How Might Patient Involvement in Healthcare Quality Improvement Efforts Work?A Realist Literature Review. Watch the following video:? Quality: The Process Improvement Team and
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How Might Patient Involvement in Healthcare Quality Improvement Efforts Work—A Realist Literature Review.
Watch the following video:
Quality: The Process Improvement Team and Plan-Do-Check-Act (https://www.youtube.com/watch?v=9dndmsIOrAQ)
Quality improvement in health care organizations involves a system of continuously finding better approaches to provide quality patient care and service. Health care delivery is complex and accomplished by a team of health care professionals. At its core, quality improvement is a team process and effort. In the health care ecosystem, there are various external stakeholders who have a stake on quality of care. Each internal or external stakeholder can make significant contributions to sustain quality of care and patient safety.
In 300 to 400 words:
• Identify internal stakeholders and their roles in quality improvement.
• Determine external stakeholders (e.g., payors, regulatory agencies, accrediting entities, etc.) and their roles in quality improvement.
• Evaluate the role of the patients and their family members in continuous quality improvement.
• Discuss the importance of a team in quality and risk management.
Support your response with at least two scholarly sources published within the last 5 years in APA Style.
952 | Health Expectations. 2019;22:952–964.wileyonlinelibrary.com/journal/hex
Received: 6 July 2018 | Revised: 7 March 2019 | Accepted: 6 April 2019 DOI: 10.1111/hex.12900
O R I G I N A L R E S E A R C H P A P E R
How might patient involvement in healthcare quality improvement efforts work—A realist literature review
Carolina Bergerum RN, RM, MSc1,2 | Johan Thor MD, MPH, PhD, Associate Professor2 | Karin Josefsson RNT, PhD, Professor, Senior Lecturer1 | Maria Wolmesjö PhD, Associate Professor, Senior Lecturer1
This is an open access article under the terms of the Creat ive Commo ns Attri bution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors Health Expectations published by John Wiley & Sons Ltd
1Faculty of Caring Science, Work Life and Social Welfare, University of Borås, Borås, Sweden 2School of Health and Welfare, Jönköping Academy for Improvement of Health and Welfare, Jönköping University, Jönköping, Sweden
Correspondence Carolina Bergerum, Faculty of Caring Science, Work Life and Social Welfare, University of Borås, Borås S‐501 90, Sweden. Email: [email protected]
Abstract Introduction: This realist literature review, regarding active patient involvement in healthcare quality improvement (QI), seeks to identify possible mechanisms that con‐ tribute to success or failure. Furthermore, the paper outlines key considerations for organizing and supporting patient involvement in healthcare QI efforts. Methods: Two literature searches were performed. Altogether, 1204 articles from a healthcare context were screened, focusing on improvement efforts that involve pa‐ tients, healthcare professionals and/or managers and leaders. Among these, 107 arti‐ cles fulfilled the chosen study selection criteria and were further analysed. Eighteen articles underwent a full realist review. In the realist synthesis, context‐mechanism‐ outcome configurations were articulated as middle‐range theories and organized thematically to generate a program theory on how active patient involvement in QI efforts might work. Results: The articles exhibited a diversity of patient involvement approaches at dif‐ ferent levels of healthcare organizations. To be successful, organizations’ support of QI efforts that actively involved patients tailored the QI efforts to their context to achieve the desired outcomes, and involved the relevant microsystem members. Furthermore, it promoted interaction and partnership within the microsystem, and supported the behavioural change that follows. Conclusion: This realist synthesis generates a program theory for active patient in‐ volvement in QI efforts; active patient involvement can be a tool (resource), if tailored for interaction and partnership (reasoning), that leads to behaviour change (outcome) within healthcare QI efforts. The theory explains essential resource and reasoning mechanisms, and outcomes that together form guidance for healthcare organizations when managing active patient involvement in QI efforts.
