Rural Hospitals that Closed between 2017‐20: Profitability and Liquidity in the Year Before Closure


In a 2017 article, we presented the Financial Distress Index (FDI). The FDI is an algorithm that uses historical data about hospital financial performance, government reimbursement, organizational characteristics, and market characteristics to predict the current risk of financial distress. The model assigns every rural hospital to one of four financial risk categories: high, mid‐high, mid‐low, or low. Two measures in the FDI that are important predictors of financial distress are profitability and liquidity. The purpose of this study is to gain some insight into the importance of these single measures as immediate precursors of rural hospital closure. In this brief, we use Centers for Medicare & Medicaid Services Healthcare Cost Report Information System data to examine the preclosure profitability and liquidity performance of rural hospitals that closed between 2017‐20 and compare it to the median performance of rural hospitals that remained open during the same year.

The NC Rural Health Research Program has tracked rural hospital closures since 2012. Complete closures are defined as facilities that no longer provide healthcare services and converted closures are defined as facilities that no longer provide inpatient care, but continue to provide some healthcare services (e.g., primary care, skilled nursing care, rehabilitation care). In this study, we analyzed 56 rural hospitals that closed between January 2017 and August 2020 and found that:

  • The closed hospitals were clustered in the Southeast and South‐central census divisions.
  • In the year before closure, most rural hospitals had a negative operating margin, negative total margin, and few days cash on hand.
  • In comparison with rural hospitals that remained open between 2017‐20, most rural hospitals that closed were much more unprofitable and much less liquid.
North Carolina Rural Health Research and Policy Analysis Center, Rapid Response to Requests for Rural Data Analysis
Andrew Osgood, George Pink