Design an action plan to evaluate the results of decisions

• Tailor decision-making style to be situationally appropriate

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The content is for information and education only. The content is not intended to provide medical advice, diagnosis, or treatment. Please see the full terms of use for this content and this website .

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When Patients Do Their Own Research

At its best, medicine will be a process of shared decision making, and doctors need to be prepared.

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Miscarriage early in pregnancy is very common—roughly one-fifth of detected pregnancies are thought to end in miscarriage, mostly in the first trimester. After a single miscarriage, patients are typically told that no further testing is needed; most women go on to have healthy pregnancies.

But after multiple miscarriages, doctors and patients begin a process of figuring out what is going on. In these situations, a lot of patients will take information gathering into their own hands. They’ll compile ideas from Google, WebMD, chat boards, support groups, friends, and friends of friends. Patients may arrive at their doctor’s office with file folders of information, a cobbled-together idea of their possibilities. Meanwhile, doctors have clinical knowledge, but they may struggle—especially given their limited time—to engage with their patients’ ideas and guide them.

Medicine wasn’t always this sort of shared process. Not long ago, medical decision making was largely left to doctors. Patients were a passive bunch, arriving at the doctor with their concerns and symptoms, and departing with their doctor’s orders. But today patients have incredible access to information online and elsewhere, and this has prompted a shift to what is sometimes called “shared decision making”: patients and doctors, together, sharing the burden of making consequential health choices.

Emily Oster: Thinking about pregnancy like an economist

This approach sounds great in principle. Shouldn’t patients be involved in decision making about their own health? In the area of obstetrics, the alternative brings to mind deliveries of the 1950s—white-coated doctors smoking cigarettes in their office while women labor in “twilight sleep,” even, in many cases, strapped to the bed. Surely if women had been involved, they would have opted for something a bit more comfortable.

In practice, though, shared decision making can be a source of frustration and confusion, for both sides. From the patient side, it can feel like doctors are either expecting too much engagement— Isn’t it your job to know what to do?— or not listening and not taking the patient’s ideas and preferences seriously. Sometimes it feels like all of this at once. From the medical side, frustration also comes in several forms—with patients who do not want to engage with the decision, and with those who do but are unwilling to listen to expert advice. Why won’t they listen to me? A patient who arrives with her own research can give the impression that she believes her Google search makes her an expert in medicine.

We, the authors of this article, come at this from both angles—one of us is a doctor, and one of us is an expert in statistics who has made a career of helping millions of pregnant people sort through data to make their own best decisions. We both believe that shared decision making in medicine can work, but many doctor-patient interactions today are not working. In our new book, The Unexpected , we try to provide a road map for improving this interaction, focusing on pregnancy. Our idea is simple. Two things are missing from this conversation: some common knowledge, and a script.

First, patients cannot engage with shared decision making if they do not understand the basics of their condition. To return to the example of miscarriage: A very large share of first-trimester miscarriages are a result of chromosomal abnormalities. If a patient does not know how chromosomes work in conception and what might influence them, discussing miscarriage prevention will be difficult. A patient doesn’t possess a doctor’s understanding of their condition—this would be unrealistic—but acquiring basic knowledge will allow patients to most effectively hear and process what is being said.

In particular, patients may benefit from getting a handle on the fundamental medical terminology associated with whatever symptoms they are presenting. Unfamiliar jargon can spark fear far beyond what one would feel if she knew what was being said. “Antiphospholipid antibody syndrome” sounds terrifying if you don’t know that, for many, it’s a treatable condition. When patients do not understand, many will shut down, unable to ask the questions they have or engage with the choices they need to make.

As a result, before doctors ask people to engage with decisions about their health, they need to prepare them. Our book tries to do this for people facing complicated pregnancy conditions. In other cases—cancer treatment, diabetes, other chronic illnesses—different resources exist. Patients should do some homework before they go to the doctor’s office.

The second thing these conversations need is a script. If patients and their doctor had limitless time to talk, then maybe it would be okay to enter the conversation with only a vague idea of the purpose. But time is limited, and that means a script is key, prioritizing questions where the answers matter for decisions.

To return to the miscarriage example, a script might start with the details of what happened. Knowing exactly when in pregnancy a loss occurred, what kind of testing followed it, and how many times it has happened will shape next steps. A second question is whether there are clues as to why it happened, which will inform whether it will happen again. A script might end by talking about what can be done to decrease risk, if anything.

Read: When evidence says no, but doctors say yes

In the best form of this conversation, the doctor brings a deep understanding of what might be going on medically with the patient, the range of possible tests, and what those tests might reveal to the patient. The patient brings a knowledge of their own preferences and their own emotional state. How much information do they want to know? Would they be willing to use more complex medical treatments if they were recommended? Are they even ready to engage emotionally with thinking about trying for pregnancy again?

The central recognition here is that shared decision making isn’t about both sides bringing the same thing to the table and deliberating about it. It’s about two different types of expertise—expertise in medicine on the part of the doctor, and expertise in herself on the part of the patient. Seeing this, in turn, can help the doctors and the patient both recognize when one decision maker should be paramount, or when a decision requires input from both.

An emergency situation—when, say, a person has been in a bike accident, his blood pressure is low, and he is bleeding from his head—isn’t the time for shared decision making. This is when the medical side takes over. No patient needs to be asked whether they think it’s a good idea to scan their head for a skull fracture. At the other end of the spectrum are decisions such as prenatal genetic screening and testing, which are in many cases almost exclusively about patient values and preferences.

