Thirty medical home pilot primary care practices had high structural capabilities at baseline and performance improved substantially after 24 months in practices starting with lower capabilities.
1) Evaluate structural capabilities associated with the patient-centered medical home (PCMH) model in PCMH pilots in Colorado, Ohio, and Rhode Island; 2) evaluate changes in capabilities over 2 years in the Rhode Island pilot; and 3) evaluate facilitators and barriers to the adoption of capabilities.
We assessed structural capabilities in the 30 pilot practices using a cross-sectional study design and examined changes over 2 years in 5 Rhode Island practices using a pre/post design.
We used National Committee for Quality Assurance’s Physician Practice Connections—Patient-Centered Medical Home (PPC/PCMH) accreditation survey data to measure capabilities. We stratified by high and low performance based on total score and by practice size. We analyzed change from baseline to 24 months for the Rhode Island practices. We analyzed qualitative data from interviews with practice leaders to identify facilitators and barriers to building capabilities.
On average, practices scored 73 points (out of 100 points) for structural capabilities. High and low performers differed most on electronic prescribing, patient self-management, and care-management standards. Rhode Island practices averaged 42 points at baseline, and reached 90 points by the end of year 2. Some of the key facilitators that emerged were payment incentives, “transformation coaches,” learning collaboratives, and data availability supporting performance management and quality improvement. Barriers to improvement included the extent of transformation required, technology shortcomings, slow cultural change, change fatigue, and lack of broader payment reform.
For these early adopters, prevalence of structural capabilities was high, and performance was substantially improved for practices with initially lower capabilities. We conclude that building capabilities requires payment reform, attention to implementation, and cultural change.
Am J Manag Care. 2014;20(7):e265-e277
This article examines structural capabilities associated with the patient-centered medical home model in 30 small- and medium-sized primary care practices participating in medical home pilots in Colorado, Ohio, and Rhode Island. The authors found:
The patient-centered medical home (PCMH) is gaining traction as a promising model for reforming primary care. Some experts believe that PCMHs have the potential to improve the quality, coordination, and efficiency of healthcare and to alleviate the impending manpower crisis in primary care.1-3 The PCMH has been supported by mounting evidence in 3 areas. First, there is abundant evidence from the United States and other Western countries that links primary care with better health outcomes, lower costs, and greater equity in care.4-6 Second, there is a growing body of evidence around individual components of primary care—particularly those embodied in Wagner’s Chronic Care Model—linking the use of practice systems with improved quality of care, quality of life, and cost savings for some high-risk populations.7-9 Third, there is early evidence around the PCMH model itself that suggests it has the potential to enhance patient experience, improve some aspects of clinical quality, and reduce avoidable emergency utilization, although the impact on avoidable hospital utilization is, to date, mixed.10-12
Interest in the PCMH is high, but to achieve maximum potential benefits, primary care practices may be required to invest substantially in structural capabilities associated with this model of care. For example, a population registry can help primary care practices group patients by diagnosis, to facilitate appropriate follow-up; performance management can help providers compare their data with benchmarks and motivate quality improvement; and referral tracking and care management can improve coordination among different professionals and organizations when patients are most vulnerable to medical errors. The Institute of Medicine, the health arm of the National Academy of Sciences, has highlighted the importance of these capabilities and identified their absence as representing a key gap in primary care.13
However, studies examining the “readiness” of physician practices to implement structural capabilities show low levels of preparedness. Factors that increase the likelihood of the presence of structural capabilities include: an affiliation with an integrated system, hospital, or other large entity;14-16 the presence of external incentives, such as pay-for-performance;16 serving racial/ethnic and economically disadvantaged populations;17 and operation in a less-competitive environment.15
Practice size seems an especially important factor. 14,18,19 Larger practice size is associated with average adoption, with 22% of structural capabilities in place in small- to medium-sized practices (≤9 physicians)16 and 35% in larger practices (>9 physicians).19 Rittenhouse et al19 found that the capabilities of nurse care managers, disease registries, clinical-information technology, and quality-improvement processes were least developed in smaller practices.
