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Abstract

Purpose:

To improve practices in rapidly changing environments, it is helpful to learn from relevant innovators. This article describes a well-defined and adaptable method for discovering innovative cases that inform best practices or positive/negative deviant research.

Methods:

As part of a national study of innovation in primary care settings, we developed a three-step method for identifying exemplar practices and applied that method to finding a sample of relevant innovators for in-depth case studies from which to draw transportable lessons about improving primary care practice.

Results:

Relevant, information-rich cases are uncovered using cycles of identification, sampling, and assessment. This cycle is repeated at each step of the defined three-step method. Step 1, a scan of the published literature, assesses both the state-of-the-art and the baseline characteristics of relevant cases; Step 2, a scan of practice settings, draws upon the expert knowledge of key informants to identify additional potentially relevant cases; and Step 3, sample refinement, evaluates potential cases for eligibility, purposeful diversity, and information-rich expressions of defined key domains. Using this three-step method, we identified a national cohort of primary care practice innovators. We found the method to be feasible, practical, and highly successful at identifying information-rich practices from which to draw transportable lessons about practice innovation.

Conclusions:

The three-step method outlines an effective sampling strategy for identifying innovation exemplars and information-rich cases that exceed measures of central tendency. By leveraging the collective knowledge of innovators, this method can support dynamic research and foster rapid cycle learning.

Keywords

qualitative methods primary care practice innovation sampling strategy workforce innovations

Introduction

Innovations in technology, treatments, and evidence-based guidelines have resulted in a myriad of interventions and health-care reform efforts worldwide. These are especially noteworthy with primary care reforms in the National Health Service in the United Kingdom (Blumenthal & Dixon, 2012; Reynolds & McKee, 2012) as well as primary care redesign in Canada, Australia, and the United States (Russell et al., 2017; Starfield & Shi, 2002). Ten years after the National Institutes of Health–inspired jump into translational research and implementation science, health care in the United States continues to be hindered by a time lag between hypothesis, discovery, and meaningful change in practice (Etz, Hahn, Gonzalez, Crabtree, & Stange, 2014; Grimshaw, Eccles, Lavis, Hill, & Squires, 2012; Westfall, Mold, & Fagnan, 2007). In a rapidly evolving environment, innovators and early adopters emerge de novo with important breakthroughs in the delivery of health services seemingly every day (Rogers, 2003).

A growing number of primary care pioneers are transforming the way health care is delivered by creating emergent, practice-appropriate solutions that produce better results at lower costs (Etz et al., 2008; Sinsky et al., 2013). Many of these breakthroughs happen at the local level beyond the reach of typical academic settings or studies and therefore remain both potentially prevalent and hidden, while others emerged as part of demonstration projects (Bitton, Martin, & Landon, 2010). Recently, the identification and careful examination of these successful innovators, or positive deviants, has been proposed (Baxter, Taylor, Kellar, & Lawton, 2016; Bradley et al., 2009).

Practice innovators and early adopters comprise a valuable and largely untapped resource (Bradley et al., 2009). Studies of innovators, or of any information-rich population, generally use a purposeful sampling method to identify unique or exemplar cases (Merriam, 1998; Patton, 2015). The work of Jim Collins exemplifies this approach. His widely read book, Good to Great, describes a 6-month search to identify 11 companies as positive deviant case studies (Collins, 2001)—exemplar case studies from which other companies could learn. Purposive sampling methods have previously been developed for case study research (Merriam, 1998); however, these methods are generally used to develop small samples within a narrow sampling frame, whereas questions in practice improvement and health services research generally require broader sampling with an aim toward wide transportability of findings.

In the United States, Canada, Australia, and Europe, there have been literally hundreds of demonstration projects or interventions focused on improving the quality of care in primary care practices (Bitton et al., 2010; Nutting et al., 2010). Many of these have had negative or ambiguous results (Jaen et al., 2010; Shi et al., 2015). Some of the greatest lessons learned regarding best practices in primary care settings remain hidden in plain sight among unpublished innovators. This article articulates a rigorous, pragmatic, and actionable method to bring those lessons to light. The three-step method allows research teams to identify a sample of information-rich cases, such as practice innovators, as the first crucial step in rapid, relevant research.

