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美国医院破产的预测因素 - 一个多模型比较
Brad Beauvais1, Zo Ramamonjiarivelo2, C Scott Kruse3
1Texas State University, School of Health Administration, Encino Hall, Room 250 A, 601 University Drive, San Marcos, TX, 78666, USA. bmb230@txstate.edu.
Health care management science
|February 21, 2026
概括
一个新的医院破产预测模型 (BRKFSST) 准确地识别了有风险的医疗机构. 这种可解释的模型有助于领导者防止财务崩,并确保患者继续获得护理.
科学领域:
- 医疗保健管理的管理
- 金融风险评估 金融风险评估
- 卫生经济学 卫生经济学
背景情况:
- 越来越多的医院破产对美国医疗保健的获得构成重大威胁.
- 现有的破产预测模型缺乏医疗保健特定的细微差别和预测准确性.
- 迫切需要一个定制的,可解释的模型来预测医院的财务困境.
研究的目的:
- 开发和验证一个新的,可解释的,医院特定的破产预测模型.
- 将新模型的性能与传统的破产预测工具进行比较.
- 确定医院破产的主要财务和运营预测因素.
主要方法:
- 利用了3091家短期急性护理医院 (2008-2021) 的纵向数据集.
- 开发了一个物流回归模型 (BRKFSST),结合了30多个财务和医院级变量.
- 对于真正的样本外预测,滞后的未知变量与阿尔特曼的Z',Ohlson的O-score和Zmijewski的模型相比较.
主要成果:
- BRKFSST模型表现出卓越的性能,AUC为81.8%,均衡精度为72.2%.
- 在预测医院财务困境方面,BRKFSST的表现优于传统的破产预测模型.
- 确定的关键预测因素包括劳动报酬比率,调整的患者日和质量评级.
结论:
- 开发的BRKFSST模型为预测医院破产提供了一个可靠和可解释的工具.
- 调查结果为医院领导人和政策制定者提供了可操作的见解,以实施早期干预.
- 该模型支持防止金融崩的努力,并保持获得基本医疗保健服务的机会.
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