医院床位容量战略规划的长期预测与仿真模型

IF 1.5 Q3 HEALTH CARE SCIENCES & SERVICES Operations Research for Health Care Pub Date : 2023-03-01 DOI:10.1016/j.orhc.2022.100375
Timo Latruwe , Marlies Van der Wee , Pieter Vanleenhove , Joke Devriese , Sofie Verbrugge , Didier Colle
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引用次数: 4

摘要

不断增长的医疗保健需求利用了有效利用资源的潜在节省。为此目的,ProMoBed是一个全面的模式,支持住院医院床位容量的战略规划。该模型由外推和仿真组成,外推为仿真提供输入。外推模型预测了入院率和病理组的平均住院时间,并校正了人口统计学的变化。随后,仿真模型对床位容量需求进行仿真,并提出基于服务水平的床位容量建议。此外,该模型使用Shapley值原理来分解不同原因对住院天数需求的影响。外推模型的结果应用于比利时地区,显示住院日需求演变的预期差异。
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A long-term forecasting and simulation model for strategic planning of hospital bed capacity

Growing healthcare needs leverage the potential savings of using resources efficiently. To that end, ProMoBed is a comprehensive model that supports strategic planning of bed capacity in inpatient hospitals. The model consists of an extrapolation and simulation component, the former supplying input for the latter. The extrapolation model forecasts admission rates and the average Length of Stay for pathology groups, and corrects for demographic changes. Subsequently, the simulation model emulates the demand for bed capacity, and makes service-level based bed capacity suggestions. Additionally, the model uses the Shapley value principle to disaggregate the effects on demand for inpatient days due to different causes. Results from the extrapolation model are applied to regions in Belgium, showing expected divergence in inpatient day demand evolution.

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来源期刊
Operations Research for Health Care
Operations Research for Health Care HEALTH CARE SCIENCES & SERVICES-
CiteScore
3.90
自引率
0.00%
发文量
9
审稿时长
69 days
期刊最新文献
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