K E Y W O R D S
clinical microsystem, co‐design, co‐production, healthcare management, healthcare organization, patient involvement, quality improvement, realist review
CarolinaᅠBergerum RN, RM, MSc See footnote 1
See footnote 2
https://orcid.org/0000-0003-1281-7918 See footnote 2
https://orcid.org/0000-0003-1814-4478
See footnote 1
https://orcid.org/0000-0002-7117-9808
See footnote 1
https://orcid.org/0000-0002-8807-0876
(Footnote 1) 1Faculty of Caring Science, Work Life and Social Welfare,ᅠUniversity of Bor¥s, Bor¥s, Sweden
(Footnote 2) School of Health and Welfare, Jnkping Academy for Improvement of Health and Welfare,ᅠJnkping University, Jnkping, Sweden
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1 | I N T R O D U C T I O N
Patient involvement in health‐care improvement is attracting inter‐ est.1‐3 Due to lived experiences of different health conditions and receiving health care, patients can contribute to health‐care im‐ provement.3‐7 Increasingly, health‐care professionals are expected to involve patients at different levels of health care, and health‐care organizations and their leaders are expected to support such ef‐ forts.8‐11 Societal focus on health‐care quality, patient safety and patients’ health‐care experiences, and growing rejection of paternal‐ ism further drives efforts to involve patients—the era of co‐produc‐ tion and co‐design.4,5,7,12 In the literature, patient involvement has been described by many terms with diverse definitions—patient‐ or person‐centred care, patient or user participation and engagement, co‐creation, co‐design, co‐production, etc3‐7,12 Yet, there is no uni‐ versally agreed‐upon definition of the different patient involve‐ ment concepts or what aspects should be fulfilled for each concept. Furthermore, there are few examples, and little knowledge, of how to organize for it. These limitations in the literature cause confusion for patients, health‐care professionals, managers and health‐care organizations.3‐7
The science of quality improvement (QI) in health care concerns how to conduct QI and how to narrow the gap between current health‐care practice and the best possible practice.13,14 It focuses on “what works” to improve quality and the best ways to capture and spread lessons learned to promote positive change. Therefore, it may inform the design, or re‐design, of complex health‐care ser‐ vices.13‐18 The present study rests on the premise that the health‐ care system consists of clinical microsystems, which are nested in meso‐ and overarching macrosystems.19 Clinical microsystems are the smallest, functional units of a health‐care system where patients and health‐care professionals meet—for example an emergency room or a primary care centre. Microsystem interactions produce quality, safety and cost outcomes at the frontlines of health care. Macrosystem outcomes depend on the outcomes in the microsys‐ tems it harbours. Therefore, to improve and sustain quality in a health‐care system, key leverage points exist at the clinical microsys‐ tem level.19,20 Considering the growing interest in active patient in‐ volvement in QI, where the patients hold the role as co‐creators,21 the uncertainty over how best to orchestrate such involvement, and what outcomes to expect on micro‐, meso‐, and macrosystem levels,12,22 it is important to understand how approaches to patient involvement might work. The realist literature review approach aims to determine what works for whom, in what circumstances, in what respects and why.23‐25
Guided by questions from a local hospital organization about how to involve patients in QI activities, we set out to review stud‐ ies with active patient involvement in QI. We aimed to reveal how patient involvement in QI interventions might work in different con‐ texts, to articulate guidance for health‐care organizations on manag‐ ing active patient involvement in their QI efforts.
2 | M E T H O D S
2.1 | Realist literature review framework
The realist literature review framework23‐26 seeks to identify and explain the interaction between context, mechanism and outcome, here regarding mechanisms for patient involvement in QI. With its philosophical basis in realism, the framework was developed for complex social interventions. It is a systematic, theory‐driven inter‐ pretative technique. The approach determines what works, how, for whom, to what extent and under what conditions, expressed as “pro‐ gram theory.” 23‐27 It was developed to make sense of heterogeneous evidence about complex interventions applied in diverse contexts, and focuses on how different contexts (C) interact with different mechanisms (M) to make particular outcomes (O) more or less likely. This is expressed in “C + M = O” formulas. Consequently, a realist review proposes general recommendations in the following format: “In situations (X), complex intervention (Y), modified in this way and taking account of these circumstances, may be appropriate” to yield these outcomes (O).26
2.2 | Search strategy
Due to qualitative research, this study has been presented at seminars for colleagues from different disciplines and has evolved accordingly. Based on an initial search and review, we focused on pa‐ tients’ active involvement in QI efforts, guided by feedback from col‐ leagues, and undertook a complementary second literature search. Both search strategies were developed in collaboration with a uni‐ versity librarian and included the following electronic databases: the Web of Science (Core Collection), Scopus, Cinahl and PubMed. Authors and stakeholders were interested in the field's recent devel‐ opments, and we, therefore, limited the search to articles published from 2011 forward.
