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What the Case Study Method Really Teaches

  • Nitin Nohria

articles about case study

Seven meta-skills that stick even if the cases fade from memory.

It’s been 100 years since Harvard Business School began using the case study method. Beyond teaching specific subject matter, the case study method excels in instilling meta-skills in students. This article explains the importance of seven such skills: preparation, discernment, bias recognition, judgement, collaboration, curiosity, and self-confidence.

During my decade as dean of Harvard Business School, I spent hundreds of hours talking with our alumni. To enliven these conversations, I relied on a favorite question: “What was the most important thing you learned from your time in our MBA program?”

  • Nitin Nohria is the George F. Baker Jr. Professor at Harvard Business School and the former dean of HBS.

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  • Knowledge Base

Methodology

  • What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

  • Provide new or unexpected insights into the subject
  • Challenge or complicate existing assumptions and theories
  • Propose practical courses of action to resolve a problem
  • Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

  • Exemplify a theory by showing how it explains the case under investigation
  • Expand on a theory by uncovering new concepts and ideas that need to be incorporated
  • Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

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articles about case study

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

  • Normal distribution
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  • Published: 10 November 2020

Case study research for better evaluations of complex interventions: rationale and challenges

  • Sara Paparini   ORCID: orcid.org/0000-0002-1909-2481 1 ,
  • Judith Green 2 ,
  • Chrysanthi Papoutsi 1 ,
  • Jamie Murdoch 3 ,
  • Mark Petticrew 4 ,
  • Trish Greenhalgh 1 ,
  • Benjamin Hanckel 5 &
  • Sara Shaw 1  

BMC Medicine volume  18 , Article number:  301 ( 2020 ) Cite this article

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The need for better methods for evaluation in health research has been widely recognised. The ‘complexity turn’ has drawn attention to the limitations of relying on causal inference from randomised controlled trials alone for understanding whether, and under which conditions, interventions in complex systems improve health services or the public health, and what mechanisms might link interventions and outcomes. We argue that case study research—currently denigrated as poor evidence—is an under-utilised resource for not only providing evidence about context and transferability, but also for helping strengthen causal inferences when pathways between intervention and effects are likely to be non-linear.

Case study research, as an overall approach, is based on in-depth explorations of complex phenomena in their natural, or real-life, settings. Empirical case studies typically enable dynamic understanding of complex challenges and provide evidence about causal mechanisms and the necessary and sufficient conditions (contexts) for intervention implementation and effects. This is essential evidence not just for researchers concerned about internal and external validity, but also research users in policy and practice who need to know what the likely effects of complex programmes or interventions will be in their settings. The health sciences have much to learn from scholarship on case study methodology in the social sciences. However, there are multiple challenges in fully exploiting the potential learning from case study research. First are misconceptions that case study research can only provide exploratory or descriptive evidence. Second, there is little consensus about what a case study is, and considerable diversity in how empirical case studies are conducted and reported. Finally, as case study researchers typically (and appropriately) focus on thick description (that captures contextual detail), it can be challenging to identify the key messages related to intervention evaluation from case study reports.

Whilst the diversity of published case studies in health services and public health research is rich and productive, we recommend further clarity and specific methodological guidance for those reporting case study research for evaluation audiences.

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The need for methodological development to address the most urgent challenges in health research has been well-documented. Many of the most pressing questions for public health research, where the focus is on system-level determinants [ 1 , 2 ], and for health services research, where provisions typically vary across sites and are provided through interlocking networks of services [ 3 ], require methodological approaches that can attend to complexity. The need for methodological advance has arisen, in part, as a result of the diminishing returns from randomised controlled trials (RCTs) where they have been used to answer questions about the effects of interventions in complex systems [ 4 , 5 , 6 ]. In conditions of complexity, there is limited value in maintaining the current orientation to experimental trial designs in the health sciences as providing ‘gold standard’ evidence of effect.

There are increasing calls for methodological pluralism [ 7 , 8 ], with the recognition that complex intervention and context are not easily or usefully separated (as is often the situation when using trial design), and that system interruptions may have effects that are not reducible to linear causal pathways between intervention and outcome. These calls are reflected in a shifting and contested discourse of trial design, seen with the emergence of realist [ 9 ], adaptive and hybrid (types 1, 2 and 3) [ 10 , 11 ] trials that blend studies of effectiveness with a close consideration of the contexts of implementation. Similarly, process evaluation has now become a core component of complex healthcare intervention trials, reflected in MRC guidance on how to explore implementation, causal mechanisms and context [ 12 ].

Evidence about the context of an intervention is crucial for questions of external validity. As Woolcock [ 4 ] notes, even if RCT designs are accepted as robust for maximising internal validity, questions of transferability (how well the intervention works in different contexts) and generalisability (how well the intervention can be scaled up) remain unanswered [ 5 , 13 ]. For research evidence to have impact on policy and systems organisation, and thus to improve population and patient health, there is an urgent need for better methods for strengthening external validity, including a better understanding of the relationship between intervention and context [ 14 ].

Policymakers, healthcare commissioners and other research users require credible evidence of relevance to their settings and populations [ 15 ], to perform what Rosengarten and Savransky [ 16 ] call ‘careful abstraction’ to the locales that matter for them. They also require robust evidence for understanding complex causal pathways. Case study research, currently under-utilised in public health and health services evaluation, can offer considerable potential for strengthening faith in both external and internal validity. For example, in an empirical case study of how the policy of free bus travel had specific health effects in London, UK, a quasi-experimental evaluation (led by JG) identified how important aspects of context (a good public transport system) and intervention (that it was universal) were necessary conditions for the observed effects, thus providing useful, actionable evidence for decision-makers in other contexts [ 17 ].

The overall approach of case study research is based on the in-depth exploration of complex phenomena in their natural, or ‘real-life’, settings. Empirical case studies typically enable dynamic understanding of complex challenges rather than restricting the focus on narrow problem delineations and simple fixes. Case study research is a diverse and somewhat contested field, with multiple definitions and perspectives grounded in different ways of viewing the world, and involving different combinations of methods. In this paper, we raise awareness of such plurality and highlight the contribution that case study research can make to the evaluation of complex system-level interventions. We review some of the challenges in exploiting the current evidence base from empirical case studies and conclude by recommending that further guidance and minimum reporting criteria for evaluation using case studies, appropriate for audiences in the health sciences, can enhance the take-up of evidence from case study research.

Case study research offers evidence about context, causal inference in complex systems and implementation

Well-conducted and described empirical case studies provide evidence on context, complexity and mechanisms for understanding how, where and why interventions have their observed effects. Recognition of the importance of context for understanding the relationships between interventions and outcomes is hardly new. In 1943, Canguilhem berated an over-reliance on experimental designs for determining universal physiological laws: ‘As if one could determine a phenomenon’s essence apart from its conditions! As if conditions were a mask or frame which changed neither the face nor the picture!’ ([ 18 ] p126). More recently, a concern with context has been expressed in health systems and public health research as part of what has been called the ‘complexity turn’ [ 1 ]: a recognition that many of the most enduring challenges for developing an evidence base require a consideration of system-level effects [ 1 ] and the conceptualisation of interventions as interruptions in systems [ 19 ].

The case study approach is widely recognised as offering an invaluable resource for understanding the dynamic and evolving influence of context on complex, system-level interventions [ 20 , 21 , 22 , 23 ]. Empirically, case studies can directly inform assessments of where, when, how and for whom interventions might be successfully implemented, by helping to specify the necessary and sufficient conditions under which interventions might have effects and to consolidate learning on how interdependencies, emergence and unpredictability can be managed to achieve and sustain desired effects. Case study research has the potential to address four objectives for improving research and reporting of context recently set out by guidance on taking account of context in population health research [ 24 ], that is to (1) improve the appropriateness of intervention development for specific contexts, (2) improve understanding of ‘how’ interventions work, (3) better understand how and why impacts vary across contexts and (4) ensure reports of intervention studies are most useful for decision-makers and researchers.

However, evaluations of complex healthcare interventions have arguably not exploited the full potential of case study research and can learn much from other disciplines. For evaluative research, exploratory case studies have had a traditional role of providing data on ‘process’, or initial ‘hypothesis-generating’ scoping, but might also have an increasing salience for explanatory aims. Across the social and political sciences, different kinds of case studies are undertaken to meet diverse aims (description, exploration or explanation) and across different scales (from small N qualitative studies that aim to elucidate processes, or provide thick description, to more systematic techniques designed for medium-to-large N cases).

Case studies with explanatory aims vary in terms of their positioning within mixed-methods projects, with designs including (but not restricted to) (1) single N of 1 studies of interventions in specific contexts, where the overall design is a case study that may incorporate one or more (randomised or not) comparisons over time and between variables within the case; (2) a series of cases conducted or synthesised to provide explanation from variations between cases; and (3) case studies of particular settings within RCT or quasi-experimental designs to explore variation in effects or implementation.

Detailed qualitative research (typically done as ‘case studies’ within process evaluations) provides evidence for the plausibility of mechanisms [ 25 ], offering theoretical generalisations for how interventions may function under different conditions. Although RCT designs reduce many threats to internal validity, the mechanisms of effect remain opaque, particularly when the causal pathways between ‘intervention’ and ‘effect’ are long and potentially non-linear: case study research has a more fundamental role here, in providing detailed observational evidence for causal claims [ 26 ] as well as producing a rich, nuanced picture of tensions and multiple perspectives [ 8 ].

Longitudinal or cross-case analysis may be best suited for evidence generation in system-level evaluative research. Turner [ 27 ], for instance, reflecting on the complex processes in major system change, has argued for the need for methods that integrate learning across cases, to develop theoretical knowledge that would enable inferences beyond the single case, and to develop generalisable theory about organisational and structural change in health systems. Qualitative Comparative Analysis (QCA) [ 28 ] is one such formal method for deriving causal claims, using set theory mathematics to integrate data from empirical case studies to answer questions about the configurations of causal pathways linking conditions to outcomes [ 29 , 30 ].

Nonetheless, the single N case study, too, provides opportunities for theoretical development [ 31 ], and theoretical generalisation or analytical refinement [ 32 ]. How ‘the case’ and ‘context’ are conceptualised is crucial here. Findings from the single case may seem to be confined to its intrinsic particularities in a specific and distinct context [ 33 ]. However, if such context is viewed as exemplifying wider social and political forces, the single case can be ‘telling’, rather than ‘typical’, and offer insight into a wider issue [ 34 ]. Internal comparisons within the case can offer rich possibilities for logical inferences about causation [ 17 ]. Further, case studies of any size can be used for theory testing through refutation [ 22 ]. The potential lies, then, in utilising the strengths and plurality of case study to support theory-driven research within different methodological paradigms.

Evaluation research in health has much to learn from a range of social sciences where case study methodology has been used to develop various kinds of causal inference. For instance, Gerring [ 35 ] expands on the within-case variations utilised to make causal claims. For Gerring [ 35 ], case studies come into their own with regard to invariant or strong causal claims (such as X is a necessary and/or sufficient condition for Y) rather than for probabilistic causal claims. For the latter (where experimental methods might have an advantage in estimating effect sizes), case studies offer evidence on mechanisms: from observations of X affecting Y, from process tracing or from pattern matching. Case studies also support the study of emergent causation, that is, the multiple interacting properties that account for particular and unexpected outcomes in complex systems, such as in healthcare [ 8 ].

Finally, efficacy (or beliefs about efficacy) is not the only contributor to intervention uptake, with a range of organisational and policy contingencies affecting whether an intervention is likely to be rolled out in practice. Case study research is, therefore, invaluable for learning about contextual contingencies and identifying the conditions necessary for interventions to become normalised (i.e. implemented routinely) in practice [ 36 ].

The challenges in exploiting evidence from case study research

At present, there are significant challenges in exploiting the benefits of case study research in evaluative health research, which relate to status, definition and reporting. Case study research has been marginalised at the bottom of an evidence hierarchy, seen to offer little by way of explanatory power, if nonetheless useful for adding descriptive data on process or providing useful illustrations for policymakers [ 37 ]. This is an opportune moment to revisit this low status. As health researchers are increasingly charged with evaluating ‘natural experiments’—the use of face masks in the response to the COVID-19 pandemic being a recent example [ 38 ]—rather than interventions that take place in settings that can be controlled, research approaches using methods to strengthen causal inference that does not require randomisation become more relevant.

A second challenge for improving the use of case study evidence in evaluative health research is that, as we have seen, what is meant by ‘case study’ varies widely, not only across but also within disciplines. There is indeed little consensus amongst methodologists as to how to define ‘a case study’. Definitions focus, variously, on small sample size or lack of control over the intervention (e.g. [ 39 ] p194), on in-depth study and context [ 40 , 41 ], on the logic of inference used [ 35 ] or on distinct research strategies which incorporate a number of methods to address questions of ‘how’ and ‘why’ [ 42 ]. Moreover, definitions developed for specific disciplines do not capture the range of ways in which case study research is carried out across disciplines. Multiple definitions of case study reflect the richness and diversity of the approach. However, evidence suggests that a lack of consensus across methodologists results in some of the limitations of published reports of empirical case studies [ 43 , 44 ]. Hyett and colleagues [ 43 ], for instance, reviewing reports in qualitative journals, found little match between methodological definitions of case study research and how authors used the term.

