Implementing Effective Care Management in the Patient-Centered Medical Home
Published Online: December 12, 2013
Catherine A. Taliani, BS; Patricia L. Bricker, MBA; Alan M. Adelman, MD, MS; Peter F. Cronholm, MD, MSCE, FAAFP; and Robert A. Gabbay, MD, PhD
The patient-centered medical home (PCMH) is a new and increasingly widespread1 model of healthcare delivery that shows significant promise for improving patient care. The PCMH emphasizes team-based care, coordinated and integrated care, and whole-person care,2,3 and has been associated with improved measures of quality care and cost reduction.4,5 The process of becoming a PCMH involves practice transformation often centered on the development of a care management plan and infrastructure.6-9
Care management involves more intensely caring for high-risk patients through the establishment and monitoring of care plans, more frequent follow-up visits, regular outreach between office visits to assess health status, extensive support for disease management and self-care, tracking and coordination of specialty and other services, and linkages with community resources.10,11
Care management has traditionally been conducted by insurer-based nurses providing telephonic outreach to patients identified as either high cost or high risk by claims-based predictive modeling software. However, this method has provided inconsistent care improvement results.12,13 Some successful models of care management include community-based care managers,14,15 health plan care managers embedded in primary care practices,16 and health system–based nurse teams working with primary care practices.17,18
This study examined the development of care management within 25 heterogeneous primary care practices in southeastern Pennsylvania implementing the PCMH focused initially on improving diabetes care. Diabetes is a common chronic disease used as a starting point for many PCMH initiatives.19 A recent review described team-based care and care management as critical components in improving the care of patients with chronic conditions such as diabetes.20 With care management and team-based care both representing key elements of the PCMH3 and growing evidence that practice-based care management is highly effective in improving clinical quality and reducing costly healthcare utilization,21,22 it is important to better understand the implementation of care management in primary care practices. Although care management is an important addition to primary care, there is tremendous variation in the definition and implementation of the role at the practice level, making the implementation of care management an important research topic. This is one of the first studies to explore how a disparate group of unaffiliated primary care practices embedded care management within the team care environment of a PCMH. We used a positive deviance approach contrasting care management implementation in higher- and lower-performing practices to identify a collection of potential best practices synthesized from individual higherperforming practices.
The practices studied were part of the first regional rollout of a statewide, multipayer PCMH initiative consisting of regional learning collaborative meetings, practice facilitation support, and monthly clinical data and narrative reports describing PCMH and care management implementation. All 25 practices were recognized PCMHs by the National Committee on Quality Assurance (NCQA), and 6 regional payers provided pro rata payments to the practices to support PCMH and care management implementation. Practices were expected to take an all-payer approach to population management, including planned chronic and preventive care for all patients and, specific to this study, care management for the highest risk patients. Using a positive deviance method, performed by calculating high and low performance on standard measures of diabetes management and developing hypotheses related to the description of top-performing practices,23,24 we analyzed and characterized care management implementation in the PCMH setting. We aimed to identify best practices for primary care sites seeking to develop embedded care management services.
This mixed-methods study involved (1) rank-ordering the sites based on practice-reported diabetes data to determine the highest and lowest performing practices and (2) analyzing qualitative data collected from interviews to contrast care management implementation in high- and low-performing practices.
Positive Deviance Stratification
The highest and lowest performing practices were identified using practice-reported diabetes data, the initial clinical focus of the statewide initiative. The 25 practices participating in the collaborative were ranked according to their improvement from baseline to 18 months across 3 diabetes performance measures most closely associated with minimizing morbidity and mortality: the percentage of diabetes patients (1) whose latest glycated hemoglobin (A1C) result was less than 7%, (2) whose blood pressure was less than 130/80 mm Hg, and (3) whose low-density lipoprotein cholesterol was less than 100 mg/dL. The resulting improvement index was calculated as the arithmetic mean of the absolute percentage improvement in the 3 clinical diabetes measures. Practices were divided into performance tertiles based on their calculated improvement index. The improvement indexes were statistically significantly different between performance tertiles (1-way analysis of variance P <.001).
Semistructured interviews were conducted with 136 individuals, including clinicians (n = 56), practice managers (n = 15), care managers (n = 13), and other staff (n = 52), in 21 of the 25 practices. Interviews were framed by interview guides with extra questions related to finances for practice leaders and office administrators. Interviews were conducted by 2 teams of 2 trained researchers, with 1 person asking questions and the other taking notes. Both teams followed the same semistructured interview guide and recorded notes from the interviews that were used to assess and ensure inter-observer consistency within and across the interviewer teams. In addition, members of the 2 interviewer teams each observed 1 of the other team’s on-site interview sessions to identify and address any differences in interviewer style or delivery of the questions. Members of both interviewer teams also participated in weekly team meetings to review discrepancies and reach consensus. Most interviews were conducted on-site, during office hours, in private locations. Additional interviews were conducted through focus groups or phone calls if key personnel were not available in person. Participants were not compensated for their interview time.
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