The first, broader search, which included articles published from January 2011 until February 2016, combined the following terms and keywords: quality improvement, healthcare, service, involvement, patients, next of kin, professionals, managers and leaders. This also included literature that addressed health‐care improvement more broadly, such as value‐based care and the application of clinical microsystem thinking. The second search, covering January 2011 to September 2017, focused, more specif‐ ically, on active patient involvement in QI. Terms and keywords included: user involvement, quality improvement, healthcare, service, patients, next of kin, professionals, managers and lead‐ ers. Furthermore, this search included literature that addressed the words: patient, participation, involvement, collaboration and service design. The Boolean terms “AND,” “OR” and “NEAR” were used to find the words’ intersections. The search approaches were modified as necessary to fit each database. Altogether, the two searches yielded 1204 articles.
954 | BERGERUM Et al.
2.3 | Study selection
Each article's title, abstract and subject headings were screened ac‐ cording to the following criteria:
• Publication type—original peer‐reviewed articles, published in English.
• Setting—hospital care, inpatient or outpatient hospital care; sin‐ gle speciality setting, multiple specialities in collaboration and pri‐ mary health care.
• Population—patients, health‐care professionals, managers and leaders.
• Interventions—clinical QI work that involved patients, families, next of kin, health‐care professionals and/or managers and leaders.
• Outcome reporting—empirical, clinical QI efforts, with patient health outcomes, system performance outcomes (care and/or costs), and/ or professional development as the primary outcome measure.
After this first screening, two of the study's authors independently reviewed the remaining 107 articles, in full text, against the above selection criteria. Discrepancies were resolved by consensus, and reasons for exclusion were documented for each article. This step yielded 59 articles, many of which concerned QI efforts to develop patient involvement in health care, without patients actively taking part in those QI efforts. We, therefore, selected the subgroup of ar‐ ticles with active patient involvement, resulting in 18 articles. The study selection procedures are displayed in the article selection flow diagrams (Figures 1 and 2).
2.4 | Data collection
A data collection protocol was developed by two of this study's au‐ thors, and, in the data extraction procedure, they compared their respective data collections. The protocol is available in Table S1.
2.5 | Quality assessment
To assess articles’ methodological quality, two authors developed criteria based on the Standards for Quality Improvement Reporting Excellence (SQUIRE) guidelines.28 The 26 criteria concern the ration‐ ale, specific aims, context, intervention(s), study of the intervention(s) measures, analysis, ethical considerations, results, interpretation, limitations, conclusions and funding. A methodological quality score was developed as a three‐point scale, ranging from “poor,” to “fair” to “good.” Each article was given its methodological quality score by sim‐ ply counting the number of criteria satisfied. For an article to be scored as “good,” at least 20 criteria had to be fulfilled. No article was excluded at this stage, so all 18 were brought into the realist review procedure.
2.6 | The realist synthesis procedure
To reflect the articles’ heterogeneity, they were categorized by the organizational level of their patient involvement approach3
and by the complexity of problems and interventions29 (outlined in the findings section). The literature was approached to identify mechanisms that explain why health‐care QI involving patients might, or might not, work. The synthesis involved comparing find‐ ings regarding the review questions across health‐care settings to articulate the conditions that support or hinder active patient involvement.23,25
The review questions were:
• What are the key mechanisms influencing or driving the QI effort? • What contextual factors have the most impact? • How might health‐care organizations support active patient in‐
volvement in QI?