This raises the third challenge we identify that case study reports are typically not written in ways that are accessible or useful for the evaluation research community and policymakers. Case studies may not appear in journals widely read by those in the health sciences, either because space constraints preclude the reporting of rich, thick descriptions, or because of the reported lack of willingness of some biomedical journals to publish research that uses qualitative methods [ 45 ], signalling the persistence of the aforementioned evidence hierarchy. Where they do, however, the term ‘case study’ is used to indicate, interchangeably, a qualitative study, an N of 1 sample, or a multi-method, in-depth analysis of one example from a population of phenomena. Definitions of what constitutes the ‘case’ are frequently lacking and appear to be used as a synonym for the settings in which the research is conducted. Despite offering insights for evaluation, the primary aims may not have been evaluative, so the implications may not be explicitly drawn out. Indeed, some case study reports might properly be aiming for thick description without necessarily seeking to inform about context or causality.

Acknowledging plurality and developing guidance

We recognise that definitional and methodological plurality is not only inevitable, but also a necessary and creative reflection of the very different epistemological and disciplinary origins of health researchers, and the aims they have in doing and reporting case study research. Indeed, to provide some clarity, Thomas [ 46 ] has suggested a typology of subject/purpose/approach/process for classifying aims (e.g. evaluative or exploratory), sample rationale and selection and methods for data generation of case studies. We also recognise that the diversity of methods used in case study research, and the necessary focus on narrative reporting, does not lend itself to straightforward development of formal quality or reporting criteria.

Existing checklists for reporting case study research from the social sciences—for example Lincoln and Guba’s [ 47 ] and Stake’s [ 33 ]—are primarily orientated to the quality of narrative produced, and the extent to which they encapsulate thick description, rather than the more pragmatic issues of implications for intervention effects. Those designed for clinical settings, such as the CARE (CAse REports) guidelines, provide specific reporting guidelines for medical case reports about single, or small groups of patients [ 48 ], not for case study research.

The Design of Case Study Research in Health Care (DESCARTE) model [ 44 ] suggests a series of questions to be asked of a case study researcher (including clarity about the philosophy underpinning their research), study design (with a focus on case definition) and analysis (to improve process). The model resembles toolkits for enhancing the quality and robustness of qualitative and mixed-methods research reporting, and it is usefully open-ended and non-prescriptive. However, even if it does include some reflections on context, the model does not fully address aspects of context, logic and causal inference that are perhaps most relevant for evaluative research in health.

Hence, for evaluative research where the aim is to report empirical findings in ways that are intended to be pragmatically useful for health policy and practice, this may be an opportune time to consider how to best navigate plurality around what is (minimally) important to report when publishing empirical case studies, especially with regards to the complex relationships between context and interventions, information that case study research is well placed to provide.

The conventional scientific quest for certainty, predictability and linear causality (maximised in RCT designs) has to be augmented by the study of uncertainty, unpredictability and emergent causality [ 8 ] in complex systems. This will require methodological pluralism, and openness to broadening the evidence base to better understand both causality in and the transferability of system change intervention [ 14 , 20 , 23 , 25 ]. Case study research evidence is essential, yet is currently under exploited in the health sciences. If evaluative health research is to move beyond the current impasse on methods for understanding interventions as interruptions in complex systems, we need to consider in more detail how researchers can conduct and report empirical case studies which do aim to elucidate the contextual factors which interact with interventions to produce particular effects. To this end, supported by the UK’s Medical Research Council, we are embracing the challenge to develop guidance for case study researchers studying complex interventions. Following a meta-narrative review of the literature, we are planning a Delphi study to inform guidance that will, at minimum, cover the value of case study research for evaluating the interrelationship between context and complex system-level interventions; for situating and defining ‘the case’, and generalising from case studies; as well as provide specific guidance on conducting, analysing and reporting case study research. Our hope is that such guidance can support researchers evaluating interventions in complex systems to better exploit the diversity and richness of case study research.

Availability of data and materials

Not applicable (article based on existing available academic publications)

Abbreviations

Qualitative comparative analysis

Quasi-experimental design

Randomised controlled trial

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This work was funded by the Medical Research Council - MRC Award MR/S014632/1 HCS: Case study, Context and Complex interventions (TRIPLE C). SP was additionally funded by the University of Oxford's Higher Education Innovation Fund (HEIF).

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Sara Paparini, Chrysanthi Papoutsi, Trish Greenhalgh & Sara Shaw

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Paparini, S., Green, J., Papoutsi, C. et al. Case study research for better evaluations of complex interventions: rationale and challenges. BMC Med 18 , 301 (2020). https://doi.org/10.1186/s12916-020-01777-6

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  • Perspective
  • Published: 22 November 2022

Single case studies are a powerful tool for developing, testing and extending theories

  • Lyndsey Nickels   ORCID: orcid.org/0000-0002-0311-3524 1 , 2 ,
  • Simon Fischer-Baum   ORCID: orcid.org/0000-0002-6067-0538 3 &
  • Wendy Best   ORCID: orcid.org/0000-0001-8375-5916 4  

Nature Reviews Psychology volume  1 ,  pages 733–747 ( 2022 ) Cite this article

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Psychology embraces a diverse range of methodologies. However, most rely on averaging group data to draw conclusions. In this Perspective, we argue that single case methodology is a valuable tool for developing and extending psychological theories. We stress the importance of single case and case series research, drawing on classic and contemporary cases in which cognitive and perceptual deficits provide insights into typical cognitive processes in domains such as memory, delusions, reading and face perception. We unpack the key features of single case methodology, describe its strengths, its value in adjudicating between theories, and outline its benefits for a better understanding of deficits and hence more appropriate interventions. The unique insights that single case studies have provided illustrate the value of in-depth investigation within an individual. Single case methodology has an important place in the psychologist’s toolkit and it should be valued as a primary research tool.

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The authors thank all of those pioneers of and advocates for single case study research who have mentored, inspired and encouraged us over the years, and the many other colleagues with whom we have discussed these issues.

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This chapter reviews the strengths and limitations of case study as a research method in social sciences. It provides an account of an evidence base to justify why a case study is best suitable for some research questions and why not for some other research questions. Case study designing around the research context, defining the structure and modality, conducting the study, collecting the data through triangulation mode, analysing the data, and interpreting the data and theory building at the end give a holistic view of it. In addition, the chapter also focuses on the types of case study and when and where to use case study as a research method in social science research.

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Hertz CEO Kathryn Marinello with CFO Jamere Jackson and other members of the executive team in 2017

Top 40 Most Popular Case Studies of 2021

Two cases about Hertz claimed top spots in 2021's Top 40 Most Popular Case Studies

Two cases on the uses of debt and equity at Hertz claimed top spots in the CRDT’s (Case Research and Development Team) 2021 top 40 review of cases.

Hertz (A) took the top spot. The case details the financial structure of the rental car company through the end of 2019. Hertz (B), which ranked third in CRDT’s list, describes the company’s struggles during the early part of the COVID pandemic and its eventual need to enter Chapter 11 bankruptcy. 

The success of the Hertz cases was unprecedented for the top 40 list. Usually, cases take a number of years to gain popularity, but the Hertz cases claimed top spots in their first year of release. Hertz (A) also became the first ‘cooked’ case to top the annual review, as all of the other winners had been web-based ‘raw’ cases.

Besides introducing students to the complicated financing required to maintain an enormous fleet of cars, the Hertz cases also expanded the diversity of case protagonists. Kathyrn Marinello was the CEO of Hertz during this period and the CFO, Jamere Jackson is black.

Sandwiched between the two Hertz cases, Coffee 2016, a perennial best seller, finished second. “Glory, Glory, Man United!” a case about an English football team’s IPO made a surprise move to number four.  Cases on search fund boards, the future of malls,  Norway’s Sovereign Wealth fund, Prodigy Finance, the Mayo Clinic, and Cadbury rounded out the top ten.

Other year-end data for 2021 showed:

  • Online “raw” case usage remained steady as compared to 2020 with over 35K users from 170 countries and all 50 U.S. states interacting with 196 cases.
  • Fifty four percent of raw case users came from outside the U.S..
  • The Yale School of Management (SOM) case study directory pages received over 160K page views from 177 countries with approximately a third originating in India followed by the U.S. and the Philippines.
  • Twenty-six of the cases in the list are raw cases.
  • A third of the cases feature a woman protagonist.
  • Orders for Yale SOM case studies increased by almost 50% compared to 2020.
  • The top 40 cases were supervised by 19 different Yale SOM faculty members, several supervising multiple cases.

CRDT compiled the Top 40 list by combining data from its case store, Google Analytics, and other measures of interest and adoption.

All of this year’s Top 40 cases are available for purchase from the Yale Management Media store .

And the Top 40 cases studies of 2021 are:

1.   Hertz Global Holdings (A): Uses of Debt and Equity

2.   Coffee 2016

3.   Hertz Global Holdings (B): Uses of Debt and Equity 2020

4.   Glory, Glory Man United!

5.   Search Fund Company Boards: How CEOs Can Build Boards to Help Them Thrive

6.   The Future of Malls: Was Decline Inevitable?

7.   Strategy for Norway's Pension Fund Global

8.   Prodigy Finance

9.   Design at Mayo

10. Cadbury

11. City Hospital Emergency Room

13. Volkswagen

14. Marina Bay Sands

15. Shake Shack IPO

16. Mastercard

17. Netflix

18. Ant Financial

19. AXA: Creating the New CR Metrics

20. IBM Corporate Service Corps

21. Business Leadership in South Africa's 1994 Reforms

22. Alternative Meat Industry

23. Children's Premier

24. Khalil Tawil and Umi (A)

25. Palm Oil 2016

26. Teach For All: Designing a Global Network

27. What's Next? Search Fund Entrepreneurs Reflect on Life After Exit

28. Searching for a Search Fund Structure: A Student Takes a Tour of Various Options

30. Project Sammaan

31. Commonfund ESG

32. Polaroid

33. Connecticut Green Bank 2018: After the Raid

34. FieldFresh Foods

35. The Alibaba Group

36. 360 State Street: Real Options

37. Herman Miller

38. AgBiome

39. Nathan Cummings Foundation

40. Toyota 2010

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What Is a Case Study?

Weighing the pros and cons of this method of research

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

articles about case study

Cara Lustik is a fact-checker and copywriter.

articles about case study

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  • Pros and Cons

What Types of Case Studies Are Out There?

Where do you find data for a case study, how do i write a psychology case study.

A case study is an in-depth study of one person, group, or event. In a case study, nearly every aspect of the subject's life and history is analyzed to seek patterns and causes of behavior. Case studies can be used in many different fields, including psychology, medicine, education, anthropology, political science, and social work.

The point of a case study is to learn as much as possible about an individual or group so that the information can be generalized to many others. Unfortunately, case studies tend to be highly subjective, and it is sometimes difficult to generalize results to a larger population.

While case studies focus on a single individual or group, they follow a format similar to other types of psychology writing. If you are writing a case study, we got you—here are some rules of APA format to reference.  

At a Glance

A case study, or an in-depth study of a person, group, or event, can be a useful research tool when used wisely. In many cases, case studies are best used in situations where it would be difficult or impossible for you to conduct an experiment. They are helpful for looking at unique situations and allow researchers to gather a lot of˜ information about a specific individual or group of people. However, it's important to be cautious of any bias we draw from them as they are highly subjective.

What Are the Benefits and Limitations of Case Studies?

A case study can have its strengths and weaknesses. Researchers must consider these pros and cons before deciding if this type of study is appropriate for their needs.

One of the greatest advantages of a case study is that it allows researchers to investigate things that are often difficult or impossible to replicate in a lab. Some other benefits of a case study:

  • Allows researchers to capture information on the 'how,' 'what,' and 'why,' of something that's implemented
  • Gives researchers the chance to collect information on why one strategy might be chosen over another
  • Permits researchers to develop hypotheses that can be explored in experimental research

On the other hand, a case study can have some drawbacks:

  • It cannot necessarily be generalized to the larger population
  • Cannot demonstrate cause and effect
  • It may not be scientifically rigorous
  • It can lead to bias

Researchers may choose to perform a case study if they want to explore a unique or recently discovered phenomenon. Through their insights, researchers develop additional ideas and study questions that might be explored in future studies.

It's important to remember that the insights from case studies cannot be used to determine cause-and-effect relationships between variables. However, case studies may be used to develop hypotheses that can then be addressed in experimental research.

