Using interpretable survival analysis to assess hospital length of stay

• DOI: 10.1186/s12913-025-12852-0
• Publication Date: 2025-05-22T03:52:48Z
• Authors: Yan Li; Trevor Hall; Fahad Razak; Amol Verma; Mark Chignell; Lu Wang
• Keywords: Health administration

Abstract Accurate in-hospital length of stay prediction is a vital quality metric for hospital leaders and health policy decision-makers. It assists with decision-making informs operations involving factors such as patient flow, elective cases, human resources allocation, while also informing care risk considerations. The aim the research reported in this paper to use survival analysis model General Internal Medicine (GIM) stay, Shapley value support interpretation resulting model. Survival aims predict time until specific event occurs. In our study, we duration from admission discharge home, i.e., stay. addition discussing modeling results, talk about how can be used guide improvements efficiency development metrics.