Most decisions fall somewhere in between, requiring medical input but with room for patients’ preferences to play a role. Attempting a vaginal birth after a C-section is an example here—both a repeat Cesarean and an attempted vaginal birth have their risks and benefits. The medical expertise comes in explaining these risks and benefits, but the decision for many women here should come down to their own preferences.

With better understanding, clear scripts, and a sense of when different decision makers should dominate, we believe there is space for some decision making to be truly shared. But one more crucial element should be present: trust. Sometimes the desire by patients to play a role in their medical care can seem like a lack of trust in their doctors. And on the flip side, when patients do not feel like their concerns, ideas, or preferences are being listened to, they can lose trust in their provider to find what is best for them . Good decisions require the trust to recognize that we are all rowing in the same direction, and the willingness to engage so we can get there.

​When you buy a book using a link on this page, we receive a commission. Thank you for supporting The Atlantic.

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Supreme Court appears to side with an Oregon city's crackdown on homelessness

Jennifer Ludden

A group of volunteers check on homeless people living in a park in Grants Pass, Ore., on March 21. Jenny Kane/AP hide caption

A group of volunteers check on homeless people living in a park in Grants Pass, Ore., on March 21.

In a major case on homelessness, the U.S. Supreme Court on Monday appeared to side with an Oregon city's crackdown on sleeping in public. The decision could have sweeping implications for the record number of people living in tents and cars, and the cities and states struggling to manage them.

The Supreme Court had declined to hear a similar case out of Boise, Idaho, in 2019. But since then rates of homelessness have spiked. An annual federal count found more than 250,000 people living in parks, on streets, and in their vehicles. Sprawling street encampments have grown larger and expanded to new places, igniting intense backlash from residents and businesses.

The current case centers on the small city of Grants Pass, Ore. , which has a population just under 40,000 and is a symbol of just how widespread the homelessness problem has become. A slew of other cities and states — led by Democrats and Republicans alike — urged the justices to take up this issue.

Cities say the courts have hamstrung efforts to address homelessness

In both the Boise and Grants Pass cases, lower courts said that under the Eighth Amendment it's cruel and unusual to fine or jail someone for sleeping on public land if there's no adequate shelter available. But Grants Pass and many other cities across the West say those rulings have tied their hands as they try to keep their public spaces open and safe for everyone.

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Grants Pass has no public shelter. But its local law essentially banned people from sleeping with a blanket or pillow on any public land, at any time.

During Monday's arguments, the Supreme Court's more liberal justices suggested this amounts to unlawfully targeting people simply because they're homeless. "You don't arrest babies who have blankets over them. You don't arrest people who are sleeping on the beach," said Justice Sotomayor.

Justice Kagan said sleeping is not a criminal act. "Sleeping is a biological necessity. It's sort of like breathing. ... But I wouldn't expect you to criminalize breathing in public."

But the court's conservative justices said it can be hard to draw the line between someone's conduct — which can be legally punished — and a status they are unable to change — which cannot be punished. "How about if there are no public bathroom facilities?" Justice Gorsuch asked. "Do people have an Eighth Amendment right to defecate and urinate? Is that conduct or is that status?"

Over and over, conservative justices also said homelessness is a complex policy problem and questioned whether courts like theirs should "micromanage" it.

"Why would you think that these nine people are the best people to judge and weigh those policy judgments?" Chief Justice Roberts asked.

Demonstrators rally outside City Hall in Grants Pass, Ore., on March 20. The self-proclaimed "park watch" group opposes public drug use in homeless encampments. Jenny Kane/AP hide caption

Demonstrators rally outside City Hall in Grants Pass, Ore., on March 20. The self-proclaimed "park watch" group opposes public drug use in homeless encampments.

Whatever the decision, this case won't solve the homelessness problem

States and cities across the U.S. have struggled to manage record rates of homelessness. Some in the West have found ways to limit encampments and even clear them out without running afoul of the 9th Circuit rulings. Elsewhere, several states have taken a more sweeping approach with camping bans. Florida's governor recently signed a law that seeks to move unhoused people off public property altogether and into government-run encampments.

Some worry that a decision in favor of Grants Pass will lead to more such moves or even a worst-case scenario of a "banishment race" if communities seek to push people out of their jurisdiction. Justice Sotomayor raised that concern during the arguments.

"Where do we put them if every city, every village, every town lacks compassion?" she said.

How far can cities go to clear homeless camps? The U.S. Supreme Court will decide

Grants Pass and other cities argue that the 9th Circuit's ruling has fueled the expansion of homeless encampments. But whichever way the case is decided, it's not likely to dramatically bring down the enormous number of people living outside in tents and vehicles. Many places simply don't have enough shelter beds for everyone. And more importantly, they don't have nearly enough permanent, affordable housing. The city of Grants Pass is short by 4,000 housing units; nationally, the deficit is in the millions.

That shortage has pushed rents to levels many cannot afford, which advocates say is a main driver of rising homelessness. Even where places are investing heavily to create more affordable housing, it will take a while to catch up. This Supreme Court case won't solve any of that, but it could dramatically shape the lives of those forced to live on streets, parks and back alleys for years to come.

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