Case Study Examples

There have been a number of notable case studies in the history of psychology. Much of  Freud's work and theories were developed through individual case studies. Some great examples of case studies in psychology include:

  • Anna O : Anna O. was a pseudonym of a woman named Bertha Pappenheim, a patient of a physician named Josef Breuer. While she was never a patient of Freud's, Freud and Breuer discussed her case extensively. The woman was experiencing symptoms of a condition that was then known as hysteria and found that talking about her problems helped relieve her symptoms. Her case played an important part in the development of talk therapy as an approach to mental health treatment.
  • Phineas Gage : Phineas Gage was a railroad employee who experienced a terrible accident in which an explosion sent a metal rod through his skull, damaging important portions of his brain. Gage recovered from his accident but was left with serious changes in both personality and behavior.
  • Genie : Genie was a young girl subjected to horrific abuse and isolation. The case study of Genie allowed researchers to study whether language learning was possible, even after missing critical periods for language development. Her case also served as an example of how scientific research may interfere with treatment and lead to further abuse of vulnerable individuals.

Such cases demonstrate how case research can be used to study things that researchers could not replicate in experimental settings. In Genie's case, her horrific abuse denied her the opportunity to learn a language at critical points in her development.

This is clearly not something researchers could ethically replicate, but conducting a case study on Genie allowed researchers to study phenomena that are otherwise impossible to reproduce.

There are a few different types of case studies that psychologists and other researchers might use:

  • Collective case studies : These involve studying a group of individuals. Researchers might study a group of people in a certain setting or look at an entire community. For example, psychologists might explore how access to resources in a community has affected the collective mental well-being of those who live there.
  • Descriptive case studies : These involve starting with a descriptive theory. The subjects are then observed, and the information gathered is compared to the pre-existing theory.
  • Explanatory case studies : These   are often used to do causal investigations. In other words, researchers are interested in looking at factors that may have caused certain things to occur.
  • Exploratory case studies : These are sometimes used as a prelude to further, more in-depth research. This allows researchers to gather more information before developing their research questions and hypotheses .
  • Instrumental case studies : These occur when the individual or group allows researchers to understand more than what is initially obvious to observers.
  • Intrinsic case studies : This type of case study is when the researcher has a personal interest in the case. Jean Piaget's observations of his own children are good examples of how an intrinsic case study can contribute to the development of a psychological theory.

The three main case study types often used are intrinsic, instrumental, and collective. Intrinsic case studies are useful for learning about unique cases. Instrumental case studies help look at an individual to learn more about a broader issue. A collective case study can be useful for looking at several cases simultaneously.

The type of case study that psychology researchers use depends on the unique characteristics of the situation and the case itself.

There are a number of different sources and methods that researchers can use to gather information about an individual or group. Six major sources that have been identified by researchers are:

  • Archival records : Census records, survey records, and name lists are examples of archival records.
  • Direct observation : This strategy involves observing the subject, often in a natural setting . While an individual observer is sometimes used, it is more common to utilize a group of observers.
  • Documents : Letters, newspaper articles, administrative records, etc., are the types of documents often used as sources.
  • Interviews : Interviews are one of the most important methods for gathering information in case studies. An interview can involve structured survey questions or more open-ended questions.
  • Participant observation : When the researcher serves as a participant in events and observes the actions and outcomes, it is called participant observation.
  • Physical artifacts : Tools, objects, instruments, and other artifacts are often observed during a direct observation of the subject.

If you have been directed to write a case study for a psychology course, be sure to check with your instructor for any specific guidelines you need to follow. If you are writing your case study for a professional publication, check with the publisher for their specific guidelines for submitting a case study.

Here is a general outline of what should be included in a case study.

Section 1: A Case History

This section will have the following structure and content:

Background information : The first section of your paper will present your client's background. Include factors such as age, gender, work, health status, family mental health history, family and social relationships, drug and alcohol history, life difficulties, goals, and coping skills and weaknesses.

Description of the presenting problem : In the next section of your case study, you will describe the problem or symptoms that the client presented with.

Describe any physical, emotional, or sensory symptoms reported by the client. Thoughts, feelings, and perceptions related to the symptoms should also be noted. Any screening or diagnostic assessments that are used should also be described in detail and all scores reported.

Your diagnosis : Provide your diagnosis and give the appropriate Diagnostic and Statistical Manual code. Explain how you reached your diagnosis, how the client's symptoms fit the diagnostic criteria for the disorder(s), or any possible difficulties in reaching a diagnosis.

Section 2: Treatment Plan

This portion of the paper will address the chosen treatment for the condition. This might also include the theoretical basis for the chosen treatment or any other evidence that might exist to support why this approach was chosen.

  • Cognitive behavioral approach : Explain how a cognitive behavioral therapist would approach treatment. Offer background information on cognitive behavioral therapy and describe the treatment sessions, client response, and outcome of this type of treatment. Make note of any difficulties or successes encountered by your client during treatment.
  • Humanistic approach : Describe a humanistic approach that could be used to treat your client, such as client-centered therapy . Provide information on the type of treatment you chose, the client's reaction to the treatment, and the end result of this approach. Explain why the treatment was successful or unsuccessful.
  • Psychoanalytic approach : Describe how a psychoanalytic therapist would view the client's problem. Provide some background on the psychoanalytic approach and cite relevant references. Explain how psychoanalytic therapy would be used to treat the client, how the client would respond to therapy, and the effectiveness of this treatment approach.
  • Pharmacological approach : If treatment primarily involves the use of medications, explain which medications were used and why. Provide background on the effectiveness of these medications and how monotherapy may compare with an approach that combines medications with therapy or other treatments.

This section of a case study should also include information about the treatment goals, process, and outcomes.

When you are writing a case study, you should also include a section where you discuss the case study itself, including the strengths and limitiations of the study. You should note how the findings of your case study might support previous research. 

In your discussion section, you should also describe some of the implications of your case study. What ideas or findings might require further exploration? How might researchers go about exploring some of these questions in additional studies?

Need More Tips?

Here are a few additional pointers to keep in mind when formatting your case study:

  • Never refer to the subject of your case study as "the client." Instead, use their name or a pseudonym.
  • Read examples of case studies to gain an idea about the style and format.
  • Remember to use APA format when citing references .

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach .  BMC Med Res Methodol . 2011;11:100.

Crowe S, Cresswell K, Robertson A, Huby G, Avery A, Sheikh A. The case study approach . BMC Med Res Methodol . 2011 Jun 27;11:100. doi:10.1186/1471-2288-11-100

Gagnon, Yves-Chantal.  The Case Study as Research Method: A Practical Handbook . Canada, Chicago Review Press Incorporated DBA Independent Pub Group, 2010.

Yin, Robert K. Case Study Research and Applications: Design and Methods . United States, SAGE Publications, 2017.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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The case study approach

  • Sarah Crowe 1 ,
  • Kathrin Cresswell 2 ,
  • Ann Robertson 2 ,
  • Guro Huby 3 ,
  • Anthony Avery 1 &
  • Aziz Sheikh 2  

BMC Medical Research Methodology volume  11 , Article number:  100 ( 2011 ) Cite this article

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The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

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Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables 1 , 2 , 3 and 4 ) and those of others to illustrate our discussion[ 3 – 7 ].

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables 2 , 3 and 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 – 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables 2 and 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 – 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table 8 )[ 8 , 18 – 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table 9 )[ 8 ].

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

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Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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Sarah Crowe & Anthony Avery

Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Kathrin Cresswell, Ann Robertson & Aziz Sheikh

School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

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Correspondence to Sarah Crowe .

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Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

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Crowe, S., Cresswell, K., Robertson, A. et al. The case study approach. BMC Med Res Methodol 11 , 100 (2011). https://doi.org/10.1186/1471-2288-11-100

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  • Published: 19 February 2024

Sustaining the collaborative chronic care model in outpatient mental health: a matrixed multiple case study

  • Bo Kim 1 , 2 ,
  • Jennifer L. Sullivan 3 , 4 ,
  • Madisen E. Brown 1 ,
  • Samantha L. Connolly 1 , 2 ,
  • Elizabeth G. Spitzer 1 , 5 ,
  • Hannah M. Bailey 1 ,
  • Lauren M. Sippel 6 , 7 ,
  • Kendra Weaver 8 &
  • Christopher J. Miller 1 , 2  

Implementation Science volume  19 , Article number:  16 ( 2024 ) Cite this article

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Sustaining evidence-based practices (EBPs) is crucial to ensuring care quality and addressing health disparities. Approaches to identifying factors related to sustainability are critically needed. One such approach is Matrixed Multiple Case Study (MMCS), which identifies factors and their combinations that influence implementation. We applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM) at nine Department of Veterans Affairs (VA) outpatient mental health clinics, 3–4 years after implementation support had concluded.

We conducted a directed content analysis of 30 provider interviews, using 6 CCM elements and 4 Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) domains as codes. Based on CCM code summaries, we designated each site as high/medium/low sustainability. We used i-PARIHS code summaries to identify relevant factors for each site, the extent of their presence, and the type of influence they had on sustainability (enabling/neutral/hindering/unclear). We organized these data into a sortable matrix and assessed sustainability-related cross-site trends.

CCM sustainability status was distributed among the sites, with three sites each being high, medium, and low. Twenty-five factors were identified from the i-PARIHS code summaries, of which 3 exhibited strong trends by sustainability status (relevant i-PARIHS domain in square brackets): “Collaborativeness/Teamwork [Recipients],” “Staff/Leadership turnover [Recipients],” and “Having a consistent/strong internal facilitator [Facilitation]” during and after active implementation. At most high-sustainability sites only, (i) “Having a knowledgeable/helpful external facilitator [Facilitation]” was variably present and enabled sustainability when present, while (ii) “Clarity about what CCM comprises [Innovation],” “Interdisciplinary coordination [Recipients],” and “Adequate clinic space for CCM team members [Context]” were somewhat or less present with mixed influences on sustainability.

Conclusions

MMCS revealed that CCM sustainability in VA outpatient mental health clinics may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators. These findings have informed a subsequent CCM implementation trial that prospectively examines whether enhancing the above-mentioned factors within implementation facilitation improves sustainability. MMCS is a systematic approach to multi-site examination that can be used to investigate sustainability-related factors applicable to other EBPs and across multiple contexts.

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Contributions to the literature

We examined the ways in which the sustainability of the evidence-based Collaborative Chronic Care Model differed across nine outpatient mental health clinics where it was implemented.

This work demonstrates a unique application of the Matrixed Multiple Case Study (MMCS) method, originally developed to identify factors and their combinations that influence implementation, to investigate the long-term sustainability of a previously implemented evidence-based practice.

Contextual influences on sustainability identified through this work, as well as the systematic approach to multi-site examination offered by MMCS, can inform future efforts to sustainably implement and methodically evaluate an evidence-based practice’s uptake and continued use in routine care.

The sustainability of evidence-based practices (EBPs) over time is crucial to maximize the public health impact of EBPs implemented into routine care. Implementation evaluators focus on sustainability as a central implementation outcome, and funders of implementation efforts seek sustained long-term returns on their investment. Furthermore, practitioners and leadership at implementation sites face the task of sustaining an EBP’s usage even after implementation funding, support, and associated evaluation efforts conclude. The circumstances and influences contributing to EBP sustainability are therefore of high interest to the field of implementation science.

Sustainability depends on the specific EBP being implemented, the individuals undergoing the implementation, the contexts in which the implementation takes place, and the facilitation of (i.e., support for) the implementation. Hence, universal conditions that invariably lead to sustainability are challenging to establish. Even if a set of conditions could be identified as being associated with high sustainability “on average,” its usefulness is questionable when most real-world implementation contexts may deviate from “average” on key implementation-relevant metrics.

Thus, when seeking a better understanding of EBP sustainability, there is a critical need for methods that examine the ways in which sustainability varies in diverse contexts. One such method is Matrixed Multiple Case Study (MMCS) [ 1 ], which is beginning to be applied in implementation research to identify factors related to implementation [ 2 , 3 , 4 , 5 ]. MMCS capitalizes on the many contextual variations and heterogeneous outcomes that are expected when an EBP is implemented across multiple sites. Specifically, MMCS provides a formalized sequence of steps for cross-site analysis by arranging data into an array of matrices, which are sorted and filtered to test for expected factors and identify less expected factors influencing an implementation outcome of interest.

Although the MMCS represents a promising method for systematically exploring the “black box” of the ways in which implementation is more or less successful, it has not yet been applied to investigate the long-term sustainability of implemented EBPs. Therefore, we applied MMCS to identify factors related to the sustainability of the evidence-based Collaborative Chronic Care Model (CCM), previously implemented using implementation facilitation [ 6 , 7 , 8 ], at nine VA medical centers’ outpatient general mental health clinics. An earlier interview-based investigation of CCM provider perspectives had identified key determinants of CCM sustainability at the sites, yet characteristics related to the ways in which CCM sustainability differed at the sites are still not well understood. For this reason, our objective was to apply MMCS to examine the interview data to determine factors associated with CCM sustainability at each site.