The questions were viewed from the perspectives of patients, health‐ care professionals, managers and leaders.19,20,24,26 To complement data on the study characteristics outlined above, we identified each article's theoretical contribution—that is “how” patient involvement in QI works, “for whom,” “to what extent” and “under what conditions.” We extracted illustrative quotes and summarized, in a spreadsheet, each article's contents relevant to the review questions.
In practice, the articles were read several times to gain a general overview. Each article was then reviewed individually for C‐M‐O configurations (CMOc). In CMOc, the mechanisms explain what an intervention—for example patient involvement in QI—triggers in a given context that makes things happen to produce observable outcomes. Drawing on methodological guidance to distinguish the context from the mechanism,30 we split the “C + M = O” formula's mechanism component into “mechanism resource” (the component introduced in a context) and “mechanism reasoning” (stakeholders’ volition), yielding the formula “M resource + C → M reasoning = O” (Figure 3).
The synthesis involved identifying and articulating “middle‐range theories,” that is theoretical explanations of CMOc.24 “Middle‐range theories” explain examples of success, failure and the variations in between. They involve abstraction but are concrete enough to per‐ mit empirical testing. The “middle‐range theories” emerged in the process of identifying CMOc relevant to the review questions, map‐ ping patterns of findings, and sense‐making. They were then orga‐ nized thematically and expressed as theories.31,32 This procedure is demonstrated in Supplement 2, and the full procedure is available upon request.
The program theory31,32 was generated in an iterative procedure. Several methods were used for this, such as brain‐storming, follow‐ ing references of references, browsing grey literature23—including internal reports, national policy documents and websites—discuss‐ ing within the research team and with other researchers, and with local health‐care improvement facilitators. Thus, synthesizing the evidence, the theories were articulated, and the authors drew the study's conclusions. In line with the realist literature review pro‐ cess,23,24 this yielded a program theory on how patient involvement in QI interventions might work in different contexts, presented below.
The program theory (See page 12 Endnote 31, 32) was generated in an iterative procedure. Several methods were used for this, such as brain�storming, following references of references, browsing grey literature (See page 12 Endnote 23)�including internal reports, national policy documents and websites�discussing within the research team and with other researchers, and with local health�care improvement facilitators. Thus, synthesizing the evidence, the theories were articulated, and the authors drew the study's conclusions. In line with the realist literature review process, (See page 12 Endnote 23, 24) this yielded a program theory on how patient involvement in QI interventions might work in different contexts, presented below.
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F I G U R E 1 First article selection flow diagram [Colour figure can be viewed at wileyonlinelibrary.com]
Ar�cles included in pa�ent involvement categorisa�on: n = 29
Ar�cles screened for eligibility: n = 492
1 reviewer Ar�cles excluded by abstract & �tle review:
n = 440
1 reviewer Full-text ar�cles assessed for eligibility:
published 2016 (Jan – Feb) – 2 published 2015 – 8
published 2014 – 13 published 2013 – 10 published 2012 – 12 published 2011 – 7
n = 52
2 reviewers
Ar�cles excluded by full-text review:
Wrong design – 9 Wrong se�ng – 12
Wrong popula�on – 7 Wrong interven�on – 6 Wrong outcomes – 6
n = 23
2 reviewers
Ar�cles added to realist review: n = 7
Ar�cles excluded for being duplicates within the search:
n = 304
Ar�cles excluded due to lack of ac�ve pa�ent
involvement in QI effort: n = 22
1 reviewerAr�cles included in quality assessment: n = 7
Ar�cles excluded by quality assessment:
n = 0
1 reviewer
Ar�cles iden�fied through combined electronic database search:
Web of Science/Core Collec�on – 118 Scopus – 448 Cinahl – 36
PubMed – 194
n = 796
1 reviewer and 1 librarian
Arᄑcles idenᄑfied through combined electronic database search:
Webof Science/Core Collecᄑon � 118
Scopus �448
Cinahl � 36
PubMed � 194
n= 796
1 reviewer and 1 librarian
Arᄑcles excluded for being duplicateswithin thesearch:
n= 304 Arᄑcles screened for eligibility:
n= 492
1 reviewer Arᄑcles excluded by abstract & ᄑtle review:
n =440
1 reviewer Full-text arᄑclesassessed for eligibility:
published 2016 (Jan � Feb) �2 published 2015 � 8 published 2014 � 13 published 2013 � 10 published 2012 � 12 published 2011 � 7 n= 52
2 reviewers
Arᄑcles excluded by full-text review:
Wrong design �9 Wrong seng �12 Wrong populaᄑon � 7 Wrong intervenᄑon � 6 Wrong outcomes �6 n= 23
2 reviewers
Arᄑcles included in paᄑent involvement categorisaᄑon:
n= 29 Arᄑcles excluded due to lack of acᄑve paᄑent involvement in QI effort:
n= 22
1 reviewer Arᄑcles included in quality assessment:
n= 7
Arᄑcles excluded by quality assessment:
n= 0
1 reviewer
Arᄑcles added to realist review:
n= 7
956 | BERGERUM Et al.
