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OBJECTIVE: To test the hypothesis that health systems provide better care to patients with high needs by comparing differences in quality between system‐affiliated and nonaffiliated physician organizations (POs) and to examine variability in quality across health systems. DATA SOURCES: 2015 Medicare Data on Provider Practice and Specialty linked physicians to POs. Medicare Provider Enrollment, Chain, and Ownership System (PECOS) and IRS Form 990 data identified health system affiliations. Fee‐for‐service Medicare enrollment and claims data were used to examine quality. STUDY DESIGN: This cross‐sectional analysis of beneficiaries with high needs, defined as having more than twice the expected spending of an average beneficiary, examined six quality measures: continuity of care, follow‐up visits after hospitalizations and emergency department (ED) visits, ED visits, all‐cause readmissions, and ambulatory care‐sensitive hospitalizations. Using a matched‐pair design, we estimated beneficiary‐level regression models with PO random effects to compare quality of care in system‐affiliated and nonaffiliated POs. We then limited the sample to system‐affiliated POs and estimated models with system random effects to examine variability in quality across systems. PRINCIPAL FINDINGS: Among 2 323 301 beneficiaries with high needs, 52.3% received care from system‐affiliated POs. Rates of ED visits were statistically significantly different in system‐affiliated POs (117.5 per 100) and nonaffiliated POs (106.8 per 100, P

OBJECTIVE: To understand the process of practice transformation by identifying pathways for attaining patient‐centered medical home (PCMH) recognition. DATA SOURCES/STUDY SETTING: The CMS Federally Qualified Health Center (FQHC) Advanced Primary Care Practice Demonstration was designed to help FQHCs achieve NCQA Level 3 PCMH recognition and improve patient outcomes. We used a stratified random sample of 20 (out of 503) participating sites for this analysis. STUDY DESIGN: We developed a conceptual model of structural, cultural, and implementation factors affecting PCMH transformation based on literature and initial qualitative interview themes. We then used conventional cross‐case analysis, followed by qualitative comparative analysis (QCA), a cross‐case method based on Boolean logic algorithms, to systematically identify pathways (i.e., combinations of factors) associated with attaining—or not attaining—Level 3 recognition. DATA COLLECTION METHODS: Site‐level indicators were derived from semistructured interviews with site leaders at two points in time (mid‐ and late‐implementation) and administrative data collected prior to and during the demonstration period. PRINCIPAL FINDINGS: The QCA results identified five distinct pathways to attaining PCMH recognition and four distinct pathways to not attaining recognition by the end of the demonstration. Across these pathways, one condition (change leader capacity) was common to all pathways for attaining recognition, and another (previous improvement or recognition experience) was absent in all pathways for not attaining recognition. In general, sites could compensate for deficiencies in one factor with capacity in others, but they needed a threshold of strengths in cultural and implementation factors to attain PCMH recognition. CONCLUSIONS: Future efforts at primary care transformation should take into account multiple pathways sites may pursue. Sites should be assessed on key cultural and implementation factors, in addition to structural components, in order to differentiate interventions and technical assistance.

Objective To compare performance between Medicare Advantage (MA) and Fee-for-Service (FFS) Medicare during a time of policy changes affecting both programs. Data Sources/Study Setting Performance data for 16 clinical quality measures and 6 patient experience measures for 9.9 million beneficiaries living in California, New York, and Florida. Study Design We compared MA and FFS performance overall, by plan type, and within service areas associated with contracts between CMS and MA organizations. Case mix-adjusted analyses (for measures not typically adjusted) were used to explore the effect of case mix on MA/FFS differences. Data Collection/Extraction Methods Performance measures were submitted by MA organizations, obtained from the nationwide fielding of the Medicare Consumer Assessment of Healthcare Providers and Systems (MCAHPS) Survey, or derived from claims. Principal Findings Overall, MA outperformed FFS on all 16 clinical quality measures. Differences were large for HEDIS measures and small for Part D measures and remained after case mix adjustment. MA enrollees reported better experiences overall, but FFS beneficiaries reported better access to care. Relative to FFS, performance gaps were much wider for HMOs than PPOs. Excluding HEDIS measures, MA/FFS differences were much smaller in contract-level comparisons. Conclusions Medicare Advantage/Fee-for-Service differences are often large but vary in important ways across types of measures and contracts.

RESEARCH OBJECTIVE: A clinically integrated network is a group of health care providers that join together for the stated purpose of improving care and reducing costs. The Federal Trade Commission has established standards for clinically integrated networks for purposes of determining whether cooperation among otherwise competing organizations to jointly negotiate fees runs afoul of antitrust law. However, little is known about how CINs are implemented on the ground and how health systems use CINs to compete in health care markets. STUDY DESIGN: We conducted explanatory case studies of 24 health systems using in‐depth interviews of c‐suite executives (n = 162), descriptive surveys, and document review. The interview protocols focused on topics such as market context; origin of the health system; structural organization and governance; and the influence of the health system on hospital and physician organization operations. We developed a codebook based on the interview guides. After a multistage process of testing and refining codes, two researchers independently coded the interview data. A high threshold of interrater reliability was achieved (pooled kappa across all codes was 0.84). We used comparative case study analysis to compare and contrast the development of CINs in our sample of health systems. POPULATION STUDIED: Using secondary data sources, we identified the health system affiliations of all physician organizations publicly reporting performance data in four states that host a health care measurement and improvement collaborative. From the universe of health systems, we selected a purposive sample of 24 health systems to achieve variability on important attributes (eg, size and performance). PRINCIPAL FINDINGS: Respondents in half of the health systems described the use of a CIN, although the organizational structures and the functions of the CINs varied widely. CINs can be classified into three basic types—those made up of primarily closely affiliated practices, those made up of primarily loosely affiliated practices, and those that represent partnerships among health systems. CONCLUSIONS: Health systems are using CINs to adapt to competitive environments and changing payment policies in several ways. CINs allow health systems to (1) move care into lower‐cost settings while retaining referral pathways for their tertiary facilities; (2) extend their geographic reach without the capital and administrative costs of acquiring and onboarding; (3) maximize negotiating leverage while reducing contracting burden; and (4) offer advantages (such as EHR and quality reporting support) to physicians while allowing them to remain in independent practice. IMPLICATIONS FOR POLICY OR PRACTICE: Research on competition in health care markets has concentrated on mergers and acquisitions; however, many health systems have begun to use an affiliation approach to expansion and integration with other providers in their market. This approach allows independent physician practices to benefit from some of the strengths of a larger HS without capital outlays or administrative burden to the HS, and to reduce transactional costs for the providers. It remains unclear whether this new model of integration is achieving the purported objectives of improved quality and reduced costs. CINs may have the same negative impact on health care prices as have traditional mergers and acquisitions, and will face considerable challenges in coordinating care across providers that are not fully integrated. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality.