Association of a State-Wide Alternative Payment Model for Rural Hospitals With Bypass for Elective Surgeries.

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This study aimed to measure the changes in rural hospital bypass for 11 common elective surgeries following the implementation of the Pennsylvania Rural Health Model (PARHM), a global budget payment model. We leveraged a natural experiment arising from the phase-in of PHARM in Pennsylvania. We conducted a comparative interrupted time series analysis to assess changes in rural hospital bypass, comparing trends in rural hospital bypass among patients in hospital service areas (HSAs) with PARHM-participating hospitals to patients in control HSAs with hospitals eligible for but not participating in PARHM. Analyses accounted for staggered entry into PARHM and examined outcomes up to 4 years post-entry. We used Pennsylvania all-payer visit-level inpatient discharge data (2016-2022) to measure rural hospital bypass, encompassing 175,138 surgeries. The average bypass rate for elective surgeries was 59.9%, with an increasing trend observed during the study period. Overall, differential changes in bypass rates between PARHM-participating and control HSAs were not statistically significant, from a low of 0.53 percentage points (-8.17-9.22) among Cohort 2 HSAs and a high of 5.96 percentage points (-4.63-16.55) among Cohort 1 HSAs. However, among critical access hospitals, PARHM participation was associated with a significant relative increase in levels and trends in bypass rates compared to controls, from a low of 9.12 percentage points (2.45-15.79) among Cohort 1 HSAs and a high of 29.70 percentage points (12.54-46.86) among Cohort 2 HSAs. These relative increases were largely due to a stable rate in PARHM-participating HSAs and a marked decrease in control HSAs. This study fills a gap in the relationship between global budgets and hospital bypass. Although PARHM did not broadly alter rural bypass rates overall, the differential increase in bypass among HSAs with CAHs participating in PARHM suggests meaningful effect heterogeneity, warranting further research and analysis of impacts on patient outcomes.