Clinical and implementation contexts

CCM-based care aims to ensure that patients are treated in a coordinated, patient-centered, and anticipatory manner. This project’s nine outpatient general mental health clinics had participated in a hybrid CCM effectiveness-implementation trial 3 to 4 years prior, which had resulted in improved clinical outcomes that were not universally maintained post-implementation (i.e., after implementation funding and associated evaluation efforts concluded) [ 7 , 9 ]. This lack of aggregate sustainability across the nine clinics is what prompted the earlier interview-based investigation of CCM provider perspectives that identified key determinants of CCM sustainability at the trial sites [ 10 ].

These prior works were conducted in VA outpatient mental health teams, known as Behavioral Health Interdisciplinary Program (BHIP) teams. While there was variability in the exact composition of each BHIP team, all teams consisted of a multidisciplinary set of frontline clinicians (e.g., psychiatrists, psychologists, social workers, nurses) and support staff, serving a panel of about 1000 patients each.

This current project applied MMCS to examine the data from the earlier interviews [ 10 ] for the ways in which CCM sustainability differed at the sites and the factors related to sustainability. The project was determined to be non-research by the VA Boston Research and Development Service, and therefore did not require oversight by the Institutional Review Board (IRB). Details regarding the procedures undertaken for the completed hybrid CCM effectiveness-implementation trial, which serves as the context for this project, have been previously published [ 6 , 7 ]. Similarly, details regarding data collection for the follow-up provider interviews have also been previously published [ 10 ]. We provide a brief overview of the steps that we took for data collection and describe the steps that we took for applying MMCS to analyze the interview data. Additional file  1 outlines our use of the Consolidated Criteria for Reporting Qualitative Research (COREQ) Checklist [ 11 ].

Data collection

We recruited 30 outpatient mental health providers across the nine sites that had participated in the CCM implementation trial, including a multidisciplinary mix of mental health leaders and frontline staff. We recruited participants via email, and we obtained verbal informed consent from all participants. Each interview lasted between 30 and 60 min and focused on the degree to which the participant perceived care processes to have remained aligned to the CCM’s six core elements: work role redesign, patient self-management support, provider decision support, clinical information systems, linkages to community resources, and organizational/leadership support [ 12 , 13 , 14 ]. Interview questions also inquired about the participant’s perceived barriers and enablers influencing CCM sustainability, as well as about the latest status of CCM-based care practices. Interviews were digitally recorded and professionally transcribed. Additional details regarding data collection have been previously published [ 10 ].

Data analysis

We applied MMCS’ nine analytical steps [ 1 ] to the interview data. Each step described below was led by one designated member of the project team, with subsequent review by all project team members to reach a consensus on the examination conducted for each step.

We established the evaluation goal (step 1) to identify the ways in which sustainability differed across the sites and the factors related to sustainability, defining sustainability (step 2) as the continued existence of CCM-aligned care practices—namely, that care processes remained aligned with the six core CCM elements. Table  1 shows examples of care processes that align with each CCM element. As our prior works directly leading up to this project (i.e., design and evaluation of the CCM implementation trial that involved the very sites included in this project [ 6 , 15 , 16 ]) were guided by the Integrated Promoting Action on Research Implementation in Health Services (i-PARIHS) framework [ 17 ] and i-PARIHS positions facilitation (the implementation strategy that our trial was testing) as the core ingredient that drives implementation [ 17 ], we selected i-PARIHS’ four domains—innovation, recipients, context, and facilitation—as relevant domains under which to examine factors influencing sustainability (step 3). i-PARIHS posits that the successful implementation of an innovation and its sustained use by recipients in a context is enabled by facilitation (both the individuals doing the facilitation and the process used for facilitation). We examined the data on both sustainability and potentially relevant i-PARIHS domains (step 4) by conducting directed content analysis [ 18 ] of the recorded and professionally transcribed interview data. We used the six CCM elements and the four i-PARIHS domains as a priori codes.

Additional file  2 provides an overview of data input, tasks performed, and analysis output for MMCS steps 5 through 9 described below. We assessed sustainability per site (step 5) by generating CCM code summaries per site, and reached a consensus on whether each site exhibited high, medium, or low sustainability relative to other sites based on the summary data. We assigned a higher sustainability level for sites that exhibited more CCM-aligned care processes, had more participants consistently mention those processes, and considered those processes more as “just the way things are done” at the site. Namely, (i) high sustainability sites had concrete examples of CCM-aligned care processes (such as the ones shown in Table  1 ) for many of the six CCM elements, which multiple participants mentioned as central to how they deliver care, (ii) low sustainability sites had only a few concrete examples of CCM-aligned care processes, mentioned by only a small subset of participants and/or inconsistently practiced, and (iii) medium sustainability sites matched neither of the high nor low sustainability cases, having several concrete examples of CCM-aligned care process for some of the CCM elements, varying in whether they are mentioned by multiple participants or how consistently they are a part of delivering care. For the CCM code summaries per site, one project team member initially reviewed the coded data to draft the summaries including exemplar quotes. Each summary and relevant exemplar quotes were then reviewed by and refined with input from all six project team members during recurring team meetings to finalize the high, medium, or low sustainability designation to use in the subsequent MMCS steps. Reviewing and refining the summaries for the nine sites took approximately four 60-min meetings of the six project team members, with each site’s CCM code summary taking approximately 20–35 min to discuss and reach consensus on. We referred to lists of specific examples of how the six core CCM elements were operationalized in our CCM implementation trial [ 19 , 20 ]. Refinements occurred mostly around familiarizing the newer members of the project team (i.e., those who had not participated in our prior CCM-related work) with the examples and definitions. We aligned to established qualitative analysis methods for consensus-reaching discussions [ 18 , 21 ]. Recognizing the common challenge faced by such discussions in adequately accounting for everyone’s interpretations of the data [ 22 ], we drew on Bens’ meeting facilitation techniques [ 23 ] that include setting ground rules, ensuring balanced participation from all project team members, and accurately recording decisions and action items.

We then identified influencing factors per site (step 6), by generating i-PARIHS code summaries per site and identifying distinct factors under each domain of i-PARIHS (e.g., Collaborativeness and teamwork as a factor under the Recipients domain). For the i-PARIHS code summaries per site, one project team member initially reviewed the coded data to draft the summaries including exemplar quotes. They elaborated on each i-PARIHS domain-specific summary by noting distinct factors that they deemed relevant to the summary, proposing descriptive wording to refer to each factor (e.g., “team members share a commitment to their patients” under the Recipients domain). Each summary, associated factor descriptions, and relevant exemplar quotes were then reviewed and refined with input from all six project team members during recurring team meetings to finalize the relevant factors to use in the subsequent MMCS steps. Finalizing the factors included deciding which similar proposed factor descriptions from different sites to consolidate into one factor and which wording to use to refer to the consolidated factor (e.g., “team members share a commitment to their patients,” “team members collaborate well,” and “team members know each other’s styles and what to expect” were consolidated into the Collaborativeness and teamwork factor under the Recipients domain). It took approximately four 60-min meetings of the six project team members to review and refine the summaries and factors for the nine sites, with each site’s i-PARIHS code summary and factors taking approximately 20–35 min to discuss and reach consensus on. We referred to lists of explicit definitions of i-PARIHS constructs that our team members had previously developed and published [ 16 , 24 ]. We once again aligned to established qualitative analysis methods for consensus-reaching discussions [ 18 , 21 ], drawing on Bens’ meeting facilitation techniques [ 23 ] to adequately account for everyone’s interpretations of the data [ 22 ].

We organized the examined data (i.e., the assessed sustainability and identified factors per site) into a sortable matrix (step 7) using Microsoft Excel [ 25 ], laid out by influencing factor (row), sustainability (column), and site (sheet). We conducted within-site analysis of the matrixed data (step 8), examining the data on each influencing factor and designating whether the factor (i) was present, somewhat present, or minimally present [based on aggregate reports from the site’s participants; used “minimally present” when, considering all available data from a site regarding a factor, the factor was predominantly weak (e.g., predominantly weak Ability to continue patient care during COVID at a medium sustainability site); used “somewhat present” when, considering all available data from a site regarding a factor, the factor was neither predominantly strong nor predominantly weak (e.g., neither predominantly strong nor predominantly weak Collaborativeness and teamwork at a low sustainability site)], and (ii) had an enabling, hindering, or neutral/unclear influence on sustainability (designated as “neutral” when, considering all available data from a site regarding a factor, the factor had neither a predominantly enabling nor a predominantly hindering influence on sustainability). These designations of factors’ presence and influence are conceptually representative of what is commonly referred to as magnitude and valence, respectively, by other efforts that construct scoring for qualitative data (e.g., [ 26 , 27 ]). Like the team-based consensus approach of earlier MMCS steps, factors’ presence and type of influence per site were initially proposed by one project team member after reviewing the matrix’s site-specific data, then refined with input from all project team members during recurring team meetings that reviewed the matrix. Accordingly, similar to the earlier MMCS steps, we aligned to established qualitative methods [ 18 , 21 ] and meeting facilitation techniques [ 23 ] for these consensus-reaching discussions.

We then conducted a cross-site analysis of the matrixed data (step 9), assessing whether factors and their combinations were (i) present across multiple sites, (ii) consistently associated with higher or lower sustainability, and (iii) emphasized at some sites more than others. We noted that any factor may have not come up during interviews with a site because either it is not pertinent or it is pertinent but still did not come up, although we asked an open-ended question at the end of each interview about whether there was anything else that the participant wanted to share regarding sustainability. To adequately account for these possibilities, we decided as a team to regard a factor or a combination of factors as being associated with high/medium/low sustainability if it was identified at a majority (i.e., even if not all) of the sites designated as high/medium/low sustainability (e.g., if the Collaborativeness and teamwork factor is identified at a majority, even if not all, of the high sustainability sites, we would find it to be associated with high sustainability). Like the team-based consensus approach of earlier MMCS steps, cross-site patterns were initially proposed by one project team member after reviewing the matrix’s cross-site data, then refined with input from all project team members during recurring team meetings that reviewed the matrix. Accordingly, similar to the earlier MMCS steps, we aligned to established qualitative methods [ 18 , 21 ] and meeting facilitation techniques [ 23 ] for these consensus-reaching discussions. We acknowledged the potential existence of additional factors influencing sustainability that may not have emerged during our interviews and also may vary substantially between sites. For example, adaptation of the CCM, characteristics of the patient population, and availability of continued funding, which are factors that extant literature reports as being relevant to sustainability [ 28 , 29 ], were not seen in our interview data. To maintain our analytic focus on the factors seen in our data, we did not add these factors to our analysis.

For the nine sites included in this project, we found the degree of CCM sustainability to be split evenly across the sites—three high-, three medium-, and three low-sustainability. Twenty-five total influencing factors were identified under the i-PARIHS domains of Innovation (6), Recipients (6), Context (8), and Facilitation (5). Table  2 shows these identified influencing factors by domain. Figure  1 shows 11 influencing factors that were identified for at least two sites within a group of high/medium/low sustainability sites—e.g., the factor “consistent and strong internal facilitator” is shown as being present at high sustainability sites with an enabling influence on sustainability, because it was identified as such at two or more of the high sustainability sites. Of these 11 influencing factors, four were identified only for sites with high CCM sustainability and two were identified only for sites with medium or low CCM sustainability.

figure 1

Influencing factors that were identified for at least two sites within a group of high/medium/low sustainability sites

Key trends in influencing factors associated with high, medium, and/or low CCM sustainability

Three factors across two i-PARIHS domains exhibited strong trends by sustainability status. They were the Collaborativeness and teamwork and Turnover of clinic staff and leadership factors under the Recipients domain, and the Having a consistent and strong internal facilitator factor under the Facilitation domain.

Recipients-related factors

Collaborativeness and teamwork was present with an enabling influence on CCM sustainability at most high and medium sustainability sites, while it was only somewhat present with a neutral influence on CCM sustainability at most low sustainability sites. When asked what had made their BHIP team work well, a participant from a high sustainability site said,

“Just a collaborative spirit.” (Participant 604)

A participant from a medium sustainability site said,

“We joke that [the BHIP teams] are even family, that the teams really do function pretty tightly and they each have their own personality.” (Participant 201)

At the low sustainability sites, willingness to work as a team varied across team members; a participant from a low sustainability site said,

“… I think it has to be the commitment of the people who are on the team. So those that are regularly attending, we get a lot more out of it than those that probably don't ever come [to team meetings].” (Participant 904)

Collaborativeness and teamwork of BHIP team members were often perceived as the highlight of pursuing interdisciplinary care.

Turnover of clinic staff and leadership was present with a hindering influence on CCM sustainability at most high, medium, and low sustainability sites.