Context for Method Development

While working on a study, funded by the Robert Wood Johnson Foundation (RWJF), which focused on the identification and critical examination of U.S. primary care workforce innovations and barriers to their spread (Friedman et al., 2014), it became clear that our intended methodology would not work. Informed by our collective research experience in primary care settings, it was clear when conducting our literature review that many innovations known to the research team were either absent or underrepresented in the literature. Additionally, our review of the literature uncovered no clear guidance regarding how a broad sample of practice exemplars could be found, contacted, and vetted. This identification of a national cohort of exemplar primary care practices posed a logistical and methodological challenge.

Therefore, to our first aim of understanding frontline innovation through the literature, we added a second study focus to learn from creative staffing solutions as found in everyday primary care settings. With this second aim, we sought to identify practices able to pioneer new models of care delivery through innovations that both redefined traditional roles and created new, team-based approaches to primary health care. We intentionally selected practices that reflected a variety of geographic types, organizational types, and sizes that ranged from large health systems to solo and micro practices.

The Three-Step Method

Sampling strategy is an essential, though often underdeveloped, element in health-care delivery studies (Miller, Crabtree, Harrison, & Fennell, 2013). The method described here is comprised of three steps. Each step incorporates cycles of identification, reflective sampling, and assessment, which result in a rigorously developed sample able to support scientific advancement. The method can be altered to fit a study regardless of the size and/or length of the study. In addition to the detailed methodology described below, a concise illustration of the purpose and process associated with each step can be found in Table 1.

Table 1.

Three-Step Method for Identifying Practice Exemplars.

Step	Purpose	Process
1: Literature-based environmental scan	Establish potential scopeNarrow focus for feasibility and study fitIdentify known state of the art for this topic	Key word search of relevant sourcesTargeted search of high-profile projects and theme-based publicationsEstablish baseline that identifies and defines “exemplar”
2: Practice-based environmental scan	Identify seed pool for sampling strategyGenerate sample list able to absorb expected attritionIdentify key domains able to define sample	Create list of thought leaders and/or key informantsConduct purposeful and snowball sampling for defined periodCreate typology descriptive of sample and sample variation
3: Sample refinement	Create tool to investigate fit of practices to studyEstablish study eligibility among practice sampleCreate list of eligible sites inclusive of strategic and purposeful diversity	Develop assessment process able to investigate variation in sampleData collection, for example, interviews, targeting specified domainsDevelop objective evaluation metrics able to distinguish qualitative difference and variation in sample

Step 1: Literature-Based Environmental Scan

Step 1 of developing a study sample is conducting an appropriate scan of the published literature. Not all literature reviews must follow the same design; efforts should be made to match the extent and parameters of the literature review with the research questions and time line constraints endemic to the project. The purpose of the literature review is to establish the state-of-the-art scientific knowledge as it relates to a particular topic. Investigating the published universe related to the topic establishes a known baseline and identifies remaining questions and potential opportunities for the development of new knowledge. This baseline informs the use of theoretical sampling in Step 2 by identifying patterns of characteristics likely to be indicative of practice exemplars (Draucker, Martsolf, Ross, & Rusk, 2007).

Careful notes should be taken during the literature review process regarding databases searched, search techniques, and inclusion/exclusion criteria employed. The searching process narrows focus and determines feasibility, thereby establishing the potential scope of the study. Once the preliminary scope is established, it is important to reflect on the match of the identified literature with the research and learning objectives. Narrowing a literature review to make it more manageable risks inadvertently omitting critical projects, questions, and known conversations that are relevant to the topic. Reviewing the constraints of the manuscript sample generated during the literature review allows for the identification of potential gaps in the sample and the opportunity for purposeful sampling to fill such gaps in service of the overall research aims. Key analytic findings are drawn out while assessing the compiled literature review.

Most often, literature findings are reported as identified patterns and commonalities among publications. While this is useful information, it is one step short of a full analysis. Understanding the significance of those patterns and the narratives from which their authority derives is critical for operationalizing lessons learned from the literature review in real-world settings.

