Bruyneel Arnaud, den Bulcke Julie Van, Leclercq Pol, Pirson Magali
Health Economics, Hospital Management and Nursing Research Deptment, School of Public Health, Université Libre de Bruxelles - Bruxelles, Belgium.
Crit Care Sci. 2025 Jan 27;37:e20250207. doi: 10.62675/2965-2774.20250207. eCollection 2025.
This study aimed to explore the association between high outliers and intensive care unit admissions and to identify the factors contributing to high intensive care unit costs.
This retrospective cohort study used data from 17 Belgian hospitals from 2018 and 2019. The study focused on the 10 most frequently admitted diagnosis-related groups in the intensive care unit. The dataset included medical discharge summaries and cost per stay from the hospital perspective.
A total of 39,279 hospital stays were analyzed, 11,124 of which were intensive care unit admissions; additionally, 2,500 of these stays were high outliers. The proportion of high outliers was significantly greater in the intensive care unit group, and admission to the intensive care unit was significantly associated with high outliers in the multivariate analyses. Factors associated with high intensive care unit outliers included the medical diagnosis-related group category, patients from nursing homes, intensive care unit stay duration exceeding 4 days, and specific technical procedures (measurement of intracranial pressure, continuous hemofiltration, and mechanical ventilation).
Admission to the intensive care unit increases the likelihood of being classified as an outlier, thus significantly impacting hospital costs. This study identified factors that can be used to predict intensive care unit outliers, which can enable adjustments to diagnosis-related group-based funding for intensive care units.
本研究旨在探讨高费用异常值与重症监护病房(ICU)收治之间的关联,并确定导致ICU高费用的因素。
这项回顾性队列研究使用了2018年和2019年来自17家比利时医院的数据。该研究聚焦于ICU中10个最常收治的诊断相关组。数据集包括医院角度的医疗出院小结和每次住院费用。
共分析了39279次住院,其中11124次为ICU收治;此外,这些住院中有2500次为高费用异常值。高费用异常值在ICU组中的比例显著更高,在多变量分析中,入住ICU与高费用异常值显著相关。与ICU高费用异常值相关的因素包括医疗诊断相关组类别、来自养老院的患者、ICU住院时间超过4天以及特定技术操作(颅内压测量、连续性血液滤过和机械通气)。
入住ICU会增加被归类为异常值的可能性,从而对医院成本产生重大影响。本研究确定了可用于预测ICU异常值的因素,这有助于调整基于诊断相关组的ICU资金分配。