The effect of time-varying capacity utilization on 14-day in-hospital mortality: a retrospective longitudinal study in Swiss general hospitals

BMC Health Services Research

Research

Narayan Sharma¹  Michael Simon¹  Dietmar Ausserhofer²  René Schwendimann³  Giusi Moffa⁴  Olga Endrich⁵ 

[1] Department Public Health (DPH), Institute of Nursing Science (INS), University of Basel, Bernoullistrasse 28, 4056, Basel, Switzerland;Department Public Health (DPH), Institute of Nursing Science (INS), University of Basel, Bernoullistrasse 28, 4056, Basel, Switzerland;College of Health Care-Professions Claudiana, Bozen, Italy;Department Public Health (DPH), Institute of Nursing Science (INS), University of Basel, Bernoullistrasse 28, 4056, Basel, Switzerland;Patient Safety Office, University Hospital Basel, Basel, Switzerland;Department of Mathematics and Computer Science, University of Basel, Basel, Switzerland;Directorate of Medicine, Inselspital University Hospital Bern, Bern, Switzerland;

关键词: Causal effect;    Time-varying covariates;    Capacity utilization;    In-hospital mortality;   

DOI  :  10.1186/s12913-022-08950-y

 received in 2022-06-17, accepted in 2022-12-09,  发布年份 2022

来源: Springer

【 摘 要 】

BackgroundHigh bed-occupancy (capacity utilization) rates are commonly thought to increase in-hospital mortality; however, little evidence supports a causal relationship between the two. This observational study aimed to assess three time-varying covariates—capacity utilization, patient turnover and clinical complexity level— and to estimate causal effect of time-varying high capacity utilization on 14 day in-hospital mortality.MethodsThis retrospective population-based analysis was based on routine administrative data (n = 1,152,506 inpatient cases) of 102 Swiss general hospitals. Considering the longitudinal nature of the problem from available literature and expert knowledge, we represented the underlying data generating mechanism as a directed acyclic graph. To adjust for patient turnover and patient clinical complexity levels as time-varying confounders, we fitted a marginal structure model (MSM) that used inverse probability of treatment weights (IPTWs) for high and low capacity utilization. We also adjusted for patient age and sex, weekdays-vs-weekend, comorbidity weight, and hospital type.ResultsFor each participating hospital, our analyses evaluated the ≥85th percentile as a threshold for high capacity utilization for the higher risk of mortality. The mean bed-occupancy threshold was 83.1% (SD 8.6) across hospitals and ranged from 42.1 to 95.9% between hospitals. For each additional day of exposure to high capacity utilization, our MSM incorporating IPTWs showed a 2% increase in the odds of 14-day in-hospital mortality (OR 1.02, 95% CI: 1.01 to 1.03).ConclusionsExposure to high capacity utilization increases the mortality risk of inpatients. Accurate monitoring of capacity utilization and flexible human resource planning are key strategies for hospitals to lower the exposure to high capacity utilization.

【 授权许可】

CC BY   
© The Author(s) 2022

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