Development of the Prediction Method for Hospital Bankruptcy using a Hierarchical Generalized Linear Model(HGIM)

HGLM을 적용한 병원 도산 예측방법의 개발

  • Noh, Maeng-Seok (Department of Health Industry Informatics, Korea Health Industry Development Institute) ;
  • Chang, Hye-Jung (Department of Health Services management, Kyung Hee University) ;
  • Lee, Young-Jo (Department of Statistics, Seoul National University)
  • 노맹석 (한국보건산업진흥원 산업정보단) ;
  • 장혜정 (경희대학교 의료경영학과) ;
  • 이명조 (서울대학교 통계학과)
  • Published : 2001.06.30

Abstract

The hospital bankruptcy rate is increasing, therefore it is very important to predict the bankruptcy using the existing hospital management information. The hospital bankruptcy is often measured in year intervals, called grouped duration data, not by the continuous time elapsed to the bankruptcy. This study introduces a hierarchical generalized linear model(HGLM) for analysis of hospital bankruptcy data. The hazard function for each hospital may be influenced by unobservable latent variables, and these unknown variables are usually termed as random effects or frailties which explain correlations among repeated measures of the same hospital and describe individual heterogeneities of hospitals. Practically, the data of twenty bankrupt and sixty profitable hospitals were collected for five years, and were fitted to HGLM. The results were compared with those of the logit model. While the logit model resulted only in the effects of explanatory variables on the bankruptcy status at specific period, the HGLM showed variables with significant effects over all observed years. It is concluded that the HGLM with a fixed ratio and a period of total asset turnrounds was justified, and could find significant within and between hospital variations.

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