Because 88% of all patient visits occur in small- and medium-sized practices, it is important to understand the experience of these practices with regard to implementing structural capabilities, including which capabilities are easier or more difficult to adopt, whether practice size makes a difference, the time frame for implementation, and the resources and supports they require. This information can help policy makers understand how to best facilitate the transformation of physician practices into PCMHs.
METHODSResearch Design and Sample
As part of a larger study of the impact of the PCMH model on quality, costs, coordination, and consumer and provider satisfaction (using data from 30 primary care practices in 3 pilot initiatives in Rhode Island, Colorado, and Ohio),12 we conducted a quantitative investigation of the practices’ PCMH structural capabilities, using the Physician Practice Connections—Patient-Centered Medical Home Model (PPCPCMH) accreditation survey data from the National Committee for Quality Assurance (NCQA). We used a cross-sectional study design to assess the extent of adoption of structural capabilities in the pilots across the 3 states.
For the Rhode Island pilot, we obtained data on the structural capabilities of participating practices at 2 years post baseline because their baseline data were lower than in the other pilots. This allowed us to explore the change in prevalence of structural capabilities. To understand the facilitators and barriers to the adoption of structural capabilities, we interviewed practice care leaders in the primary care practices involved in the pilot. The study was approved by the Institutional Review Board at the Harvard School of Public Health.
Although there was variation across the pilots in the timing and priority attached to implementing specific components of the medical home, the 3 pilots shared 3 common elements: a self-assessment using the PPC-PCMH survey to obtain PCMH recognition; technical assistance from “transformation coaches” and participation in a learning collaborative; and a per-member, per-month care management fee.
The Rhode Island pilot involved 5 primary care practices with 28 physicians collectively serving 24,000 patients. Historically, there was an underinvestment in primary care, compared to high-performing healthcare systems.20 In 2008, the State Office of the Health Insurance Commissioner Department worked with commercial insurers to increase the portion of spending on primary care and also to support the Rhode Island Chronic Care Sustainability Initiative (with participation from primary care physicians, specialists, professional associations, payers, purchasers, and technical experts) with a graduated, per-member, per-month fee of $3 to $4.50, and funding support for a nurse care manager for each of the 5 pilot practices. The 5 practices were invited to participate in the pilot based on their diverse practice characteristics, history of working with each other, readiness for change, and use of an electronic medical record (EMR) (D. Hurwitz, MBA, letter, August 2013). The expectation was that the practices would strive to achieve certain levels of medical home recognition, participate in shared learning to facilitate practice transformation, and measure their performance.20
The Colorado pilot included 14 primary care practices with 50 physicians collectively serving 98,000 patients. This pilot was initiated in May 2009 by HealthTeamWorks and major payers that included Aetna, Anthem-Wellpoint, Cigna, CoverColorado, Colorado Medicaid, Humana, and UnitedHealthcare. The practices were selected from a pool of 23 applications in a competitive process based on their demographics, the culture of the practice (eg, teamwork, collegiality, attitude), quality improvement practices, and electronic capabilities (eg, EMR, disease registry).21 The practices received a monthly fee of $4 to $8 per patient based on their NCQA recognition level, a pay-for-performance payment, assistance from transformation coaches, and participation in a learning collaborative involving all practices in the pilot. Additionally, for all participating practices, HealthTeamWorks brought in a vendor to implement “Reach My Doctor,” an extant Webbased registry featuring a patient portal.
The Ohio pilot had 11 primary care practices with 37 physicians collectively serving 30,000 patients. The pilot was initiated in September 2009 by the Health Improvement Collaborative of Greater Cincinnati and payers that included Anthem, Humana, and United- Healthcare. The practices were selected from a pool of 27 applications in a competitive process based on their diverse practice characteristics, demographics, readiness for change, and EMR capabilities S. Bolton, MPH, letter, August 2013). The practices received a monthly fee of $6 to $7 per patient based on their PCMH recognition level, practice transformation assistance offered mainly by telephone and webinars, and benchmarking data to support improvement.
