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Avoiding Hospital Admissions and Delayed Transfers of Care by Improved Access to Intermediate Care: A Simulation Study
Institution:1. Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands;2. Stochastics group, Centrum Wiskunde & Informatica, Amsterdam, the Netherlands;3. Section of Geriatric Medicine, Department of Internal Medicine, Amsterdam Public Health Research Institute, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
Abstract:ObjectiveThe current waiting times for intermediate care in the Netherlands prohibit timely access, leading to unwanted and costly hospital admissions. We propose alternative policies for improvement of intermediate care and estimate the effects on the waiting times, hospitalization, and the number of patient replacements.DesignSimulation study.Setting and ParticipantsFor our case study, data were used of older adults who received intermediate care in Amsterdam, the Netherlands, in 2019. For this target group, in- and outflows and patient characteristics were identified.MethodsA process map of the main pathways into and out of the intermediate care was obtained and a discrete event simulation (DES) was built. We demonstrate the use of our DES for intermediate care by evaluating possible policy changes for a real-life case study in Amsterdam.ResultsBy means of a sensitivity analysis with the DES, we show that in Amsterdam the waiting times are not a result of a lack in bed capacity but are due to an inefficient triage and application process. Older adults have to wait a median of 1.8 days for admission, leading to hospitalization. If the application process becomes more efficient and evening and weekend admissions are allowed, we find that unwanted hospitalization can be decreased substantially.Conclusion and ImplicationsIn this study, a simulation model is developed for intermediate care that can serve as a basis for policy decisions. Our case study shows that the waiting times for health care facilities are not always solved by increasing bed capacity. This underlines the necessity for a data-driven approach to identify logistic bottlenecks and find the best ways to solve them.
Keywords:Intermediate care  post-acute care  simulation  health care management
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