F I G U R E 2 Second article selection flow diagram [Colour figure can be viewed at wileyonlinelibrary.com]
Ar�cles included in pa�ent involvement categorisa�on: n = 30
Ar�cles screened for eligibility: n = 712
1 reviewer Ar�cles excluded by abstract & �tle review:
n = 657
1 reviewer Full-text ar�cles assessed for eligibility:
published 2017 – 6 published 2016 – 12 published 2015 – 8
published 2014 – 11 published 2013 – 11 published 2012 – 7 published 2011 – 0
n = 55
2 reviewers
Ar�cles excluded by full-text review:
Wrong design – 13 Wrong se�ng – 3
Wrong popula�on – 0 Wrong interven�on – 6 Wrong outcomes – 0
Full-text not available on-line – 3
n = 25
2 reviewers
Ar�cles added to realist review: n = 11
Ar�cles excluded for being duplicates within the search:
n = 87
Ar�cles excluded because of being previously
iden�fied in of the first search: n = 36
In total n = 123 duplicates
1 reviewer
Ar�cles excluded due to lack of ac�ve pa�ent
involvement in QI effort: n = 19
1 reviewerAr�cles included in quality assessment: n = 11
Ar�cles excluded by quality assessment:
n = 0
1 reviewer
Ar�cles iden�fied through combined electronic database search:
Web of Science/Core Collec�on – 33 Scopus – 375 Cinahl – 370 PubMed – 57
n = 835
1 reviewer and 1 librarian
Arᄑcles idenᄑfied through combined electronic database search:
Web of Science/Core Collecᄑon �33 Scopus � 375 Cinahl � 370 PubMed � 57 n= 835
1 reviewer and 1 librarian
Arᄑcles excluded for being duplicateswithin the search:
n=87
Arᄑcles excluded because of being previously idenᄑfied inof the first search:
n= 36
In total n =123 duplicates
1 reviewer Arᄑcles screened for eligibility:
n= 712
1 reviewer Arᄑcles excluded by abstract & ᄑtle review:
n= 657
1 reviewer Full-text arᄑcles assessed for eligibility:
published 2017 �6 published 2016 �12 published 2015 �8 published 2014 �11 published 2013 �11 published 2012 �7 published 2011 �0 n= 55
2 reviewers
Arᄑcles excluded by full-text review:
Wrong design � 13 Wrong seng �3 Wrong populaᄑon � 0 Wrong intervenᄑon �6 Wrong outcomes � 0 Full-text not available on-line -3 n= 25
2 reviewers
Arᄑcles included in paᄑent involvement categorisaᄑon:
n= 30 Arᄑcles excluded due to lack of acᄑve paᄑent involvement in QI effort:
n= 19
1 reviewer Arᄑcles included in quality assessment:
n= 11
Arᄑcles excluded by quality assessment:
n= 0
1 reviewer
Arᄑcles added to realist review:
n= 11
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2.7 | Findings
The search strategies yielded 1,204 articles total. In assessing the methodological quality of the 18 articles included in the review, nine articles scored > 20 (ranging 20 ‐ 23) for “good” quality, 33‐41 and nine scored “fair” (ranging 11‐19).42‐50 Weaknesses were noted in several studies. For example, methods employed for assessing data completeness and accuracy, and for understanding variation within the data, were not always described. Ethical considerations were not declared in several studies. Unintended consequences and details about missing data were not always discussed, and efforts made to minimize and adjust for limitations were not consistently declared. Nevertheless, since all articles exhibited at least fair quality, they were all equally considered in the analysis.