We used the PPC-PCMH accreditation survey data to measure structural capabilities in the pilot practices. The PPC-PCMH survey asks 170 questions (elements) regarding the capabilities of physician practices on 9 standards: 1) access and communication, 2) patient tracking and registry, 3) care management, 4) patient self-management support, 5) electronic prescribing, 6) test tracking, 7) referral tracking, 8) performance reporting and improvement, and 9) interactive website. The questions identify the presence or absence of the elements, which are coded as present, absent, or not applicable. The score for each standard represents the proportion of weighted points, up to a possible cumulative score of 100 points (see ).
To gain recognition by the NCQA, a practice selfassessed its capabilities using the PPC-PCMH web-based survey and submitted the required data to the NCQA. The NCQA then evaluated and scored the application based on the information received, and it conducted an audit of a sample of the applications as well. Pilot practices received 1 of 3 levels of recognition based on their total score and achievement on 10 “must pass” areas considered foundational for undergoing medical home transformation: 20 Level 1 (a total score of 25 to 49 points and at least 50% achievement on 5 out of the 10 “must pass” elements); Level 2: (a total score of 50 to 74 points and at least 50% achievement on the 10 “must pass” elements); or Level 3 (a total score of 75 to 100 points and at least 50% achievement on the 10 “must pass” elements).
We obtained the PPC-PCMH baseline data from the NCQA for all 30 primary care practices in the Rhode Island, Colorado, and Ohio pilots. Additionally, since the 5 practices in the Rhode Island pilot began the study at below Level 3 status, they had the opportunity to improve their recognition level. Accordingly, we also obtained their PPC-PCMH data at 24 months post baseline. We used practice addresses to identify the state involved and calculated each practice’s size based on its number of physicians.
To understand the implementation experiences as they sought to transform into medical homes, we conducted interviews at baseline, 18 months, and 30 months with a practice leader in each medical home who had responsibility for facilitating the transformation from primary care physician practices to patient-centered medical homes. Most often, they were physicians with a formal leadership role within the practice (eg, medical director), although sometimes they were informal champions of medical home transformation. The interviews lasted approximately 1 hour and were conducted by 2 or more authors. The interview protocol included open-ended questions with guided probes that explored facilitators and barriers to implementing the PCMH model (please see for a copy of the interview protocol).
To understand the prevalence of structural capabilities, we calculated the mean and range of the total score, as well as the average percentage score by standard for the 30 pilot practices. To understand which capabilities are easiest to develop and which ones are more difficult, we stratified practices by their total score and compared the capabilities of the 10 lowest- and highest-performing practices by standard. To understand how the prevalence of capabilities differs by practice size, we also analyzed performance by 3 practice size categories: solo, 2 to 3 physicians, and 4 or more physicians. Finally, to understand how structural capabilities change over time, we analyzed the mean score and the average percentage by standard at baseline and 24 months for the 5 Rhode Island practices. Due to the small sample size, we did not examine statistical differences among groups.
We used thematic analysis to analyze the qualitative data.22 First, we analyzed responses to each interview question. The investigators discussed and developed a preliminary list of codes to represent salient and recurring themes describing facilitators and barriers to the adoption of structural capabilities. The primary author then applied the codes deduced through the initial analysis to data from the 60 interviews using qualitative software (ATLAS.ti, version 6.2). We established coding reliability by having the project’s research assistant code approximately 20% of the quotes extracted from the transcripts (kappa = 0.95, percent agreement = 0.96). We selected quotes to illustrate the key themes emerging from the interviews. All authors confirmed agreement with codes once applied.
The characteristics of the practices are summarized in . The majority of practices were in Colorado (47%), followed by Ohio (37%), and Rhode Island (17%). All were small- to medium-sized practices, 16 with the typical practice being a private family medicine, single-specialty practice, with 3 or fewer physicians.
Achievement of Structural Capabilities
The summary of structural capabilities at baseline appears in . The mean practice score across the 30 pilot practices was 72.7 points (range from 30 to 97 points) (eAppendix B). The majority of the practices had achieved Level 3 recognition (22 practices), while a small percentage had achieved Level 1 (4 practices) and Level 2 recognition (4 practices). The practices with lower PPC-PCMH status were predominantly those in Rhode Island.