The concern with stopping with a literature scan is that every study has limitations. Published studies typically share two common limitations. First, the statement of problem, to which the published findings are a solution, is influenced by the researcher’s intellectual interests and the funder’s strategic priorities. In other words, the solutions are rarely to practice-identified problems (Green, 2006). Second, publication guidelines, such as word limits, may lead to systematic omission of elements critical to an innovation’s success (Westfall et al., 2007). Contextual factors relevant to understanding the fullness of published solutions are likely to remain the lessons learned by the research team alone (Stange & Glasgow, 2013; Tomoaia-Cotisel et al., 2013). A scan of the practice environment is an effective counterbalance to the known limitations of findings accessible through published material. This second environmental scan will generate a list of potential exemplars, identify a set of contextual factors requisite to exemplar practices, and identify distinguishing factors among those exemplars.

Step 2: Practice-Based Environmental Scan

Like the literature-based environmental scan, the scope of the practice-based environmental scan must be responsive to the needs of the research questions and constraints. Without the same opportunity for a key word search as with written works, Step 2 of developing a study sample involves a combination of purposeful and snowball sampling to identify potential practices of interest. It is critical to select the right key informants when designing a successful practice-based environmental scan.

This selection process begins with thought leaders in the area, identified through reputation and publishing history. In addition to their academically relevant knowledge, they are likely to have been exposed to strategies and practices that were never published. They may contribute unpublished gems and known practices with strategies that appeared promising but were ultimately excluded from their study based on research design or resource constraints. They may also provide connections with other thought leaders to whom questions should be addressed. This process can effectively seed the potential pool of exemplars able to best inform study aims.

Just as thought leaders may provide further referrals, potential exemplars may assist in building the sample pool. Many innovators hunger for intellectual and service communities and will have discovered other practices “like them” from which they draw kinship, support, and inspiration. A sampling strategy built through such layers of social networks will engage fewer practices whose solutions are grant-informed or who have previously been the subjects of publication. Two important considerations during this sample-building period include the size of the potential list and the emergent contextual factors that differentiate high performing practices (Stange & Glasgow, 2013). Step 1 helps identify which characteristics potential exemplars should hold in common. Step 2 focuses on characteristics that vary among the sample in ways that will support study validity and future transportability of findings.

Understanding that not all information will be accurate and that not all identified practices will wish study participation, it is important to generate a sample list able to absorb expected reduction during eligibility assessment and attrition during enrollment. While assessing the pool of potential exemplars generated during Step 2, it is necessary to consider the diversity of the sample based on demographics and innovation strategies. The end product from this step will include a composite of practice characteristics, informed by both public and practice domains, that will enable standardization of data elements and maximum learning from practice settings.

Step 3: Sample Refinement

Step 3, sample refinement, is a process of establishing the final fit between the study sample and the research interests. Potential exemplars are evaluated for eligibility and high-quality expression of defined key domains. Having created a large sample of potential practices through an informal but intentional focus on diversity, the researcher(s) must create a tool that is able to standardize the sample selection. This tool should encompass contextual factors thought to be relevant to the phenomena under study (assessed in Step 1) as well as factors known to differentiate practices within the existing pool (assessed in Step 2). It is helpful to create a simple scale that emphasizes clear distinctions in variation among the selected contextual factors. With a focus on exemplary practices, and using Steps 1 and 2 as a guide, a three-level scale that identifies practice expression of key domains as average, better than average, and the top 10% of the sample pool can be created.

Identifying a National Cohort of Practice Exemplars Using the Three-Step Method

Below we demonstrate the application of the three-step method to identify primary care innovations underrepresented in the published literature and the contextual factors most likely to inform transportability. A concise summary of the method as applied in this context can be found in Table 2.

Table 2.

Identifying Exemplars of Workforce Innovation in Primary Care.

