Learning from Hospital Financial Distress Associated with Negative Cash Reserves

This study introduces a multivariate distance-based framework for analyzing hospital liquidity stress using three financial indicators: cash reserves, days with negative cash, and accounts receivable. Using Definitive Healthcare data from 2020–2025, the study applies principal component analysis (PCA), Mahalanobis distance, Aitchison distance, and ternary plots to characterize structural relationships among these liquidity variables. The results show that the first two principal components explain more than 94% of the variation in the transformed variables, indicating that the joint financial structure can be represented in a lower-dimensional space. Beginning in 2023, accounts receivable became more geometrically separated from the cash-based variables, suggesting that revenue-cycle dynamics may have become a more independent dimension of hospital liquidity stress. Importantly, this manuscript does not directly predict hospital closure or bankruptcy because verified event/non-event outcome data are not available in the analytic file. Instead, its contribution is methodological and exploratory: it demonstrates how distance-based and compositional methods can identify structural liquidity instability and potential early warning signals that warrant further validation with longitudinal closure, bankruptcy, or severe-distress outcomes.