The difference in structural capabilities between the 10 lowest- and highest-performing practices is shown in . There was least difference between the low- and high-performing practices in their achievement on the access and communication, patient tracking and registry, and referral tracking standards. The greatest difference in their achievement was on the electronic prescribing, patient self-management support, and care-management standards.
Solo practices averaged the highest PPC-PCMH score (87.9 points) compared with practices in other categories (average score for 2 to 3 physicians: 72 points; for 4 or more physicians: 69.5 points). Solo practices also scored the highest on each of the 9 standards (see eAppendix).
Two-Year Change in Structural Capabilities of the Rhode Island Practices
shows the capabilities in the Rhode Island pilot practices at baseline and 24 months. Even though Rhode Island practices began low, with an average score of 42 points at baseline, by the end of year 2 their average score was 90 points, surpassing the baseline figures for Colorado and Ohio on all standards except for the availability of an interactive website. The biggest gains were seen in the patient self-management (from 7% to 83%) and care management (from 30% to 97%) standards, followed by test tracking (from 41% to 100%), electronic prescribing (from 19% to 70%), and performance reporting and improvement (from 48% to 97%) standards (eAppendix C).
Facilitators and Barriers to the Adoption of Structural Capabilities
shows quotations, taken from interviews with practice leaders, which illustrate what they deemed as the facilitators and barriers to the adoption of structural capabilities. Four factors emerged as facilitators: payment incentives, technical assistance from “transformation coaches,” participation in learning collaboratives, and the availability of data to support performance management and quality improvement. Five factors surfaced as barriers: the extent of transformation required, shortcomings of electronic technology, slowness in achieving cultural change, change fatigue, and the lack of broader payment reform. These themes were consistent across states, although each state’s context is quite different.
This is the first study to examine structural capabilities and change over time in small- to medium-sized primary care practices participating in PCMH pilots, using a nationally recognized dataset. Contrary to the concerns expressed in the literature about the ability of physician practices to achieve structural capabilities,14,16,18,19 we found that a set of small practices were able to attain high levels of medical home capability. However, in comparison to Rittenhouse’s national randomly selected sample which included a broader definition of primary care and where about one-quarter of practices had an EMR (26.2%), ours was a select group, with predominantly primary care physicians, and where the vast majority of practices (approximately 90%) had an EMR.16 We also found that improvement was rapid in the Rhode Island pilot practices, for which initial performance was low. This suggests that basic capabilities do not have to take a long time to build.
A review of the capabilities of the third-highest and third-lowest performing practices suggests that some capabilities are more easily developed than others. The standards that everyone achieved—access and communication, patient tracking and registry, and referral tracking —were also the areas with the majority of the “must pass” elements, supporting the adage that what got measured had received more attention. The standards achieved disproportionately by high performers — electronic prescribing, patient self-management support, and care management standards—may require greater practice and cultural transformation. Both high- and low-performing practices had the least-developed capabilities for the interactive website standard, a capability that may require better-developed technology, as well as cultural change by providers and consumers.
To date, studies on structural capabilities have found a difference by practice size, with smaller practices having lower capabilities.14,18,19,24 However, in our sample, solo practices had the highest capabilities on all 9 standards. Although larger practices may have more resources at their disposal, solo practices may have the advantage of being more nimble and adaptable, suggesting a possible “U-shaped” relationship between practice size and capabilities. This would be consistent with research finding a curvilinear relationship for healthcare facilities between size and various quality metrics such as safety climate25 and quality improvement.26 However, the small sample size and voluntary nature of the pilots (ie, perhaps only most advanced solo practices choose to participate in a PCMH pilot) make it difficult to draw conclusions, and the question requires further exploration.