Steps/Process		Outcome
1. Literature-based environmental scan—reviewed 331 published manuscripts
	Used 80 key words to search three major databasesTargeted review of eight high-profile projects and 14 theme-based special issues of journalsDeveloped typology of published innovations and identified common characteristics	Identified 4,386 abstracts and reviewed 304 manuscriptsAdded 27 manuscripts to reviewEstablished baseline for defining innovation among sites
2. Practice-based environmental scan—identified 277 potential exemplar practices
	Identified 50 thought leaders based on literature review and knowledge of the fieldE-mailed thought leaders asking for identification of potential sites and other thought leadersCleaned data; developed typology and common characteristics among potential exemplars	Responses from 387 thought leaders; 71 requested phone callsIdentified initial list of 435 potential practicesCleaning reduced list by 158; five key domains identified
3. Sample refinement—established diverse sample of 151 exemplar practices
	Developed means for assessing key domainsConducted phone interviews collecting data on five study-relevant domainsTwo-page practice profiles used to member-check data and evaluate each site along five key domains	Created interview guide50 practices eliminated; completed 227 site interviewsScored 187 profiles using 18-point scale; 36 sites removed

Step 1: Primary Care Workforce Innovations in the Published Literature

In order to identify creative staffing solutions as represented in the peer-reviewed published literature, we searched the PubMed, PsycINFO, and CINAHL databases using 80 key terms as a purposeful counterbalance to the lack of clearly defined literature on our topic of interest. Our team read through the first 10% of resulting abstracts to develop inclusion/exclusion criteria for identifying manuscripts that would be responsive both to our research interests and to the limits and wealth of literature we uncovered. As part of the sampling/sense-making process, we conducted a targeted, slightly wider sampling of abstracts from relevant thematic journals or as outcomes of key projects. After reviewing 4,413 abstracts, we selected approximately 304 manuscripts for review. Reflecting on the sample that resulted, we additionally targeted theme issues relevant to our research aims, adding 27 manuscripts to our sample. Our subsequent assessment of the literature allowed us to identify the known cutting edge of workforce innovations and commonalities among strategies found in published studies (Friedman et al., 2014).

Step 2: Generating Sample of Potential Practice Exemplars

In Step 2, we used findings from the literature review to establish a common and defensible baseline for determining whether an identified staffing solution met the threshold for being considered “innovative.” We began our identification of potential exemplar practices by drawing on the insights of key informants: 50 thought leaders found in the literature and a handful of national experts who were known to the research team. In both cases, we asked our key informants for two pieces of information: first, identification of two or three practices they personally knew to be clinically excellent, high-quality settings employing creative staffing solutions and second, identification of two or three colleagues who might also be able to share referrals of known practices. Our sampling/sense-making strategy included e-mail and phone communication with these thought leaders followed by successive refinement in our request in order to maximize diversity of the list we were developing and the potential of that list to align with our research interests.

Once we felt we had developed a list able to withstand likely reduction through information cleaning and attrition, we assessed points of commonality and divergence among potential exemplar practices as compared with our known baseline. This assessment ensured a healthy diversity within our sample. It also allowed us to consider key contextual factors (previsit, start history note, postvisit, transitions, care/case management, health coaching, nontraditional visits, patient portals, scribing, anticoagulation clinic, hypertension clinic, empanelment, addressing PCP burnout, and shared Electronic Medical Record) that potential exemplars shared in common, which we were then able to hold in contrast to characteristics held in common by practices represented in the literature (Etz et al., 2014).

Step 3: Refinement of Sample Selection

In the third and final step, we conducted 45-min phone interviews with each remaining practice in our potential sample pool. Since every practice included at this point was selected through key informant referral, the interview process was essential in establishing the reliability of referrals and potential fit of an identified practice to our research interests. Conducting phone interviews and standardizing information learned during unstructured interviews through the creation of two-page practice profiles became the sampling/sense-making step for determining study inclusion/exclusion criteria. Practice profiles were shared with interview participants to check for validity and accuracy before they were used to inform the selection process (Cohen & Crabtree, 2008).

Once checked, the practice profiles were evaluated for six metrics (team, workforce, PB/community unity, performance, sustainability, and overall impression) on a 3-point scale where 3 was high and 1 was low. For example, sustainability included when the innovation began, how long it had been in place, and the self-reported likelihood of continuance. Thus, the practice profiles became a simple metric to allow for standardized comparison and identification of best practices across a known set of key contextual factors (assessed in Step 2) and study-relevant domains (assessed in Step 1).

Easy Outcomes and Flexible Adaptations

Using the three-step method, we developed a final national cohort of 151 exemplar primary care practices. Once complete, a panel of national experts reviewed our practice list and member-checked the standardized profiles and metric for scoring. A subset of 30 practices spanning 20 states and representing practices of varying size, ownership, and settings was then selected for inclusion in the RWJF-funded Primary Care Teams: Learning from Exemplar Ambulatory Practices (LEAP; Ladden et al., 2013). Our process relied on our ability to convey our needs and intentions to other thought leaders and practice leaders in order to receive useful referrals. Beyond referrals, it was necessary to rely heavily on effective phone interviews during Step 3 in order to make final selections. Findings of the LEAP team that resulted from intensive 3-day site visits to selected practices by teams of three to five researchers validated the usefulness and effectiveness of our method (Ladden et al., 2013; Wagner et al., 2017). In addition to the LEAP Project, the cohort of 151 exemplar practices was used in a separate National Cancer Institute–funded study to examine delivery of care for long-term cancer survivors in workforce innovators (Rubinstein et al., 2017) as well as in an Agency for Healthcare Research and Quality funded conference series focused on understanding how exemplar PCMH practices are able to overcome challenges (Howard et al., 2016; O’Malley et al., 2017).

Discussion

Previously, in a review of the literature on health services delivery, our team identified two crippling gaps between research and practice (Friedman et al., 2014). First, recognized best practices, identified and validated through rigorous scientific studies, are diffused into everyday primary care practice at a frustratingly slow rate (Rogers, 2003). Second, best practices found either through efficacy or effectiveness studies may not be best for practices when applied to real-world health-care settings that need to function at the intersection of communities, health-care delivery structures, and fiscal constraints. And yet there is an entire world of practices that occupy the space in-between. There is an urgent need to make those practice-inspired solutions that are able to bridge the innovation gap more visible (Green, 2006, 2008; Green, Ottoson, Garcia, & Hiatt, 2009). Not only can such an approach overcome obstacles that have continued to stymie successful translation of feasible and sustainable solutions but it also allows for an accelerated diffusion of innovative findings. There are hundreds of unknown, yet inspired, natural experiments occurring throughout the health-care professions (Mold & Peterson, 2005). A focus on innovators exposes what they have learned to early adopters and the early majority most likely to implement innovator-informed solutions (Rogers, 2003).

While our example required individuals with a background in research, the three-step method provides a pragmatic and actionable solution to those interested in generating a robust science for health-care delivery that is organic to context, receptive to nimble adaptation, and informed by those most affected by the outcomes of their work. Depending on the topic of interest, interested parties could include non-research-trained individuals such as patients or patient representatives from advocacy groups.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Robert Wood Johnson Foundation Center for Health Policy (Grant 68461).

ORCID iD

Rebecca S. Etz

References

Baxter

Taylor

Kellar

Lawton

(2016). What methods are used to apply positive deviance within healthcare organisations? A systematic review. BMJ Quality & Safety, 25, 190–201. doi:10.1136/bmjqs-2015-004386

Bitton

Martin

Landon

B. E.

(2010). A nationwide survey of patient centered medical home demonstration projects. Journal of General Internal Medicine, 25, 584–592. doi:10.1007/s11606-010-1262-8

Blumenthal

Dixon

(2012). Health-care reforms in the USA and England: Areas for useful learning. The Lancet, 380, 1352–1357. doi:10.1016/S0140-6736(12)60956-8

Bradley

E. H.

Curry

L. A.

Ramanadhan

Rowe

Nembhard

I. M.

Krumholz

H. M.

(2009). Research in action: Using positive deviance to improve quality of health care. Implementation Science, 4, 25. doi:10.1186/1748-5908-4-25

Cohen

D. J.

Crabtree

B. F.

(2008). Evaluative criteria for qualitative research in health care: Controversies and recommendations. Annals of Family Medicine, 6, 331–339. doi:10.1370/afm.818

Collins

J. C.

(2001). Good to great: Why some companies make the leap—And others don’t (1st ed.). New York, NY: HarperBusiness.