“We’ve lost a lot of really, really good providers here in the time I’ve been here …,” (Participant 102)

said a participant from a low-sustainability site that had to reconfigure its BHIP teams due to clinic staff shortages. Turnover of mental health clinic leadership made it difficult to maintain CCM practices, especially beyond the teams that participated in the original CCM implementation trial. A participant from a medium sustainability site said,

“Probably about 90 percent of the things that we came up with have fallen by the wayside. Within our team, many of those remain but again, that hand off towards the other teams that I think partly is due to the turnover rate with program managers, supervisors, didn’t get fully implemented.” (Participant 703)

Although turnover was an issue for high sustainability sites as well, there was also indication of the situation improving in recent years; a participant from a high sustainability site said,

“… our attrition rollover rate has dropped quite a bit and I would really attribute that to [the CCM being] more functional and more sustainable and tolerable for the providers.” (Participant 502)

As such, staff and leadership turnover was deemed a major challenge for CCM sustainability for all sites regardless of the overall level of sustainability.

Facilitation-related factor

Having a consistent and strong internal facilitator was present with an enabling influence on CCM sustainability at high sustainability sites, not identified as an influencing factor at most of the medium sustainability sites, and variably present with a hindering, neutral, or unclear influence on CCM sustainability at low sustainability sites. Participants from a high sustainability site perceived that it was important for the internal facilitator to understand different BHIP team members’ personalities and know the clinic’s history. A participant from another high sustainability site shared that, as an internal facilitator themselves, they focused on recognizing and reinforcing the progress of team members:

“… I'm often the person who kind of [starts] off with, ‘Hey, look at what we've done in this location,’ ‘Hey look at what the team's done this month.’” (Participant 402)

A participant from a low sustainability site had also served as an internal facilitator and recounted the difficulty and importance of readying the BHIP team to function in the long run without their assistance:

“I should have been able to get out sooner, I think, to get it to have them running this themselves. And that was just a really difficult process.” (Participant 301)

Participants, especially from the high and low sustainability sites, attributed their BHIP teams’ successes and challenges to the skills of the internal facilitator.

Influencing factors identified only for sites with high CCM sustainability

Four factors across four i-PARIHS domains were identified for high sustainability sites and not for medium or low sustainability sites. They were the factors Details about the CCM being well understood (Innovation domain), Interdisciplinary coordination (Recipients domain), Having adequate clinic space for CCM team members (Context domain), and Having a knowledgeable and helpful external facilitator (Facilitation domain).

Innovation-related factor

Details about the CCM being well understood was minimal to somewhat present with an unclear influence on CCM sustainability.

“We’ve … been trying to help our providers see the benefit of team-based care and the episodes-of-care idea, and I would say that is something our folks really have continued to struggle with as well,” (Participant 401)

said a participant from a high sustainability site. “What is considered CCM-based care?” continued to be a question on providers’ minds. A participant from a high sustainability site asked during the interview,

“Is there kind of a clearing house of some of the best practices for [CCM] that you guys have … or some other collection of resources that we could draw from?” (Participant 601)

Although such references are indeed accessible online organization-wide, participants were not always aware of those resources or what exactly CCM entails.

Recipients-related factor

Interdisciplinary coordination was somewhat present with a hindering, neutral, or unclear influence on CCM sustainability. Coordination between psychotherapy and psychiatry providers was deemed difficult by participants from high-sustainability sites. A participant said,

“We were initially kind of top heavy on the psychiatry so just making sure we have … therapy staff balancing that out [has been important].” (Participant 501)

Another participant perceived that BHIP teams were helpful in managing.

… ‘sibling rivalry’ between different disciplines … because [CCM] puts us all in one team and we communicate.” (Participant 505)

Interdisciplinary coordination was understood by the participants as being necessary for effective CCM-based care yet difficult to achieve.

Context-related factor

Having adequate clinic space for CCM team members was minimal to somewhat present with a hindering, neutral, or unclear influence on CCM sustainability. COVID-19 led to changes in how clinic space was used/assigned. A participant from a high sustainability site remarked,

“Pre-COVID everything was in a room instead of online. And now all our meetings are online and so it's actually really easy for the supervisors to be able to rotate through them and then, you know, they can answer programmatic questions ….” (Participant 402)

Participants from another high sustainability site found that issues regarding limited clinic space were both exacerbated and alleviated by COVID, with the mental health service losing space to vaccine clinics but more mental health clinicians teleworking and in less need of clinic space. Virtual connections were seen to alleviate some physical workspace-related concerns.

Having a knowledgeable and helpful external facilitator was variably present; when present, it had an enabling influence on CCM sustainability. Participants from a high sustainability site noted how many of the external facilitator’s efforts to change the BHIP team’s work processes very much remained over time. An example of a change was to have team meetings be structured to meet evolving patient needs. Team members came to meetings with the shared knowledge and expectation that,

“… we need to touch on folks who are coming out of the hospital, we need to touch on folks with higher acuity needs.” (Participant 402)

Implementation support that sites received from their external facilitator mostly occurred during the time period of the original CCM implementation trial; correspondence with the external facilitator after that trial time period was not common for sites. Participants still largely found the external facilitator to provide helpful guidance and advice on delivering CCM-based care.

Influencing factors identified only for sites with medium or low CCM sustainability

Two factors were identified for medium or low sustainability sites and not for high sustainability sites. They were the factors Ability to continue patient care during COVID and Adequate resources/capacity for care delivery . These factors were both under i-PARIHS’ Context domain, unlike the influencing factors above that were identified only for high sustainability sites, which spanned all four i-PARIHS domains.

Context-related factors

Ability to continue patient care during COVID had a hindering influence on CCM sustainability when minimally present. Participants felt that their CCM work was challenged when delivering care through telehealth was made difficult—e.g., at a medium sustainability site, site policies during the pandemic required a higher number of in-person services than the BHIP team providers expected or desired to deliver. On the other hand, this factor had an enabling influence on CCM sustainability when present. A participant at a low sustainability site mentioned the effect of telehealth on being able to follow up more easily with patients who did not show up for their appointments:

“… my no-show rate has dropped dramatically because if people don’t log on after a couple minutes, I call them. They're like ‘oh, I forgot, let me pop right on,’ whereas, you know, in the face-to-face space, you know, you wait 15 minutes, you call them, it’s too late for them to come in so then they're no shows.” (Participant 102)

The advantages of virtual care delivery, as well as the challenges of getting approvals to pursue it to varying extents, were well recognized by the participants.

Adequate resources/capacity for care delivery was minimally present at medium sustainability sites with a hindering influence on CCM sustainability. At a medium sustainability site, although leadership was supportive of CCM, resources were being used to keep clinics operational (especially during COVID) rather than investing in building new CCM-based care delivery processes.

“I think that if my boss came to me, [and asked] what could I do for [the clinics] … I would say even more staff,” (Participant 202)

said a participant from a medium sustainability site. At the same time, the participant, as many others we interviewed, understood and emphasized the need for BHIP teams to proceed with care delivery even when resources were limited:

“… when you’re already dealing with a very busy clinic, short staff and then you’re hit with a pandemic you handle it the best that you can.” (Participant 202)

Participants felt the need for basic resource requirements to be met in order for CCM-based care to be feasible.

In this project, we examined factors influencing the sustainability of CCM-aligned care practices at general mental health clinics within nine VA medical centers that previously participated in a CCM implementation trial. Guided by the core CCM elements and i-PARIHS domains, we conducted and analyzed CCM provider interviews. Using MMCS, we found CCM sustainability to be split evenly across the nine sites (three high, three medium, and three low), and that sustainability may be related most strongly to provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators.

In comparison to most high sustainability sites, participants from most medium or low sustainability sites did not mention a knowledgeable and helpful external facilitator who enabled sustainability. Participants at the high sustainability sites also emphasized the need for clarity about what CCM-based care comprises, interdisciplinary coordination in delivering CCM-aligned care, and adequate clinic space for BHIP team members to connect and collaborate. In contrast, in comparison to participants at most high sustainability sites, participants at most medium or low sustainability sites emphasized the need for better continuity of patient-facing activities during the COVID-19 pandemic and more resources/capacity for care delivery. A notable difference between these two groups of influencing factors is that the ones emphasized at most high sustainability sites are more CCM-specific (e.g., external facilitator with CCM expertise, knowledge, and structures to support delivery of CCM-aligned care), while the ones emphasized at most medium or low sustainability sites are factors that certainly relate to CCM sustainability but are focused on care delivery operations beyond CCM-aligned care (e.g., COVID’s widespread impacts, limited staff availability). In short, an emphasis on immediate, short-term clinical needs in the face of the COVID-19 pandemic and staffing challenges appeared to sap sites’ enthusiasm for sustaining more collaborative, CCM-consistent care processes.

Our previous qualitative analysis of these interview data suggested that in order to achieve sustainability, it is important to establish appropriate infrastructure, organizational readiness, and mental health service- or department-wide coordination for CCM implementation [ 10 ]. The findings from the current project augment these previous findings by highlighting the specific factors associated with higher and lower CCM sustainability across the project sites. This additional knowledge provides two important insights into what CCM implementation efforts should prioritize with regard to the previously recommended appropriate infrastructure, readiness, and coordination. First, for knowledge retention and coordination during personnel changes (including any changes in internal facilitators through and following implementation), care processes and their specific procedures should be established and documented in order to bring new personnel up to speed on those care processes. Management sciences, as applied to health care and other fields, suggest that such organizational knowledge retention can be maximized when there are (i) structures set up to formally recognize/praise staff when they share key knowledge, (ii) succession plans to be applied in the event of staff turnover, (iii) opportunities for mentoring and shadowing, and (iv) after action reviews of conducted care processes, which allow staff to learn about and shape the processes themselves [ 30 , 31 , 32 , 33 ]. Future CCM implementation efforts may thus benefit from enacting these suggestions alongside establishing and documenting CCM-based care processes and associated procedures.

Second, efforts to implement CCM-aligned practices into routine care should account for the extent to which sites’ more fundamental operational needs are met or being addressed. That information can be used to appropriately scope the plan, expectations, and timeline for implementation. For instance, ongoing critical staffing shortages or high turnover [ 34 ] at a site are unlikely to be resolved through a few months of CCM implementation. In fact, in that situation, it is possible that CCM implementation efforts could lead to reduced team effectiveness in the short term, given the effort required to establish more collaborative and coordinated care processes [ 35 ]. Should CCM implementation move forward at a given site, implementation goals ought to be set on making progress in realms that are within the implementation effort’s control (e.g., designing CCM-aligned practices that take staffing challenges into consideration) [ 36 , 37 ] rather than on factors outside of the effort’s control (e.g., staffing shortages). As healthcare systems determine how to deploy support (e.g., facilitators) to sites for CCM implementation, they would benefit from considering whether it is primarily CCM expertise that the site needs at the moment, or more foundational organizational resources (e.g., mental health staffing, clinical space, leadership enhancement) [ 38 ] to first reach an operational state that can most benefit from CCM implementation efforts at a later point in time. There is growing consensus across the field that the readiness of a healthcare organization to innovate is a prerequisite to successful innovation (e.g., CCM implementation) regardless of the specific innovation [ 39 , 40 ]. Several promising strategies specifically target these organizational considerations for implementing evidence-based practices (e.g., [ 41 , 42 ]). Further, recent works have begun to more clearly delineate leadership-related, climate-related, and other contextual factors that contribute to organizations’ innovation readiness [ 43 ], which can inform healthcare systems’ future decisions regarding preparatory work leading to, and timing of, CCM implementation at their sites.

These considerations informed by MMCS may have useful implications for implementation strategy selection and tailoring for future CCM implementation efforts, especially in delineating the target level (e.g., system, organizational, clinic, individual) and timeline of implementation strategies to be deployed. For instance, of the three factors found to most notably trend with CCM sustainability, Collaborativeness and teamwork may be strengthened through shorter-term team-building interventions at the organizational and/or clinic levels [ 38 ], Turnover of clinic staff and leadership may be mitigated by aiming for longer-term culture/climate change at the system and/or organizational levels [ 44 , 45 , 46 ], and Having a consistent and strong internal facilitator may be ensured more immediately by selecting an individual with fitting expertise/characteristics to serve in the role [ 15 ] and imparting innovation/facilitation knowledge to them [ 47 ]. Which of these factors to focus on, and through what specific strategies, can be decided in partnership with an implementation site—for instance, candidate strategies can be identified based on ones that literature points to for addressing these factors [ 48 ], systematic selection of the strategies to move forward can happen with close input from site personnel [ 49 ], and explicit further specification of those strategies [ 50 ] can also happen in collaboration with site personnel to amply account for site-specific contexts [ 51 ].