Given the low prevalence of structural capabilities seen nationally, it is important to identify the facilitators and barriers to achieving structural capabilities. From the interviews we conducted with practice leaders, 3 critical factors emerged. First, financial incentives were instrumental in facilitating the creation of systems. For example, the Rhode Island practices were provided with additional resources, including a care coordinator and a graduated per-member, per-month fee based on their recognition level. Rittenhouse et al16 also found that external incentives, such as pay-for-performance and public reporting, were positively associated with the presence of structural capabilities in small- to medium-sized practices. At the same time, broader payment care reform is important to ensure sustainability.
Second, while payment can facilitate the adoption of capabilities, other factors, such as inadequacies of technology, may affect their successful implementation. Implementation isn’t just about putting individual processes and systems in place; it involves transforming how primary care is delivered, a process that requires time, effort, and a focus on learning. Key intervention components that practices in Rhode Island, Colorado, and Ohio reported as being valuable included assistance from transformation coaches and participation in learning collaboratives. This finding supports the literature about the importance of quality-improvement coaches and learning collaboratives to facilitate the implementation of evidence-based practices, the transfer of tacit knowledge, benchmarking with peers, and the adoption of system-level changes.27-30
Finally, practices noted that using structural capabilities on a regular basis involved cultural change and required more time. Culture is powerful because it is rooted in the values, attitudes, norms, routines, and shared traditions of people who work together in an organization.31 In their review of the relationship between implementation of structural capabilities and culture, Duggan et al found that physician practices that emphasized collegiality and teamwork were more likely to implement structural capabilities compared to those that emphasized hierarchy and autonomy.32 However, a recent study found a preponderance of rational and patient-centered cultures in multispecialty physician groups, and less emphasis on the group and developmental cultures that are necessary for transforming primary care practices into PCMHs.33
Structural capabilities, such as referral tracking, test tracking, and continuity of care, are important not only for the delivery of safe, high-quality primary care, but also to facilitate the implementation of key reform initiatives, including accountable care organizations, medical neighborhoods, bundled payments, and initiatives to reduce inappropriate hospital readmissions by improving care coordination across the continuum. Our other research found a reduction in emergency department visits in the Rhode Island pilot.12 The findings of other studies examining the association between structural capabilities, utilization, costs, and quality have been mixed.34-36 As a result, more research is needed to isolate the capabilities that lead to improvements in care and costs.
Our study has limitations. First, we focused on pilot practices in 3 states, and these practices may differ from those in other states or in other medical home pilot interventions. Since the pilot practices volunteered to be early adopters of the model, there may be a selection bias in the sample regarding openness to innovation and baseline performance, which limits the generalizability of our findings. Indeed, our data suggest that pilot practices in Ohio and Colorado had already adopted many PCMH features at baseline. In addition, pilots received financial incentives and resources, and therefore the results may not be generalizable to practices without similar incentives and support.20
Second, state was substantially confounded with structural capabilities, suggesting that additional research is necessary to determine whether different or additional structural capability gaps are present between low and high performers from different states. Third, the PPC-PCMH measurement tool and data may not capture all the important primary care capabilities or the extent to which, and consistency with which, they are used.36 Fourth, our sample size was small, resulting in limited power for statistical analyses, including associations between the presence of capabilities and quality and patient experience. Notwithstanding these limitations, our study is the first to examine the prevalence and development of structural capabilities in small- to medium-sized PCMHs using a combined cross-sectional and longitudinal study design.
Despite some early promising evidence from PCMH initiatives, there are concerns about the ability of primary care practices, particularly small- to medium-sized ones, to achieve structural capabilities. At a minimum, the results of our study suggest that small- to medium-sized PCMHs can achieve these capabilities. Furthermore, our findings for the Rhode Island pilot suggest that building these capabilities need not take a many years. However, our sample included early adopters, and so the findings from these practices may not compare with later adopters of same-size or larger practices. Building capabilities may require at least transitional financial support if not payment reform, attention to implementation, and cultural change. These investments in primary care may be critical for achieving affordable, safe, high-quality care. A wide range of public and private stakeholders are seeking delivery system reforms rooted in the capabilities that PCMHs are intended to embody.Author Affiliations: Harvard School of Public Health, Boston, MA (SA, ECS, SJS, MBR); RAND Corporation, Boston, MA (ECS); Brigham and Women’s Hospital, Boston, MA (ECS); Harvard Medical School, Boston, MA (ECS, SJS); Massachusetts General Hospital, Boston, MA (SJS).
