The Journal of ambulatory care management · 2026
The Association Between Federally Qualified Health Centers' Payer Mix and Clinical Outcomes Pre- and Post-COVID-19.
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Upadhye Devdutt, Alzeen Mohammed, Zuparova Dilorom, Cendoma Philip, Borkowski Nancy
Аннотация
OBJECTIVE: Federally Qualified Health Centers (FQHCs) serve as critical safety net providers for over 30 million patients annually, operating with diverse payer mixes that create unique financial and operational challenges. This study examined associations between payer mix patterns and clinical quality outcomes in FQHCs, comparing relationships between 2019 and 2022 to capture COVID-19-related coverage transitions.
METHODS: Using Resource Dependence Theory, we conducted a repeated cross-sectional analysis of Uniform Data System data from 1,190 FQHCs in 2019 and 1,150 FQHCs in 2022, examining eight clinical quality measures before (2019) and after (2022) the pandemic-driven coverage shifts. Multiple linear regression models with state-clustered robust standard errors assessed associations between payer mix proportions (Medicaid, Medicare, uninsured, with private insurance as reference) and quality performance, controlling for organizational characteristics.
RESULTS: Results revealed complex, evolving relationships between payer mix and quality. In 2019, a 10 percentage point (pp) increase in Medicaid proportion was associated with lower performance on tobacco screening (-1.64 pp, p =.004), statin therapy (-1.43 pp, p = .014), and colorectal screening (-1.91 pp, p = .010). By 2022, tobacco screening associations reversed, with Medicaid (0.94 pp, p = .023) and uninsured (1.35 pp, p = .009) populations showing better performance than the privately insured. For outcome measures, higher proportions of Medicaid and uninsured patients were consistently associated with more patients with uncontrolled diabetes across both years, while higher Medicare proportions were associated with fewer patients with uncontrolled diabetes. Larger FQHCs showed better performance on process measures, while rural location was associated with lower cervical cancer screening rates but better hypertension control.
CONCLUSIONS: These findings suggest that payer mix associations with quality are neither uniform nor stable over time, challenging assumptions about resource munificence and organizational performance in safety net settings. Policymakers should consider the dynamic nature of payer mix associations when designing payment models and quality improvement initiatives for FQHCs.
METHODS: Using Resource Dependence Theory, we conducted a repeated cross-sectional analysis of Uniform Data System data from 1,190 FQHCs in 2019 and 1,150 FQHCs in 2022, examining eight clinical quality measures before (2019) and after (2022) the pandemic-driven coverage shifts. Multiple linear regression models with state-clustered robust standard errors assessed associations between payer mix proportions (Medicaid, Medicare, uninsured, with private insurance as reference) and quality performance, controlling for organizational characteristics.
RESULTS: Results revealed complex, evolving relationships between payer mix and quality. In 2019, a 10 percentage point (pp) increase in Medicaid proportion was associated with lower performance on tobacco screening (-1.64 pp, p =.004), statin therapy (-1.43 pp, p = .014), and colorectal screening (-1.91 pp, p = .010). By 2022, tobacco screening associations reversed, with Medicaid (0.94 pp, p = .023) and uninsured (1.35 pp, p = .009) populations showing better performance than the privately insured. For outcome measures, higher proportions of Medicaid and uninsured patients were consistently associated with more patients with uncontrolled diabetes across both years, while higher Medicare proportions were associated with fewer patients with uncontrolled diabetes. Larger FQHCs showed better performance on process measures, while rural location was associated with lower cervical cancer screening rates but better hypertension control.
CONCLUSIONS: These findings suggest that payer mix associations with quality are neither uniform nor stable over time, challenging assumptions about resource munificence and organizational performance in safety net settings. Policymakers should consider the dynamic nature of payer mix associations when designing payment models and quality improvement initiatives for FQHCs.