As is common for implementation projects, the findings of this project are highly context-dependent. It involves the implementation of a specific evidence-based practice (the CCM) using a specific implementation strategy (implementation facilitation) at specific sites (BHIP teams within general mental health clinics at nine VA medical centers). For such context-dependent findings to be transferable [ 52 , 53 ] to meaningfully inform future implementation efforts, sources of variation in the findings and how the findings were reached must be documented and traceable. This means being explicit about each step and decision that led up to cross-site analysis, as MMCS encourages, so that future implementation efforts can accurately view and consider why and how findings might be transferable to their own work. For instance, beyond the finding that Turnover of clinic staff and leadership was a factor present at most of the examined sites, MMCS’ traceable documentation of qualitative data associated with this factor at high sustainability sites also allowed highlighting the perception that CCM implementation is contributing to mitigating turnover of providers in the clinic over time, which may be a crucial piece of information that fuels future CCM implementation efforts.

Furthermore, to compare findings and interpretations across projects, consistent procedures for setting up and conducting these multi-site investigations are indispensable [ 54 , 55 , 56 ]. Although many projects involve multiple sites and assess variations across the sites, it is less common to have clearly delineated protocols for conducting such assessments. MMCS is meant to target this very gap, by offering a formalized sequence of steps that prompt specification of analytical procedures and decisions that are often interpretive and left less specified. MMCS uses a concrete data structure (the matrix) to traceably organize information and knowledge gained from a project, and the matrix can accommodate various data sources and conceptual groundings (e.g., guiding theories, models, and frameworks) that may differ from project to project – for instance, although our application of MMCS aligned to i-PARIHS, other projects applying MMCS [ 2 , 5 ] use different conceptual guides (e.g., Consolidated Framework for Implementation Research [ 57 ], Theoretical Domains Framework [ 58 ]). Therefore, as more projects align to the MMCS steps [ 1 ] to identify factors related to implementation and sustainability, better comparisons, consolidations, and transfers of knowledge between projects may become possible.

This project has several limitations. First, the high, medium, and low sustainability assigned to the sites were based on the sites’ CCM sustainability relative to one another, rather than based on an external metric of sustainability. As measures of sustainability such as the Program Sustainability Assessment Tool [ 59 , 60 ] and the Sustainment Measurement System Scale [ 61 ] become increasingly developed and tested, future projects may consider the feasibility of incorporating such measures to assess each site’s sustainability. In our case, we worked on addressing this limitation by using a consensus approach within our project team to assign sustainability levels to sites, as well as by confirming that the sites that we designated as high sustainability exhibited CCM elements that we had previously observed at the end of their participation in the original CCM implementation trial [ 19 ]. Second, we did not assign strict thresholds above/below which the counts or proportions of data regarding a factor would automatically indicate whether the factor (i) was present, somewhat present, or minimally present and (ii) had an enabling, hindering, or neutral/unclear influence on sustainability. This follows widely accepted qualitative analytical guidance that discourages characterizing findings solely based on the frequency with which a notion is mentioned by participants [ 62 , 63 , 64 ], in order to prevent unsubstantiated inferences or conclusions. We sought to address this limitation in two ways: We carefully documented the project team’s rationale for each consensus reached, and we reviewed all consensuses reached in their entirety to ensure that any two factors with the same designation (e.g., “minimally present”) do not have associated rationale that conflict across those factors. These endeavors we undertook closely adhere to established case study research methods [ 65 ], which MMCS builds on, that emphasize strengthening the validity and reliability of findings through documenting a detailed analytic protocol, as well as reviewing data to ensure that patterns match across analytic units (e.g., factors, interviewees, sites). Third, our findings are based on three sites each for high/medium/low sustainability, and although we identified single factors associated with sustainability, we found no specific combinations of factors’ presence and influence that were repeatedly existent at a majority of the sites designated as high/medium/low sustainability. Examining additional sites on the factors identified through this work (as we will for our subsequent CCM implementation trial described below) will allow more opportunities for repeated combinations and other factors to emerge, making possible firmer conclusions regarding the extent to which the currently identified factors and absence of identified combinations are applicable beyond the sites included in this study. Fourth, the identified influencing factor “leadership support for CCM” (under the Context domain of the i-PARIHS framework) substantially overlaps in concept with the core “organizational/leadership support” element of the CCM. To avoid circular reasoning, we used leadership support-related data to inform our assignment of sites’ high, medium, or low CCM sustainability, rather than as a reason for the sites’ CCM sustainability. In reality, strong leadership support may both result from and contribute to implementation and sustainability [ 16 , 66 ], and thus causal relationships between the i-PARIHS-aligned influencing factors and the CCM elements (possibly with feedback loops) warrant further examination to most appropriately use leadership support-related data in future analyses of CCM sustainability. Fifth, findings may be subject to both social desirability bias in participants providing more positive than negative evidence of sustainability (especially participants who are responsible for implementing and sustaining CCM-aligned care at their site) and the project team members’ bias in interpreting the findings to align to their expectations of further effort being necessary to sustainably implement the CCM. To help mitigate this challenge, the project interviewers strove to elicit from participants both positive and negative perceptions and experiences related to CCM-based care delivery, both of which were present in the examined interview data.

Future work stemming from this project is twofold. Regarding CCM implementation, we will conduct a subsequent CCM implementation trial involving eight new sites to prospectively examine how implementation facilitation with an enhanced focus on these findings affects CCM sustainability. We started planning for sustainability prior to implementation, looking to this work for indicators of specific modifications needed to the previous way in which we used implementation facilitation to promote the uptake of CCM-based care [ 67 ]. Findings from this work suggest that sustainability may be related most strongly to (i) provider collaboration, (ii) knowledge retention during staff/leadership transitions, and (iii) availability of skilled internal facilitators. Hence, we will accordingly prioritize developing procedures for (i) regular CCM-related information exchange amongst BHIP team members, as well as between the BHIP team and clinic leadership, (ii) both translating knowledge to and keeping knowledge documented at the site, and (iii) supporting the sites’ own personnel to take the lead in driving CCM implementation.

Regarding MMCS, we will continuously refine and improve the method by learning from other projects applying, testing, and critiquing MMCS. Outside of our CCM-related projects, examinations of implementation data using MMCS are actively underway for various implementation efforts including that of a data dashboard for decision support on transitioning psychiatrically stable patients from specialty mental health to primary care [ 2 ], a peer-led healthy lifestyle intervention for individuals with serious mental illness [ 3 ], screening programs for intimate partner violence [ 4 ], and a policy- and organization-based health system strengthening intervention to improve health systems in sub-Saharan Africa [ 5 ]. As MMCS is used by more projects that differ from one another in their specific outcome of interest, and especially in light of our MMCS application that examines factors related to sustainability, we are curious whether certain proximal to distal outcomes are more subject to heterogeneity in influencing factors than other outcomes. For instance, sustainability outcomes, which are tracked following a longer passage of time than some other outcomes, may be subject to more contextual variations that occur over time and thus could particularly benefit from being examined using MMCS. We will also explore MMCS’ complementarity with coincidence analysis and other configurational analytical approaches [ 68 ] for examining implementation phenomena. We are excited about both the step-by-step traceability that MMCS can bring to such methods and those methods’ computational algorithms that can be beneficial to incorporate into MMCS for projects with larger numbers of sites. For example, Salvati and colleagues [ 69 ] described both the inspiration that MMCS provided in structuring their data as well as how they addressed MMCS’ visualization shortcomings through their innovative data matrix heat mapping, which led to their selection of specific factors to include in their subsequent coincidence analysis. Coincidence analysis is an enhancement to qualitative comparative analysis and other configurational analytical methods, in that it is formulated specifically for causal inference [ 70 ]. Thus, in considering improved reformulations of MMCS’ steps to better characterize examined factors as explicit causes to the outcomes of interest, we are inspired by and can draw on coincidence analysis’ approach to building and evaluating causal chains that link factors to outcomes. Relatedly, we have begun to actively consider the potential contribution that MMCS can make to hypothesis generation and theory development for implementation science. As efforts to understand the mechanisms through which implementation strategies work are gaining momentum [ 71 , 72 , 73 ], there is an increased need for methods that help decompose our understanding of factors that influence the mechanistic pathways from strategies to outcomes [ 74 ]. Implementation science is facing the need to develop theories, beyond frameworks, which delineate hypotheses for observed implementation phenomena that can be subsequently tested [ 75 ]. The methodical approach that MMCS offers can aid this important endeavor, by enabling data curation and examination of pertinent factors in a consistent way that allows meaningful synthesis of findings across sites and studies. We see these future directions as concrete steps toward elucidating the factors related to sustainable implementation of EBPs, especially leveraging data from projects where the number of sites is much smaller than the number of factors that may matter—which is indeed the case for most implementation projects.

Using MMCS, we found that provider collaboration, knowledge retention during staff/leadership transitions, and availability of skilled internal facilitators may be most strongly related to CCM sustainability in VA outpatient mental health clinics. Informed by these findings, we have a subsequent CCM implementation trial underway to prospectively test whether increasing the aforementioned factors within implementation facilitation enhances sustainability. The MMCS steps used here for systematic multi-site examination can also be applied to determining sustainability-related factors relevant to various other EBPs and implementation contexts.

Availability of data and materials

The data analyzed during the current project are not publicly available because participant privacy could be compromised.

Abbreviations

Behavioral Health Interdisciplinary Program

Collaborative Chronic Care Model

Consolidated Criteria for Reporting Qualitative Research

coronavirus disease

evidence-based practice

Institutional Review Board

Integrated Promoting Action on Research Implementation in Health Services

Matrixed Multiple Case Study

United States Department of Veterans Affairs

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Acknowledgements

The authors sincerely thank the project participants for their time, as well as the project team members for their guidance and support. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

This project was funded by VA grant QUE 20–026 and was designed and conducted in partnership with the VA Office of Mental Health and Suicide Prevention.

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Bo Kim, Madisen E. Brown, Samantha L. Connolly, Elizabeth G. Spitzer, Hannah M. Bailey & Christopher J. Miller

Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA

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Center of Innovation in Long Term Services and Supports (LTSS COIN), VA Providence Healthcare System, 385 Niagara Street, Providence, RI, 02907, USA

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Brown University School of Public Health, 121 South Main Street, Providence, RI, 02903, USA

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Contributions

Concept and design: BK, JS, and CM. Acquisition, analysis, and/or interpretation of data: BK, JS, MB, SC, ES, and CM. Initial drafting of the manuscript: BK. Critical revisions of the manuscript for important intellectual content: JS, MB, SC, ES, HB, LS, KW, and CM. All the authors read and approved the final manuscript.

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Correspondence to Bo Kim .

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This project was determined to be non-research by the VA Boston Research and Development Service, and therefore did not require oversight by the Institutional Review Board (IRB).

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Supplementary Information

Additional file 1..

COREQ (COnsolidated criteria for REporting Qualitative research) Checklist.

Additional file 2.

Data input, tasks performed, and analysis output for MMCS Steps 5 through 9.

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Kim, B., Sullivan, J.L., Brown, M.E. et al. Sustaining the collaborative chronic care model in outpatient mental health: a matrixed multiple case study. Implementation Sci 19 , 16 (2024). https://doi.org/10.1186/s13012-024-01342-2

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DOI : https://doi.org/10.1186/s13012-024-01342-2

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Reproductive rights in America

Research at the heart of a federal case against the abortion pill has been retracted.

Selena Simmons-Duffin

Selena Simmons-Duffin

articles about case study

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy. Anna Moneymaker/Getty Images hide caption

The Supreme Court will hear the case against the abortion pill mifepristone on March 26. It's part of a two-drug regimen with misoprostol for abortions in the first 10 weeks of pregnancy.

A scientific paper that raised concerns about the safety of the abortion pill mifepristone was retracted by its publisher this week. The study was cited three times by a federal judge who ruled against mifepristone last spring. That case, which could limit access to mifepristone throughout the country, will soon be heard in the Supreme Court.

The now retracted study used Medicaid claims data to track E.R. visits by patients in the month after having an abortion. The study found a much higher rate of complications than similar studies that have examined abortion safety.

Sage, the publisher of the journal, retracted the study on Monday along with two other papers, explaining in a statement that "expert reviewers found that the studies demonstrate a lack of scientific rigor that invalidates or renders unreliable the authors' conclusions."

It also noted that most of the authors on the paper worked for the Charlotte Lozier Institute, the research arm of anti-abortion lobbying group Susan B. Anthony Pro-Life America, and that one of the original peer reviewers had also worked for the Lozier Institute.

The Sage journal, Health Services Research and Managerial Epidemiology , published all three research articles, which are still available online along with the retraction notice. In an email to NPR, a spokesperson for Sage wrote that the process leading to the retractions "was thorough, fair, and careful."

The lead author on the paper, James Studnicki, fiercely defends his work. "Sage is targeting us because we have been successful for a long period of time," he says on a video posted online this week . He asserts that the retraction has "nothing to do with real science and has everything to do with a political assassination of science."

