Mohammadi Hamed, Marateb Hamid Reza, Momenzadeh Mohammadreza, Wolkewitz Martin, Rubio-Rivas Manuel
Biomedical Engineering Department, Engineering Faculty, University of Isfahan, Isfahan 81746-73441, Iran.
Department of Automatic Control (ESAII), Biomedical Engineering Research Centre (CREB), Universitat Politèncicna de Catalunya (UPC), 08028 Barcelona, Spain.
Life (Basel). 2024 Sep 21;14(9):1195. doi: 10.3390/life14091195.
This study aims to develop and apply multistate models to estimate, forecast, and manage hospital length of stay during the COVID-19 epidemic without using any external packages. Data from Bellvitge University Hospital in Barcelona, Spain, were analyzed, involving 2285 hospitalized COVID-19 patients with moderate to severe conditions. The implemented multistate model includes transition probabilities and risk rates calculated from transitions between defined states, such as admission, ICU transfer, discharge, and death. In addition to examining key factors like age and gender, diabetes, lymphocyte count, comorbidity burden, symptom duration, and different COVID-19 waves were analyzed. Based on the model, patients hospitalized stay an average of 11.90 days before discharge, 2.84 days before moving to the ICU, or 34.21 days before death. ICU patients remain for about 24.08 days, with subsequent stays of 124.30 days before discharge and 35.44 days before death. These results highlight hospital stays' varying durations and trajectories, providing critical insights into patient flow and healthcare resource utilization. Additionally, it can predict ICU peak loads for specific subgroups, aiding in preparedness. Future work will integrate the developed code into the hospital's Health Information System (HIS) following ISO 13606 EHR standards and implement recursive methods to enhance the model's efficiency and accuracy.
本研究旨在开发并应用多状态模型，在不使用任何外部软件包的情况下，估计、预测和管理新冠疫情期间的住院时长。对西班牙巴塞罗那贝尔维奇大学医院的数据进行了分析，涉及2285名中重度新冠住院患者。所实施的多状态模型包括根据定义状态之间的转换计算得出的转移概率和风险率，这些状态如入院、转入重症监护病房（ICU）、出院和死亡。除了研究年龄、性别等关键因素外，还分析了糖尿病、淋巴细胞计数、合并症负担、症状持续时间以及不同的新冠疫情波次。基于该模型，住院患者出院前平均住院11.90天，转入ICU前平均住院2.84天，死亡前平均住院34.21天。ICU患者平均住院约24.08天，随后出院前平均住院124.30天，死亡前平均住院35.44天。这些结果突出了住院时长和病程的差异，为患者流向和医疗资源利用提供了关键见解。此外，它可以预测特定亚组的ICU高峰负荷，有助于做好准备。未来的工作将按照ISO 13606电子健康记录（EHR）标准，将开发的代码集成到医院的健康信息系统（HIS）中，并实施递归方法以提高模型的效率和准确性。
