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Erik Giesen, Wolfgang Ketter, and Rob Zuidwijk. An Agent-based Analysis Approach to Resource Allocation in the Dutch Youth Health Care System. In Proceedings of the Nineteenth Workshop on Information Systems and Technology (WITS-09), pp. –, Phoenix, Arizona, USA, December 2009.
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We study the effect of using different patient allocation preference behaviors in the Dutch youth health care sector by performing sensitivity analysis on an agent-based simulation model. This model is based on an authentic business case and is parameterized with real world market data. This is in contrast with most related research in health care where methods such as queuing theory are applied that fail to address the complexity of the health care industry. Indeed, our simulation approach addresses the complexities of the patient allocation that were found in the real world case and incorporates, among others, a withdrawal and return mechanism, a non-stationary Poisson arrival process, and an algorithm to include the preference behavior of the care providers. The analysis further includes various benchmarks such as an empirical preference algorithm based on discussions with field expert to match the real world scenario, and based on rational decision rules. In particular, we compare the performance when the patient allocation preference is either based solely on waiting time or solely on expected treatment time or a combined approach. We discuss the impact of choosing one preference model above the other when studying real world behavior by means of simulation and show that the effect of using a too simplistic preference algorithm in analysis can results in invalid conclusions or unacceptable recommendations.
@InProceedings{Giesen09WITS,
author = "Erik Giesen and Wolfgang Ketter and Rob Zuidwijk",
title = "An Agent-based Analysis Approach to Resource Allocation in the Dutch Youth Health Care System",
booktitle = "Proceedings of the Nineteenth Workshop on Information Systems and Technology (WITS-09)",
pages = "-",
year = "2009",
address = {Phoenix, Arizona, USA},
month = {December},
abstract={We study the effect of using different patient allocation
preference behaviors in the Dutch youth health care sector by performing
sensitivity analysis on an agent-based simulation model. This model is based
on an authentic business case and is parameterized with real world market
data. This is in contrast with most related research in health care where
methods such as queuing theory are applied that fail to address the
complexity of the health care industry. Indeed, our simulation approach
addresses the complexities of the patient allocation that were found in the
real world case and incorporates, among others, a withdrawal and return
mechanism, a non-stationary Poisson arrival process, and an algorithm to
include the preference behavior of the care providers. The analysis further
includes various benchmarks such as an empirical preference algorithm based
on discussions with field expert to match the real world scenario, and based
on rational decision rules. In particular, we compare the performance when
the patient allocation preference is either based solely on waiting time or
solely on expected treatment time or a combined approach. We discuss the
impact of choosing one preference model above the other when studying real
world behavior by means of simulation and show that the effect of using a too
simplistic preference algorithm in analysis can results in invalid
conclusions or unacceptable recommendations.},
bib2html_pubtype = {Refereed Workshop/Symposium},
bib2html_rescat = {Agents: Health Care},
}
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