He says that because the study's findings have been cited in legal cases like the one challenging the abortion pill, "we have become visible – people are quoting us. And for that reason, we are dangerous, and for that reason, they want to cancel our work," Studnicki says in the video.

In an email to NPR, a spokesperson for the Charlotte Lozier Institute said that they "will be taking appropriate legal action."

Role in abortion pill legal case

Anti-abortion rights groups, including a group of doctors, sued the federal Food and Drug Administration in 2022 over the approval of mifepristone, which is part of a two-drug regimen used in most medication abortions. The pill has been on the market for over 20 years, and is used in more than half abortions nationally. The FDA stands by its research that finds adverse events from mifepristone are extremely rare.

Judge Matthew Kacsmaryk, the district court judge who initially ruled on the case, pointed to the now-retracted study to support the idea that the anti-abortion rights physicians suing the FDA had the right to do so. "The associations' members have standing because they allege adverse events from chemical abortion drugs can overwhelm the medical system and place 'enormous pressure and stress' on doctors during emergencies and complications," he wrote in his decision, citing Studnicki. He ruled that mifepristone should be pulled from the market nationwide, although his decision never took effect.

articles about case study

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017. AP hide caption

Matthew Kacsmaryk at his confirmation hearing for the federal bench in 2017.

Kacsmaryk is a Trump appointee who was a vocal abortion opponent before becoming a federal judge.

"I don't think he would view the retraction as delegitimizing the research," says Mary Ziegler , a law professor and expert on the legal history of abortion at U.C. Davis. "There's been so much polarization about what the reality of abortion is on the right that I'm not sure how much a retraction would affect his reasoning."

Ziegler also doubts the retractions will alter much in the Supreme Court case, given its conservative majority. "We've already seen, when it comes to abortion, that the court has a propensity to look at the views of experts that support the results it wants," she says. The decision that overturned Roe v. Wade is an example, she says. "The majority [opinion] relied pretty much exclusively on scholars with some ties to pro-life activism and didn't really cite anybody else even or really even acknowledge that there was a majority scholarly position or even that there was meaningful disagreement on the subject."

In the mifepristone case, "there's a lot of supposition and speculation" in the argument about who has standing to sue, she explains. "There's a probability that people will take mifepristone and then there's a probability that they'll get complications and then there's a probability that they'll get treatment in the E.R. and then there's a probability that they'll encounter physicians with certain objections to mifepristone. So the question is, if this [retraction] knocks out one leg of the stool, does that somehow affect how the court is going to view standing? I imagine not."

It's impossible to know who will win the Supreme Court case, but Ziegler thinks that this retraction probably won't sway the outcome either way. "If the court is skeptical of standing because of all these aforementioned weaknesses, this is just more fuel to that fire," she says. "It's not as if this were an airtight case for standing and this was a potentially game-changing development."

Oral arguments for the case, Alliance for Hippocratic Medicine v. FDA , are scheduled for March 26 at the Supreme Court. A decision is expected by summer. Mifepristone remains available while the legal process continues.

  • Abortion policy
  • abortion pill
  • judge matthew kacsmaryk
  • mifepristone
  • retractions
  • Abortion rights
  • Supreme Court

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  • v.52(4); 2008 Dec

Guidelines to the writing of case studies

Dr. brian budgell.

* Département chiropratique, Université du Québec à Trois-Rivières, 3351, boul des Forges, Trois-Rivières, Qc, Canada G9A 5H7

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Dr. Brian Budgell, DC, PhD, JCCA Editorial Board

  • Introduction

Case studies are an invaluable record of the clinical practices of a profession. While case studies cannot provide specific guidance for the management of successive patients, they are a record of clinical interactions which help us to frame questions for more rigorously designed clinical studies. Case studies also provide valuable teaching material, demonstrating both classical and unusual presentations which may confront the practitioner. Quite obviously, since the overwhelming majority of clinical interactions occur in the field, not in teaching or research facilities, it falls to the field practitioner to record and pass on their experiences. However, field practitioners generally are not well-practised in writing for publication, and so may hesitate to embark on the task of carrying a case study to publication. These guidelines are intended to assist the relatively novice writer – practitioner or student – in efficiently navigating the relatively easy course to publication of a quality case study. Guidelines are not intended to be proscriptive, and so throughout this document we advise what authors “may” or “should” do, rather than what they “must” do. Authors may decide that the particular circumstances of their case study justify digression from our recommendations.

Additional and useful resources for chiropractic case studies include:

  • Waalen JK. Single subject research designs. J Can Chirop Assoc 1991; 35(2):95–97.
  • Gleberzon BJ. A peer-reviewer’s plea. J Can Chirop Assoc 2006; 50(2):107.
  • Merritt L. Case reports: an important contribution to chiropractic literature. J Can Chiropr Assoc 2007; 51(2):72–74.

Portions of these guidelines were derived from Budgell B. Writing a biomedical research paper. Tokyo: Springer Japan KK, 2008.

General Instructions

This set of guidelines provides both instructions and a template for the writing of case reports for publication. You might want to skip forward and take a quick look at the template now, as we will be using it as the basis for your own case study later on. While the guidelines and template contain much detail, your finished case study should be only 500 to 1,500 words in length. Therefore, you will need to write efficiently and avoid unnecessarily flowery language.

These guidelines for the writing of case studies are designed to be consistent with the “Uniform Requirements for Manuscripts Submitted to Biomedical Journals” referenced elsewhere in the JCCA instructions to authors.

After this brief introduction, the guidelines below will follow the headings of our template. Hence, it is possible to work section by section through the template to quickly produce a first draft of your study. To begin with, however, you must have a clear sense of the value of the study which you wish to describe. Therefore, before beginning to write the study itself, you should gather all of the materials relevant to the case – clinical notes, lab reports, x-rays etc. – and form a clear picture of the story that you wish to share with your profession. At the most superficial level, you may want to ask yourself “What is interesting about this case?” Keep your answer in mind as your write, because sometimes we become lost in our writing and forget the message that we want to convey.

Another important general rule for writing case studies is to stick to the facts. A case study should be a fairly modest description of what actually happened. Speculation about underlying mechanisms of the disease process or treatment should be restrained. Field practitioners and students are seldom well-prepared to discuss physiology or pathology. This is best left to experts in those fields. The thing of greatest value that you can provide to your colleagues is an honest record of clinical events.

Finally, remember that a case study is primarily a chronicle of a patient’s progress, not a story about chiropractic. Editorial or promotional remarks do not belong in a case study, no matter how great our enthusiasm. It is best to simply tell the story and let the outcome speak for itself. With these points in mind, let’s begin the process of writing the case study:

  • Title: The title page will contain the full title of the article. Remember that many people may find our article by searching on the internet. They may have to decide, just by looking at the title, whether or not they want to access the full article. A title which is vague or non-specific may not attract their attention. Thus, our title should contain the phrase “case study,” “case report” or “case series” as is appropriate to the contents. The two most common formats of titles are nominal and compound. A nominal title is a single phrase, for example “A case study of hypertension which responded to spinal manipulation.” A compound title consists of two phrases in succession, for example “Response of hypertension to spinal manipulation: a case study.” Keep in mind that titles of articles in leading journals average between 8 and 9 words in length.
  • Other contents for the title page should be as in the general JCCA instructions to authors. Remember that for a case study, we would not expect to have more than one or two authors. In order to be listed as an author, a person must have an intellectual stake in the writing – at the very least they must be able to explain and even defend the article. Someone who has only provided technical assistance, as valuable as that may be, may be acknowledged at the end of the article, but would not be listed as an author. Contact information – either home or institutional – should be provided for each author along with the authors’ academic qualifications. If there is more than one author, one author must be identified as the corresponding author – the person whom people should contact if they have questions or comments about the study.
  • Key words: Provide key words under which the article will be listed. These are the words which would be used when searching for the article using a search engine such as Medline. When practical, we should choose key words from a standard list of keywords, such as MeSH (Medical subject headings). A copy of MeSH is available in most libraries. If we can’t access a copy and we want to make sure that our keywords are included in the MeSH library, we can visit this address: http://www.ncbi.nlm.nih.gov:80/entrez/meshbrowser.cgi

A narrative abstract consists of a short version of the whole paper. There are no headings within the narrative abstract. The author simply tries to summarize the paper into a story which flows logically.

A structured abstract uses subheadings. Structured abstracts are becoming more popular for basic scientific and clinical studies, since they standardize the abstract and ensure that certain information is included. This is very useful for readers who search for articles on the internet. Often the abstract is displayed by a search engine, and on the basis of the abstract the reader will decide whether or not to download the full article (which may require payment of a fee). With a structured abstract, the reader is more likely to be given the information which they need to decide whether to go on to the full article, and so this style is encouraged. The JCCA recommends the use of structured abstracts for case studies.

Since they are summaries, both narrative and structured abstracts are easier to write once we have finished the rest of the article. We include a template for a structured abstract and encourage authors to make use of it. Our sub-headings will be:

  • Introduction: This consists of one or two sentences to describe the context of the case and summarize the entire article.
  • Case presentation: Several sentences describe the history and results of any examinations performed. The working diagnosis and management of the case are described.
  • Management and Outcome: Simply describe the course of the patient’s complaint. Where possible, make reference to any outcome measures which you used to objectively demonstrate how the patient’s condition evolved through the course of management.
  • Discussion: Synthesize the foregoing subsections and explain both correlations and apparent inconsistencies. If appropriate to the case, within one or two sentences describe the lessons to be learned.
  • Introduction: At the beginning of these guidelines we suggested that we need to have a clear idea of what is particularly interesting about the case we want to describe. The introduction is where we convey this to the reader. It is useful to begin by placing the study in a historical or social context. If similar cases have been reported previously, we describe them briefly. If there is something especially challenging about the diagnosis or management of the condition that we are describing, now is our chance to bring that out. Each time we refer to a previous study, we cite the reference (usually at the end of the sentence). Our introduction doesn’t need to be more than a few paragraphs long, and our objective is to have the reader understand clearly, but in a general sense, why it is useful for them to be reading about this case.

The next step is to describe the results of our clinical examination. Again, we should write in an efficient narrative style, restricting ourselves to the relevant information. It is not necessary to include every detail in our clinical notes.

If we are using a named orthopedic or neurological test, it is best to both name and describe the test (since some people may know the test by a different name). Also, we should describe the actual results, since not all readers will have the same understanding of what constitutes a “positive” or “negative” result.

X-rays or other images are only helpful if they are clear enough to be easily reproduced and if they are accompanied by a legend. Be sure that any information that might identify a patient is removed before the image is submitted.

At this point, or at the beginning of the next section, we will want to present our working diagnosis or clinical impression of the patient.

It is useful for the reader to know how long the patient was under care and how many times they were treated. Additionally, we should be as specific as possible in describing the treatment that we used. It does not help the reader to simply say that the patient received “chiropractic care.” Exactly what treatment did we use? If we used spinal manipulation, it is best to name the technique, if a common name exists, and also to describe the manipulation. Remember that our case study may be read by people who are not familiar with spinal manipulation, and, even within chiropractic circles, nomenclature for technique is not well standardized.

We may want to include the patient’s own reports of improvement or worsening. However, whenever possible we should try to use a well-validated method of measuring their improvement. For case studies, it may be possible to use data from visual analogue scales (VAS) for pain, or a journal of medication usage.

It is useful to include in this section an indication of how and why treatment finished. Did we decide to terminate care, and if so, why? Did the patient withdraw from care or did we refer them to another practitioner?

  • Discussion: In this section we may want to identify any questions that the case raises. It is not our duty to provide a complete physiological explanation for everything that we observed. This is usually impossible. Nor should we feel obligated to list or generate all of the possible hypotheses that might explain the course of the patient’s condition. If there is a well established item of physiology or pathology which illuminates the case, we certainly include it, but remember that we are writing what is primarily a clinical chronicle, not a basic scientific paper. Finally, we summarize the lessons learned from this case.
  • Acknowledgments: If someone provided assistance with the preparation of the case study, we thank them briefly. It is neither necessary nor conventional to thank the patient (although we appreciate what they have taught us). It would generally be regarded as excessive and inappropriate to thank others, such as teachers or colleagues who did not directly participate in preparation of the paper.

A popular search engine for English-language references is Medline: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi

  • Legends: If we used any tables, figures or photographs, they should be accompanied by a succinct explanation. A good rule for graphs is that they should contain sufficient information to be generally decipherable without reference to a legend.
  • Tables, figures and photographs should be included at the end of the manuscript.
  • Permissions: If any tables, figures or photographs, or substantial quotations, have been borrowed from other publications, we must include a letter of permission from the publisher. Also, if we use any photographs which might identify a patient, we will need their written permission.

In addition, patient consent to publish the case report is also required.

