Adaptive optimization of hospital resource calendars

I.B. Vermeulen, S.M. Bohté, S.G. Elkhuizen, J.S. Lameris, P.J.M. Bakker, J.A. Poutré, La

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

5 Citations (Scopus)

Abstract

As demand for health care increases, a high efficiency on limited resources is necessary for affordable high patient service levels. Here, we present an adaptive approach to efficient resource usage by automatic optimization of resource calendars. We describe a precise model based on a case study at the radiology department of the Academic Medical Center Amsterdam (AMC). We model the properties of the different groups of patients, with additional differentiating urgency levels. Based on this model, we develop a detailed simulation that is able to replicate the known scheduling problems. In particular, the simulation shows that due to fluctuations in demand, the allocations in the resource calendar must be flexible in order to make efficient use of the resources. We develop adaptive algorithms to automate iterative adjustments to the resource calendar. To test the effectiveness of our approach, we evaluate the algorithms using the simulation. Our adaptive optimization approach is able to maintain overall target performance levels while the resource is used at high efficiency.
Original languageEnglish
Title of host publicationProceedings of the 11th Conference on Artificial Intelligence in Medicine (AIME 2007) 7-11 July 2007, Amsterdam, The Netherlands
EditorsR. Belazzi, H. Abu-Hanna, J. Hunter
Place of PublicationBerlin
PublisherSpringer
Pages305-315
ISBN (Print)978-3-540-73598-4
DOIs
Publication statusPublished - 2007
Eventconference; AIME 2007, Amsterdam, The Netherlands; 2007-07-07; 2007-07-11 -
Duration: 7 Jul 200711 Jul 2007

Publication series

NameLecture Notes in Computer Science
Volume4594
ISSN (Print)0302-9743

Conference

Conferenceconference; AIME 2007, Amsterdam, The Netherlands; 2007-07-07; 2007-07-11
Period7/07/0711/07/07
OtherAIME 2007, Amsterdam, The Netherlands

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