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PurposeAs the Flex Program celebrates its 25th anniversary, we examined changes in critical access hospital (CAH) financial performance, investigated whether CAH status has reduced hospitals’ financial vulnerability, and identified factors influencing financial performance.MethodsWe collected data on acute care hospitals in Pennsylvania's rural counties for 2000‐20. Our sample contained 1,444 hospital‐year observations. We used trend analysis to compare the financial performance of CAHs and rural prospective payment system (PPS) hospitals (non‐CAHs). We investigated the effect of CAH status on financial performance and identified the time‐variant factors impacting financial performance using fixed‐effects regression analysis.ResultsThe median total margin of CAHs lagged behind that of non‐CAHs. When compared to non‐CAH costs over the same period, the median cost per patient day incurred by CAHs has increased, with the rate of increase being significantly higher in the most recent decade. Our findings show that while CAH status does not appear to have a direct impact on the total margin, it is significantly associated with a higher cost per patient day.ConclusionsCAHs in Pennsylvania appear to be facing a double whammy of declining margins and rising costs compared to non‐CAHs. Our findings demonstrate how crucial the Flex program has been in sustaining CAHs in Pennsylvania ever since its inception. Our findings have implications for rural health care delivery as well. While providing financial support and operational flexibility to CAHs should be a continuing policy priority, a long‐term policy goal should be to envision an economic development strategy that capitalizes on the unique strengths of each of the rural archetypes.

Declining inpatient admissions have serious consequences on hospital financial stability as well as the health of patients. Thus, identifying factors associated with inpatient admissions is crucial to properly manage healthcare services. The major objective of this research is to demonstrate a systematic methodology using regression analysis and no free lunch (NFL) theorem to identify the most significant factors associated with non-COVID-19 ADMs and to identify which of them have deviated from an ideal state of service. This research uses Pennsylvania U.S. hospital data from 2003 to 2018 and identified that bed setup, staffed and supported, average length of stay, occupancy rate, readmission index, and outpatients are significantly associated with ADMs. Further, readmissions and outpatient admissions are found with an unusual association compared to an ideal condition. This paper discusses the steps that U.S. healthcare systems have already implemented and presents improvement recommendations.