Draucker

C. B.

Martsolf

D. S.

Ross

Rusk

T. B.

(2007). Theoretical sampling and category development in grounded theory. Qualitative Health Research, 17, 1137–1148. doi:10.1177/1049732307308450

Etz

R. S.

Cohen

D. J.

Woolf

S. H.

Holtrop

J. S.

Donahue

K. E.

Isaacson

N. F.

… Olson

A. L

. (2008). Bridging primary care practices and communities to promote healthy behaviors. American Journal of Preventive Medicine, 35, S390–S397. doi:10.1016/j.amepre.2008.08.008

Etz

R. S.

Hahn

K. A.

Gonzalez

M. M.

Crabtree

B. F.

Stange

K. C.

(2014). Practice-based innovations: More relevant and transportable than NIH-funded studies. Journal of the American Board of Family Medicine, 27, 738–739. doi:10.3122/jabfm.2014.06.140053

10.

Friedman

Hahn

K. A.

Etz

Rehwinkel-Morfe

A. M.

Miller

W. L.

Nutting

P. A.

… Crabtree

B. F

. (2014). A typology of primary care workforce innovations in the United States since 2000. Medical Care, 52, 101–111. doi:10.1097/MLR.0000000000000043

11.

Green

L. W.

(2006). Public health asks of systems science: To advance our evidence-based practice, can you help us get more practice-based evidence? American Journal of Public Health, 96, 406–409. doi:10.2105/AJPH.2005.066035

12.

Green

L. W.

(2008). Making research relevant: If it is an evidence-based practice, where’s the practice-based evidence? Family Practice, 25, i20–i24. doi:10.1093/fampra/cmn055

13.

Green

L. W.

Ottoson

J. M.

Garcia

Hiatt

R. A.

(2009). Diffusion theory and knowledge dissemination, utilization, and integration in public health. Annual Review of Public Health, 30, 151–174. doi:10.1146/annurev.publhealth.031308.100049

14.

Grimshaw

J. M.

Eccles

M. P.

Lavis

J. N.

Hill

S. J.

Squires

J. E.

(2012). Knowledge translation of research findings. Implementation Science, 7, 50. doi:10.1186/1748-5908-7-50

15.

Howard

Etz

R. S.

Crocker

J. B.

Skinner

Kelleher

K. J.

Hahn

K. A.

… Crabtree

B. F

. (2016). Maximizing the patient-centered medical home (PCMH) by choosing words wisely. Journal of the American Board of Family Medicine, 29, 248–253. doi:10.3122/jabfm.2016.02.150199

16.

Jaen

C. R.

Ferrer

R. L.

Miller

W. L.

Palmer

R. F.

Wood

Davila

… Stange

K. C.

(2010). Patient outcomes at 26 months in the patient-centered medical home national demonstration project. Annals of Family Medicine, 8, S57–S67, S92. doi:10.1370/afm.1121

17.

Ladden

M. D.

Bodenheimer

Fishman

N. W.

Flinter

Hsu

Parchman

Wagner

E. H.

(2013). The emerging primary care workforce: Preliminary observations from the primary care team: Learning from effective ambulatory practices project. Academic Medicine, 88, 1830–1834. doi:10.1097/ACM.0000000000000027

18.

Merriam

S. B.

(1998). Qualitative research and case study applications in education (2nd ed.). San Francisco, CA: Jossey-Bass.

19.

Miller

W. L.

Crabtree

B. F.

Harrison

M. I.

Fennell

M. L.

(2013). Integrating mixed methods in health services and delivery system research. Health Services Research, 48, 2125–2133. doi:10.1111/1475-6773.12123

20.

Mold

J. W.

Peterson

K. A.

(2005). Primary care practice-based research networks: Working at the interface between research and quality improvement. Annals of Family Medicine, 3, S12–S20. doi:10.1370/afm.303

21.