2.8 | Description of studies
We categorized patient involvement concepts from the 18 review studies according to Gustavsson's organizational levels of patient involvement3‐5,51‐62 and to the Glouberman and Zimmerman29 com‐ plexity typology (Tables 1 and 2).
2.8.1 | Three theories for managing patient involvement
Reviewing the 18 articles, we derived 36 sets of CMOc, some of them interrelated (exemplified in Table S2). Thematically synthesiz‐ ing the “middle‐range theories” based on CMOc, three theories31,32 emerged. They indicate how QI might work in health‐care organiza‐ tions, by (a) tailoring patient involvement to the various QI efforts and contexts, (b) supporting interaction and partnership within each microsystem's QI effort and (c) supporting the behavioural change
that follows from QI efforts involving users, at all organizational levels.
2.9 | Synthesis of results
2.9.1 | Tailoring
Involving members of the relevant microsystems—the small, func‐ tional units where patients and health‐care professionals meet— influences and promotes QI efforts at all organizational levels. Enabling patients, and/or their next of kin, to share their individual goals and concerns with health‐care professionals in a direct, real‐ time way within the microsystem supports their involvement. All studies included in the review described such person‐specific and individualized interventions, where patients were actively involved and put in the lead—enabled to prioritize their needs and participate in an informed way through, for example, self‐management training, outpatient health‐care visits, patient safety issues or co‐design QI efforts.33,35,36,38,40‐46,49,50
To reach a specific target group, for example immigrant women, involvement of other key actors in the QI effort can be helpful. In one study, the involvement of local doulas who shared immigrant women's cultural background and mother tongue indirectly sup‐ ported patient involvement in cervical cancer screening. They were involved in the identification of barriers and planning, and the exe‐ cution of the QI effort and were able to encourage the immigrant women on their own terms. As a result, the number of cervical can‐ cer screening tests increased by an average of 40% during the inter‐ vention period.33
An iterative QI process, tailored to a microsystem's circum‐ stances and priorities and to research evidence, can also strengthen the responsiveness mechanism related to an intervention.34,36,45 For example, a co‐design QI approach, where patients and health‐ care professionals collaborated, focused on efforts that met both patients’ and health‐care professionals’ needs and priorities. In an outpatient rheumatology service, “the process [allows] patients to directly contribute to shaping the services they receive long‐term and realizing their opinions were of value to clinical staff and hospi‐ tal management.” 45 QI priorities within a microsystem can be iden‐ tified when patients and health‐care professionals exchange stories and experiences in face‐to‐face meetings, co‐design discussions and jointly prioritize improvement efforts. Such an approach indicates the importance of prioritizing and conducting QI, and, in turn, this reasoning may promote QI effort sustainability.39‐41,46‐50
Tailoring microsystem involvement demands organizational un‐ derstanding of the resource and reasoning mechanisms involved. One case,37 studying user involvement at several organizational levels suggests that to consider microsystem involvement valuable and recognize its effects, stakeholders benefitted from experienc‐ ing it in practice. The intervention concerned implementing a plan to enhance user involvement in a mental health hospital, and the re‐ sults illustrate that the closer the personal involvement in the imple‐ mentation process, the greater the reported experience of success.
F I G U R E 3 The context‐mechanism‐outcome configuration framework, distinguishing the resource and reasoning aspects of mechanism30 (reprinted with permission) [Colour figure can be viewed at wileyonlinelibrary.com] Http://www.wileyonlinelibrary.com
958 | BERGERUM Et al.
Participants who experienced the greatest success
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