Running Header:

  • Name, academic degrees and affiliation

Name, address and telephone number of corresponding author

Disclaimers

Statement that patient consent was obtained

Sources of financial support, if any

Key words: (limit of five)

Abstract: (maximum of 150 words)

  • Case Presentation
  • Management and Outcome

Introduction:

Provide a context for the case and describe any similar cases previously reported.

Case Presentation:

  • Introductory sentence: e.g. This 25 year old female office worker presented for the treatment of recurrent headaches.
  • Describe the essential nature of the complaint, including location, intensity and associated symptoms: e.g. Her headaches are primarily in the suboccipital region, bilaterally but worse on the right. Sometimes there is radiation towards the right temple. She describes the pain as having an intensity of up to 5 out of ten, accompanied by a feeling of tension in the back of the head. When the pain is particularly bad, she feels that her vision is blurred.
  • Further development of history including details of time and circumstances of onset, and the evolution of the complaint: e.g. This problem began to develop three years ago when she commenced work as a data entry clerk. Her headaches have increased in frequency in the past year, now occurring three to four days per week.
  • Describe relieving and aggravating factors, including responses to other treatment: e.g. The pain seems to be worse towards the end of the work day and is aggravated by stress. Aspirin provides some relieve. She has not sought any other treatment.
  • Include other health history, if relevant: e.g. Otherwise the patient reports that she is in good health.
  • Include family history, if relevant: e.g. There is no family history of headaches.
  • Summarize the results of examination, which might include general observation and postural analysis, orthopedic exam, neurological exam and chiropractic examination (static and motion palpation): e.g. Examination revealed an otherwise fit-looking young woman with slight anterior carriage of the head. Cervical active ranges of motion were full and painless except for some slight restriction of left lateral bending and rotation of the head to the left. These motions were accompanied by discomfort in the right side of the neck. Cervical compression of the neck in the neutral position did not create discomfort. However, compression of the neck in right rotation and extension produced some right suboccipital pain. Cranial nerve examination was normal. Upper limb motor, sensory and reflex functions were normal. With the patient in the supine position, static palpation revealed tender trigger points bilaterally in the cervical musculature and right trapezius. Motion palpation revealed restrictions of right and left rotation in the upper cervical spine, and restriction of left lateral bending in the mid to lower cervical spine. Blood pressure was 110/70. Houle’s test (holding the neck in extension and rotation for 30 seconds) did not produce nystagmus or dizziness. There were no carotid bruits.
  • The patient was diagnosed with cervicogenic headache due to chronic postural strain.

Management and Outcome:

  • Describe as specifically as possible the treatment provided, including the nature of the treatment, and the frequency and duration of care: e.g. The patient undertook a course of treatment consisting of cervical and upper thoracic spinal manipulation three times per week for two weeks. Manipulation was accompanied by trigger point therapy to the paraspinal muscles and stretching of the upper trapezius. Additionally, advice was provided concerning maintenance of proper posture at work. The patient was also instructed in the use of a cervical pillow.
  • If possible, refer to objective measures of the patient’s progress: e.g. The patient maintained a headache diary indicating that she had two headaches during the first week of care, and one headache the following week. Furthermore the intensity of her headaches declined throughout the course of treatment.
  • Describe the resolution of care: e.g. Based on the patient’s reported progress during the first two weeks of care, she received an additional two treatments in each of the subsequent two weeks. During the last week of care she experienced no headaches and reported feeling generally more energetic than before commencing care. Following a total of four weeks of care (10 treatments) she was discharged.

Discussion:

Synthesize foregoing sections: e.g. The distinction between migraine and cervicogenic headache is not always clear. However, this case demonstrates several features …

Summarize the case and any lessons learned: e.g. This case demonstrates a classical presentation of cervicogenic headache which resolved quickly with a course of spinal manipulation, supportive soft-tissue therapy and postural advice.

References: (using Vancouver style) e.g.

1 Terret AGJ. Vertebrogenic hearing deficit, the spine and spinal manipulation therapy: a search to validate the DD Palmer/Harvey Lillard experience. Chiropr J Aust 2002; 32:14–26.

Legends: (tables, figures or images are numbered according to the order in which they appear in the text.) e.g.

Figure 1: Intensity of headaches as recorded on a visual analogue scale (vertical axis) versus time (horizontal axis) during the four weeks that the patient was under care. Treatment was given on days 1, 3, 5, 8, 10, 12, 15, 18, 22 and 25. Headache frequency and intensity is seen to fall over time.

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99 million people included in largest global vaccine safety study

19 February 2024

Health and medicine , Faculty of Medical and Health Sciences

The Global Vaccine Data Network, hosted at the University of Auckland, utilises vast data sets to detect potential vaccine safety signals

Global Vaccine Data Network co-director Dr Helen Petousis-Harris: Latest study uses vast data sets to ensure vaccine safety.

The Global Vaccine Data Network (GVDN) assessed 13 neurological, blood, and heart related medical conditions to see if there was a greater risk of them occurring after receiving a Covid-19 vaccine in the latest of eight studies in the Global COVID Vaccine Safety (GCoVS) Project.

Recently published in the journal Vaccine , this observed versus expected rates study included 99 million people (over 23 million person-years of follow-up) from 10 collaborator sites across eight countries. The study identified the pre-established safety signals for myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the thin sac covering the heart) after mRNA vaccines, and Guillain-Barré syndrome (muscle weakness and changed sensation (feeling)), and cerebral venous sinus thrombosis (type of blood clot in the brain) after viral vector vaccines.

Possible safety signals for transverse myelitis (inflammation of part of the spinal cord) after viral vector vaccines and acute disseminated encephalomyelitis (inflammation and swelling in the brain and spinal cord) after viral vector and mRNA vaccines were identified.

So far, these findings were further investigated by the GVDN site in Victoria, Australia. Their study and results are described in the accompanying paper. Results are available for public review on GVDN’s interactive data dashboards.

Observed versus expected analyses are used to detect potential vaccine safety signals. These studies look at all people who received a vaccine and examine if there is a greater risk for developing a medical condition in various time periods after getting a vaccine compared with a period before the vaccine became available.

Lead author Kristýna Faksová of the Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark, remarked that use of a common protocol and aggregation of the data through the GVDN makes studies like this possible. “The size of the population in this study increased the possibility of identifying rare potential vaccine safety signals,” she explains. “Single sites or regions are unlikely to have a large enough population to detect very rare signals.”

By making the data dashboards publicly available, we are able to support greater transparency, and stronger communications to the health sector and public.

Associate Professor Helen Petousis-Harris Co-Director, Global Vaccine Data Network hosted at University of Auckland

GVDN Co-Director Dr Steven Black said, “GVDN supports a coordinated global effort to assess vaccine safety and effectiveness so that vaccine questions can be addressed in a more rapid, efficient, and cost-effective manner. We have a number of studies underway to build upon our understanding of vaccines and how we understand vaccine safety using big data.”

GVDN Co-Director Dr. Helen Petousis-Harris said, “By making the data dashboards publicly available, we are able to support greater transparency, and stronger communications to the health sector and public.”

The GCoVS Project was made possible with support by the Centers for Disease Control and Prevention (CDC) of the U.S. Department of Health and Human Services (HHS) to allow the comparison of the safety of vaccines across diverse global populations.

About the Global Data Vaccine Network

Established in 2019 and with data sourced from millions of individuals across six continents, the GVDN collaborates with renowned research institutions, policy makers, and vaccine related organisations to establish a harmonised and evidence-based approach to vaccine safety and effectiveness.

The GVDN is supported by the Global Coordinating Centre based at Auckland UniServices Ltd, a not-for-profit, stand-alone company that provides support to researchers and is wholly owned by the University of Auckland. Aiming to gain a comprehensive understanding of vaccine safety and effectiveness profiles, the GVDN strives to create a safer immunisation landscape that empowers decision making for the global community. For further information, visit globalvaccinedatanetwork.org.

Disclaimer: This news release summarises the key findings of the GVDN observed versus expected study. To view the full publication in Vaccine, visit doi.org/10.1016/j.vaccine.2024.01.100.

This project is supported by the Centers for Disease Control and Prevention (CDC) of the U.S. Department of Health and Human Services (HHS) as part of a financial assistance award totalling US$10,108,491 with 100 percent funded by CDC/HHS. The contents are those of the author and do not necessarily represent the official views of, nor an endorsement by, CDC/HHS, or the U.S. Government. For more information, please visit cdc.gov

Media enquiries: gvdn@auckland.ac.nz and communications@uniservices.co.nz

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Journal Retracts Studies Cited in Federal Court Ruling Against Abortion Pill

The journal found that the studies, which had suggested that medication abortion is unsafe, included incorrect factual assumptions and misleading presentation of the data.

An orange box of Mifeprex (Mifepristone) sits on a table with papers nearby.

By Pam Belluck

An academic journal publisher this week retracted two studies that were cited by a federal judge in Texas last year when he ruled that the abortion pill mifepristone should be taken off the market .

Most of the authors of the studies are doctors and researchers affiliated with anti-abortion groups, and their reports suggested that medication abortion causes dangerous complications, contradicting the widespread evidence that abortion pills are safe .

The lawsuit in which the studies were cited will be heard by the Supreme Court in March. The high court’s ruling could have major implications for access to medication abortion, which is now the most common method of pregnancy termination.

The publisher, Sage Journals, said it had asked two independent experts to evaluate the studies, published in 2021 and 2022 in the journal Health Services Research and Managerial Epidemiology, after a reader raised concerns.

Sage said both experts had “identified fundamental problems with the study design and methodology, unjustified or incorrect factual assumptions, material errors in the authors’ analysis of the data, and misleading presentations of the data that, in their opinions, demonstrate a lack of scientific rigor and invalidate the authors’ conclusions in whole or in part.”

The publisher also retracted a third study by many of the same authors that was published in 2019 in the same journal, which did not figure in the mifepristone lawsuit.

Sage said that when it had begun examining the 2021 study, it confirmed that most of the authors had listed affiliations with “pro-life advocacy organizations” but had “declared they had no conflicts of interest when they submitted the article for publication or in the article itself.”

Sage said it had also learned that one of the reviewers who evaluated the article for publication was affiliated with the Charlotte Lozier Institute, the research arm of Susan B. Anthony Pro-Life America.

The institute denied that the studies were flawed, as did the lead author, James Studnicki, who is vice president and director of data analytics at the institute.

“Sage is targeting us,” Dr. Studnicki, who has a doctor of science degree and a master’s degree in public health, said in a video defending the team’s work.

Noting that the studies had been used in legal actions, he said: “We have become visible, people are quoting us, and for that reason we are dangerous, and for that reason they want to cancel our work. What happened to us has little or nothing to do with real science and has everything to do with political assassination.”

In a statement, Dr. Studnicki said, “The authors will be taking appropriate legal action,” but he did not specify what that would be.

The lawsuit seeking to bar mifepristone — the first pill in the two-drug medication abortion regimen — was filed against the Food and Drug Administration by a consortium of groups and doctors who oppose abortion. In fighting the lawsuit, the federal government has defended its approval and regulation of mifepristone, provided years of evidence that the pill is safe and effective and argued that the plaintiffs have no legal standing to sue because they are not abortion providers and have not been harmed by mifepristone’s availability.

In his opinion last April, Judge Matthew J. Kacsmaryk cited the 2021 study to support his conclusion that the plaintiffs had legal standing to sue. That study reported a higher rate of emergency room visits after medication abortions than after procedural abortions. Citing it, Judge Kacsmaryk wrote that the plaintiffs “have standing because they allege adverse events from chemical abortion drugs can overwhelm the medical system and place ‘enormous pressure and stress’ on doctors during emergencies and complications.”

In another section of his ruling, Judge Kacsmaryk cited the 2022 study, writing that “plaintiffs allege ‘many intense side effects’ and ‘significant complications requiring medical attention’ resulting from Defendants’ actions.”

Judge Kacsmaryk’s opinion was criticized by many legal experts, and an appeals court struck parts of it but said significant restrictions should be placed on mifepristone that would prevent it from being mailed or prescribed by telemedicine.

Legal experts said it was unclear if Sage’s action would affect the Supreme Court’s decision. Mary Ziegler, a law professor at the University of California, Davis, said the retractions might simply “reinforce a position they were already ready to take.”

For example, she said, there were already strong arguments that the plaintiffs lacked legal standing, so if a justice was “willing to overlook all that other stuff, you may be willing to overlook the retractions too,” she said. For justices already “bothered by various other problems with standing, you probably were potentially going to say the plaintiffs didn’t have standing as it was.”

Similarly, she said, some justices would already have concluded that the vast majority of studies show mifepristone is safe, so if a justice was “prepared to say that, notwithstanding the weight of the evidence, mifepristone is really dangerous, you could easily do that again if you lose a couple of studies.”

Pam Belluck is a health and science reporter, covering a range of subjects, including reproductive health, long Covid, brain science, neurological disorders, mental health and genetics. More about Pam Belluck

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