Nutting

P. A.

Crabtree

B. F.

Miller

W. L.

Stewart

E. E.

Stange

K. C.

Jaen

C. R.

(2010). Journey to the patient-centered medical home: A qualitative analysis of the experiences of practices in the national demonstration project. Annals of Family Medicine, 8, S45–S56, S92. doi:10.1370/afm.1075

22.

O’Malley

Hudson

S. V.

Nekhlyudov

Howard

Rubinstein

Lee

H. S.

… Crabtree

B. F

. (2017). Learning the landscape: Implementation challenges of primary care innovators around cancer survivorship care. Journal of Cancer Survivorship, 11, 13–23. doi:10.1007/s11764-016-0555-2

23.

Patton

M. Q.

(2015). Qualitative research & evaluation methods: Integrating theory and practice (4th ed.). Thousand Oaks, CA: Sage.

24.

Reynolds

McKee

(2012). Opening the oyster: The 2010-11 NHS reforms in England. Clinical Medicine (Lond), 12, 128–132.

25.

Rogers

E. M.

(2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.

26.

Rubinstein

E. B.

Miller

W. L.

Hudson

S. V.

Howard

O’Malley

Tsui

… Crabtree

B. F

. (2017). Cancer survivorship care in advanced primary care practices: A qualitative study of challenges and opportunities. JAMA Internal Medicine. doi:10.1001/jamainternmed.2017.4747

27.

Russell

G. M.

Miller

W. L.

Gunn

J. M.

Levesque

J. F.

Harris

M. F.

Hogg

W. E.

… Crabtree

B. F

. (2017). Contextual levers for team-based primary care: Lessons from reform interventions in five jurisdictions in three countries. Family Practice. doi:10.1093/fampra/cmx095

28.

Shi

Lock

D. C.

Lee

D. C.

Lebrun-Harris

L. A.

Chin

M. H.

Chidambaran

… Sripipatana

. (2015). Patient-centered medical home capability and clinical performance in HRSA-supported health centers. Medical Care, 53, 389–395. doi:10.1097/MLR.0000000000000331

29.

Sinsky

C. A.

Willard-Grace

Schutzbank

A. M.

Sinsky

T. A.

Margolius

Bodenheimer

(2013). In search of joy in practice: A report of 23 high-functioning primary care practices. Annals of Family Medicine, 11, 272–278. doi:10.1370/afm.1531

30.

Stange

Glasgow

(2013). Considering and reporting important contextual factors in research on the patient-centered medical home. Rockville, MD: Agency for Healthcare Research and Quality.

31.

Starfield

Shi

(2002). Policy relevant determinants of health: An international perspective. Health Policy, 60, 201–218.

32.

Tomoaia-Cotisel

Scammon

D. L.

Waitzman

N. J.

Cronholm

P. F.

Halladay

J. R.

Driscoll

D. L.

… Stange

K. C

. (2013). Context matters: The experience of 14 research teams in systematically reporting contextual factors important for practice change. Annals of Family Medicine, 11, S115–S123. doi:10.1370/afm.1549

33.

Wagner

E. H.

Flinter

Hsu

Cromp

Austin

B. T.

Etz

… Ladden

M. D

. (2017). Effective team-based primary care: Observations from innovative practices. BMC Family Practice, 18, 13. doi:10.1186/s12875-017-0590-8

34.

Westfall

J. M.

Mold

Fagnan

(2007). Practice-based research—“Blue Highways” on the NIH roadmap. Journal of the American Medical Association, 297, 403–406. doi:10.1001/jama.297.4.403

An Innovative Three-Step Method for Identifying Exemplars

Abstract

Purpose:

Methods:

Results:

Conclusions:

Keywords

Introduction

Context for Method Development

The Three-Step Method

Step 1: Literature-Based Environmental Scan

Step 2: Practice-Based Environmental Scan

Step 3: Sample Refinement

Identifying a National Cohort of Practice Exemplars Using the Three-Step Method

Step 1: Primary Care Workforce Innovations in the Published Literature

Step 2: Generating Sample of Potential Practice Exemplars

Step 3: Refinement of Sample Selection

Easy Outcomes and Flexible Adaptations

Discussion

Footnotes

Declaration of Conflicting Interests

Funding

ORCID iD

References