Importance Throughout the past decades, the United States healthcare system has seen increased efforts to promote resilience to external or internal stressors. However, measuring outcomes remains a challenge, mainly because most indices rely on markers that need to be gathered from different data sources. An alternative would be to use readily available large-scale data. The American Hospital Association (AHA) annual survey gathers over 1,000 data points from more than 6,000 hospitals. The RAND corporation provides information on the financial health and viability of hospitals and health care systems. Objective Our study aimed to establish and psychometrically validate a new Hospital Resilience Index. Design We took the two databases as primary data sources, and defined hospital closure as the main negative outcome. We performed descriptive statistics, and regression analysis of the databases. Main outcomes and Measures Likelihood of hospital closure. Results Our findings show that a combination of eleven variables is strongly associated with the likelihood of hospital closure. These factors mirror smaller hospital size, lack of ancillary functions, staffing structure of the hospital, size of facilities, number of surgeries performed, Medicare discharges, operating expenses, and medical school affiliation as a teaching hospital. We further classified hospitals with a low HRI (<25) or high HRI (>25). In this setup, we found that both hospitals with a low HRI and hospitals that would subsequently close were characterized by smaller patient census, smaller numbers of surgeries, fewer beds, a smaller staff, and a lower operating margin. Conclusions and Relevance Together, these factors would point to a higher resilience to external stressors in larger, more expanded hospitals and healthcare systems, offering a broad range of services, and having a higher operating margin. The higher tiers of the healthcare system therefore seem to have more resilience, but the recent Covid-19 pandemic exhibited how much all tiers in the system are needed to respond to extraordinary crises such as pandemics or large natural disasters. Future research should seek to determine whether tracking the HRI over time may be a tool to identify hospitals at risk of closure.

The authors have declared no competing interest.

Supported by seed grants of Northeastern University and Brigham and Women's Hospital to Philipp Lirk.

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Data analysis plans are available, data itself is from a database (AHA/RAND) that requires purchase of the data, so individual data will not be available.