Source of Funding: The research was approved by the institutional review board at the Harvard School of Public Health and financially supported by the Commonwealth Fund and Colorado Trust (Principle Investigator: Dr Rosenthal). Ms. Alidina’s effort on this project was supported by a dissertation grant from the Canada Program, Weatherhead Center for International Affairs and the Canadian Federation of University Women.
Author Disclosures: None of the authors report a relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (ES, AS, SS, MR); acquisition of data (SS, MR); analysis and interpretation of data (ES, AS, SS, MR); drafting of the manuscript (ES,AS, MR); critical revision of the manuscript for important intellectual content (ES, AS, SS, MR); statistical analysis (AS,MR); obtaining funding (ES, MR); administrative, technical, or logistic support (AS); supervision (ES, SS, MR).
Address correspondence to: Shehnaz Alidina, 170 Brookline Ave, Apt 330, Boston, MA 02215. E-mail: firstname.lastname@example.org. Milstein A, Gilbertson E. American medical home runs. Health Aff (Millwood). 2009;28(5):1317-1326.
2. Rittenhouse DR, Shortell SM. The patient-centered medical home: will it stand the test of health reform? JAMA. 2009;301(19):2038-2040.
3. Pawlson LG, Bagley B, Barr M, Sevilla X, Torda P, Scholle S. Patientcentered medical home: from vision to reality. http://www.dhcs.ca.gov/ prorgovpart/documents/pcmh_vision_to_reality.pdf. Unpublished paper. Accessed July 16. 2014.
4. Baicker K, Chandra A. Medicare spending, the physician workforce, and beneficiaries’ quality of care. Health Aff (Millwood). 2004;Suppl Web Exclusives:W4-184-197.
5. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q. 2005;83(3):457-502.
6. Friedberg MW, Hussey PS, Schneider EC. Primary care: a critical review of the evidence on quality and costs of health care. Health Aff (Millwood). 2010;29(5):766-772.
7. Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness: the chronic care model, part 2. JAMA. 2002;288(15):1909-1914.
8. Tsai AC, Morton SC, Mangione CM, Keeler EB. A meta-analysis of interventions to improve care for chronic illnesses. Am J Manag Care. 2005;11(8):478-488.
9. Coleman K, Austin BT, Brach C, Wagner EH. Evidence on the chronic care model in the new millennium. Health Aff (Millwood). 2009;28(1):75-85.
10. Peikes D, Zutshi A, Genevro JL, Parchman ML, Meyers DS. Early evaluations of the medical home: building on a promising start. Am J Manag Care. 2012;18(2):105-116.
11. Jackson GL, Powers, BJ, Chatterjee R, et al. Improving patient care. the patient-centered medical home. a systematic review. Ann Intern Med. 2013;158(3):169-178.
12. Rosenthal MB, Friedberg MW, Singer SJ, Eastman D, Li Z, Schneider EC. Effect of a multipayer patient-centered medical home on health care utilization and quality: the Rhode Island chronic care sustainability initiative pilot program. JAMA Internal Med. 2013;173(20):1907-1913.
13. Institute of Medicine (US); Committee on Quality of Health Care in America. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2001.
14. Friedberg MW, Safran DG, Coltin KL, Dresser M, Schneider EC. Readiness for the patient-centered medical home: structural capabilities of Massachusetts primary care practices. J Gen Intern Med. 2009;24(2):162-169.
15. Goldberg DG, Mick SS. Medical home infrastructure: effect of the environment and practice characteristics on adoption in Virginia. Med Care Res Rev. 2010;67(4):431-449.
16. Rittenhouse DR, Casalino LP, Shortell SM, et al. Small and mediumsize physician practices use few patient-centered medical home processes. Health Aff (Millwood). 2011;30(8):1575-1584.
