Centre hospitalier de St Philibert, Lomme, France.
Faculté de Gestion, d'Economie et de Sciences, Institut catholique de Lille, Lille, France.
J Hosp Infect. 2018 Jan;98(1):29-35. doi: 10.1016/j.jhin.2017.08.023. Epub 2017 Sep 7.
Nosocomial infections place a heavy burden on the healthcare system. However, quantifying the burden raises many questions, ranging from the way to accurately estimate the extra length of stay at hospital to defining and costing the preventive methods among the different care providers.
To estimate the cost of nosocomial infection by C. difficile to inform the hospital managers.
Multi-state modelling based on Markov processes and bootstrapping was used to derive individual estimates of the prolongation of stay at hospital associated with Clostridium difficile infection (CDI). Indicators of cost for hospitals were then computed, including an estimation of the productivity losses derived from diagnosis-related group (DRG)-based payment systems. Patients were aged ≥55 years, admitted in two hospital facilities in Lille, with and without an episode of CDI from January 1, 2013 to September 15, 2014.
A total of 52 episodes were screened during the study period. The estimated mean cost of CDI was approximately €23,909 (SD: 17,458) for an extended length of hospital stay (N = 27). In the case of a reduced length of hospital stay (N = 25), the mean cost was approximately €-14,697 (SD: 16,936), which represents net savings for the hospitals. The main cost/savings driver was the productivity losses/gains resulting from the nosocomial infection. A sensitivity analysis showed that the main factor explaining the amount of costs or savings due to nosocomial infections was the length of the hospital stay.
The notion of productivity gains in the case of deaths as a factor revealing the incompleteness of the payment systems is discussed, followed by the methodological issues associated with the statistical method used to control for temporality bias.
医院感染给医疗系统带来了沉重的负担。然而,在量化负担时,会出现许多问题,包括如何准确估计医院的额外住院时间,以及如何在不同的医疗服务提供者中定义和计算预防方法的成本。
估算艰难梭菌感染(CDI)给医院带来的成本,为医院管理人员提供信息。
基于马尔可夫过程和自举的多状态模型用于得出与艰难梭菌感染相关的住院时间延长的个体估计值。然后计算了医院的成本指标,包括基于诊断相关组(DRG)的支付系统产生的生产力损失的估计值。患者年龄≥55 岁,于 2013 年 1 月 1 日至 2014 年 9 月 15 日期间在里尔的两家医院设施中住院,有无 CDI 发作。
在研究期间共筛选出 52 例 CDI 发作。估计 CDI 的平均费用约为 23909 欧元(SD:17458 欧元),用于延长住院时间(N=27)。在缩短住院时间的情况下(N=25),平均费用约为-14697 欧元(SD:16936 欧元),这代表医院的净节省。主要的成本/节省驱动因素是医院感染导致的生产力损失/收益。敏感性分析表明,导致医院感染相关成本或节省的主要因素是住院时间。
讨论了将死亡的生产力收益作为揭示支付系统不完整性的因素的概念,随后讨论了与用于控制时间偏差的统计方法相关的方法学问题。