Optimizing the strategic patient mix
P.T. Vanberkel, Richardus J. Boucherie, Elias W. Hans, Johann L. Hurink
Faculty of Behavioural, Management and Social Sciences
Stochastic Operations Research
Center for Healthcare Operations Improvement and Research
Discrete Mathematics and Mathematical Programming
In this paper we address the decision of choosing a patient mix for a hospital that leads to the most beneficial treatment case mix. We illustrate how capacity, case mix and patient mix decisions are interrelated and how understanding this complex relationship is crucial for achieving the maximum benefit from the fee-for-service financing system. Although studies to determine the case mix that is of maximum benefit exist in the literature, the hospital actions necessary to realize this case mix has seen less attention. We model the hospital as an $M/G/\infty$ queueing system to evaluate the impact of accepting certain patient types. Using this queueing model to generate the parameters, an optimization problem is formulated. We propose two methods for solving the optimization problem. The first is exact but requires an integer linear programming solver whereas the second is an approximation relying only on dynamic programming. The model is applied in the department of surgery at a Dutch hospital. The model determines which patient types result in the desired growth in the preferred surgical treatment areas. The case study highlights the impact of striving for a certain case mix without providing a sufficiently balanced supply of resources. In the case study we show how the desired case mix can be better archieved by investing in certain capacity.
University of Twente, Department of Applied Mathematics
Queueing Theory
2011-XVanberkelBoucherieHansHurink_DRGCombinedPaper
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Case Mix Business & Economics
Optimization Problem Business & Economics
Integer Linear Programming Business & Economics
Queueing Model Business & Economics
Fee-for-Service Business & Economics
Queueing System Business & Economics
Approximation Business & Economics
Dynamic Programming Business & Economics
Vanberkel, P. T., Boucherie, R. J., Hans, E. W., & Hurink, J. L. (2011). Optimizing the strategic patient mix. (Memorandum; No. 1935). University of Twente, Department of Applied Mathematics.
Vanberkel, P.T. ; Boucherie, Richardus J. ; Hans, Elias W. ; Hurink, Johann L. / Optimizing the strategic patient mix. Enschede : University of Twente, Department of Applied Mathematics, 2011. 21 p. (Memorandum; 1935).
@book{072000297fd945cf9fc79f7aed0a4d15,
title = "Optimizing the strategic patient mix",
abstract = "In this paper we address the decision of choosing a patient mix for a hospital that leads to the most beneficial treatment case mix. We illustrate how capacity, case mix and patient mix decisions are interrelated and how understanding this complex relationship is crucial for achieving the maximum benefit from the fee-for-service financing system. Although studies to determine the case mix that is of maximum benefit exist in the literature, the hospital actions necessary to realize this case mix has seen less attention. We model the hospital as an $M/G/\infty$ queueing system to evaluate the impact of accepting certain patient types. Using this queueing model to generate the parameters, an optimization problem is formulated. We propose two methods for solving the optimization problem. The first is exact but requires an integer linear programming solver whereas the second is an approximation relying only on dynamic programming. The model is applied in the department of surgery at a Dutch hospital. The model determines which patient types result in the desired growth in the preferred surgical treatment areas. The case study highlights the impact of striving for a certain case mix without providing a sufficiently balanced supply of resources. In the case study we show how the desired case mix can be better archieved by investing in certain capacity.",
keywords = "Combinatorial optimization, Diagnosis related groups, Queueing Theory",
author = "P.T. Vanberkel and Boucherie, {Richardus J.} and Hans, {Elias W.} and Hurink, {Johann L.}",
isbn = "ISSN 1874-4850",
series = "Memorandum",
publisher = "University of Twente, Department of Applied Mathematics",
Vanberkel, PT, Boucherie, RJ, Hans, EW & Hurink, JL 2011, Optimizing the strategic patient mix. Memorandum, no. 1935, University of Twente, Department of Applied Mathematics, Enschede.
Optimizing the strategic patient mix. / Vanberkel, P.T.; Boucherie, Richardus J.; Hans, Elias W.; Hurink, Johann L.
Enschede : University of Twente, Department of Applied Mathematics, 2011. 21 p. (Memorandum; No. 1935).
T1 - Optimizing the strategic patient mix
AU - Vanberkel, P.T.
AU - Boucherie, Richardus J.
AU - Hans, Elias W.
AU - Hurink, Johann L.
N2 - In this paper we address the decision of choosing a patient mix for a hospital that leads to the most beneficial treatment case mix. We illustrate how capacity, case mix and patient mix decisions are interrelated and how understanding this complex relationship is crucial for achieving the maximum benefit from the fee-for-service financing system. Although studies to determine the case mix that is of maximum benefit exist in the literature, the hospital actions necessary to realize this case mix has seen less attention. We model the hospital as an $M/G/\infty$ queueing system to evaluate the impact of accepting certain patient types. Using this queueing model to generate the parameters, an optimization problem is formulated. We propose two methods for solving the optimization problem. The first is exact but requires an integer linear programming solver whereas the second is an approximation relying only on dynamic programming. The model is applied in the department of surgery at a Dutch hospital. The model determines which patient types result in the desired growth in the preferred surgical treatment areas. The case study highlights the impact of striving for a certain case mix without providing a sufficiently balanced supply of resources. In the case study we show how the desired case mix can be better archieved by investing in certain capacity.
AB - In this paper we address the decision of choosing a patient mix for a hospital that leads to the most beneficial treatment case mix. We illustrate how capacity, case mix and patient mix decisions are interrelated and how understanding this complex relationship is crucial for achieving the maximum benefit from the fee-for-service financing system. Although studies to determine the case mix that is of maximum benefit exist in the literature, the hospital actions necessary to realize this case mix has seen less attention. We model the hospital as an $M/G/\infty$ queueing system to evaluate the impact of accepting certain patient types. Using this queueing model to generate the parameters, an optimization problem is formulated. We propose two methods for solving the optimization problem. The first is exact but requires an integer linear programming solver whereas the second is an approximation relying only on dynamic programming. The model is applied in the department of surgery at a Dutch hospital. The model determines which patient types result in the desired growth in the preferred surgical treatment areas. The case study highlights the impact of striving for a certain case mix without providing a sufficiently balanced supply of resources. In the case study we show how the desired case mix can be better archieved by investing in certain capacity.
KW - Combinatorial optimization
KW - Diagnosis related groups
KW - Queueing Theory
SN - ISSN 1874-4850
T3 - Memorandum
BT - Optimizing the strategic patient mix
PB - University of Twente, Department of Applied Mathematics
CY - Enschede
Vanberkel PT, Boucherie RJ, Hans EW, Hurink JL. Optimizing the strategic patient mix. Enschede: University of Twente, Department of Applied Mathematics, 2011. 21 p. (Memorandum; 1935).