17. Friedberg MW, Coltin KL, Safran DG, Dresser M, Schneider EC. Medical home capabilities of primary care practices that serve sociodemographically vulnerable neighborhoods. Arch Intern Med. 2010;170(11):938-944.
18. Goldberg DG, Kuzel AJ. Elements of the patient-centered medical home in family practices in Virginia. Ann Fam Med. 2009;7(4):301-308.
19. Rittenhouse DR, Casalino LP, Gillies RR, Shortell SM, Lau B. Measuring the medical home infrastructure in large medical groups. Health Aff (Millwood). 2008;27(5):1246-1258.
20. Koller CF, Brennan TA, Bailit, MH. Rhode Island’s novel experiment to rebuild primary care from the insurance side. Health Aff (Millwood). 2010; 29(5), 941-947.
21. Harbrecht MG, Latts LM. Colorado’s Patient-Centered Medical Home Pilot met numerous obstacles, yet saw results such as reduced hospital admissions. Health Aff (Millwood). (2012); 31(9), 2010-2017.
22. Boyatzis, RE. Transforming Qualitative Information: Thematic Analysis and Code Development. Thousand Oaks, CA: Sage; 1998.
23. Scholle SH, Saunders RC, Tirodkar MA, Torda P, Pawlson LG. Patient-centered medical homes in the United States. J Ambul Care Manage. 2011;34(1):20-32.
24. Hollingsworth JM, Saint S, Sakshaug JW, Hayward RA, Zhang L, Miller DC. Physician practices and readiness for medical home reforms: policy, pitfalls, and possibilities. Health Serv Res. 2012;47(1Pt2): 486-508.
25. Singer SJ, Falwell A, Gaba DM, et al. Identifying organizational cultures that promote patient safety. Health Care Manage Rev. 2009;34(4):300-311.
26. Shortell SM, Evashwick C. The structural configuration of US hospital medical staffs. Med Care. 1981;19(4): 419-430.
27. Horbar JD, Plsek PE, Leahy K; NIC/Q 2000. NIC/Q 2000: establishing habits for improvement in neonatal intensive care units. Pediatrics. 2003;111(4Pt2,Supplement E1):e397-e410.
28. Nembhard IM. Learning and improving in quality improvement collaboratives: which collaborative features do participants value most? Health Serv Res. 2009;44(2pt1):359-378.
29. Taylor EF, Machta RM, Meyers DS, Genevro J, Peikes DN. Enhancing the primary care team to provide redesigned care: the roles of practice facilitators and care managers. Ann Fam Med. 2013;11(1):80-83.
30. Shaw EK, Chase SM, Howard J, Nutting PA, Crabtree BF. More black box to explore: how quality improvement collaboratives shape practice change. J Am Board Fam Med. 2012;25(2):149-157.
31. Parmelli E, Flodgren G, Schaafsma ME, Baillie N, Beyer FR, Eccles MP. The effectiveness of strategies to change organisational culture to improve healthcare performance. Cochrane Database Syst Rev: 2011, 19(1):CD008315.
32. Dugan DP, Mick SS, Scholle SH, Steidle EF, Goldberg DG. The relationship between organizational culture and practice systems in primary care. J Ambul Care Manage. 2011;34(1):47-56.
33. Nembhard IM, Singer SJ, Shortell SM, Rittenhouse D, Casalino LP. The cultural complexity of medical groups. Health Care Manage Rev. 2012;37(3):200-213.
34. Friedberg MW, Coltin KL, Safran DG, Dresser M, Zaslavsky AM, Schneider EC. Associations between structural capabilities of primary care practices and performance on selected quality measures. Ann Intern Med. 2009:151(7):456-463.
35. Flottemesch TJ, Fontaine P, Asche SE, Solberg, LI. Relationship of clinic medical home scores to health care costs. J Ambul Care Manage. 2011;34(1):78-89.
36. Solberg LI, Asche SE, Fontaine P, Flottemesch TJ, Pawlson LG, Scholle SH. Relationship of clinic medical home scores to quality and patient experience. J Ambul Care Manage. 2011;34(1):57-66.