School of Management, Kyung Hee University, Seoul 02447, Republic of Korea.
Department of Bigdata Analytics, Kyung Hee University, Seoul 02447, Republic of Korea.
Int J Environ Res Public Health. 2024 Oct 26;21(11):1424. doi: 10.3390/ijerph21111424.
With the increase in insured patients and an aging population, managing the length of stay (LOS) for inpatients has become crucial for controlling medical costs. Analyzing the factors influencing LOS is necessary for effective management. Previous studies often used multiple or logistic regression analyses, which have limitations such as unmet assumptions and the inability to handle time-dependent variables. To address these issues, this study applied survival analysis to examine the factors affecting LOS using the National Health Insurance Service (NHIS) sample cohort data from 2016 to 2019, covering over 4 million records. We used Kaplan-Meier survival estimation to assess LOS probabilities based on sociodemographic, patient, health checkup, and institutional characteristics. Additionally, the Cox proportional hazards model controlled for confounding factors, providing more robust validation. Key findings include the influence of age, gender, type of insurance, and hospital type on LOS. For instance, older patients and medical aid recipients had longer LOS, while general hospitals showed shorter stays. This study is the first in Korea to use survival analysis with a large cohort database to identify LOS determinants. The results provide valuable insights for shaping healthcare policies aimed at optimizing inpatient care and managing hospital resources more efficiently.
随着参保患者人数的增加和人口老龄化，管理住院患者的住院时间（LOS）对于控制医疗成本变得至关重要。分析影响 LOS 的因素对于有效管理是必要的。先前的研究通常使用多元或逻辑回归分析，这些方法存在未满足的假设和无法处理时变变量等局限性。为了解决这些问题，本研究应用生存分析，使用 2016 年至 2019 年国家健康保险服务（NHIS）样本队列数据，涵盖超过 400 万条记录，来检查影响 LOS 的因素。我们使用 Kaplan-Meier 生存估计来评估基于社会人口统计学、患者、健康检查和机构特征的 LOS 概率。此外，Cox 比例风险模型控制了混杂因素，提供了更稳健的验证。主要发现包括年龄、性别、保险类型和医院类型对 LOS 的影响。例如，老年患者和医疗救助受助人的 LOS 更长，而综合医院的住院时间更短。这项研究是韩国首次使用生存分析和大型队列数据库来确定 LOS 决定因素。研究结果为制定旨在优化住院患者护理和更有效地管理医院资源的医疗政策提供了有价值的见解。
