Tactical planning in healthcare using approximate dynamic programming

Research output: Book/ReportReportProfessional

48 Downloads (Pure)

Abstract

Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to serve the strategically agreed number of patients, and to use resources efficiently. We propose a method to develop a tactical resource allocation and patient admission plan that takes stochastic elements into consideration, thereby providing robust plans. Our method is developed in an Approximate Dynamic Programming (ADP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital and an uncertain number of arrivals in each time period, thereby integrating decision making for a chain of hospital resources. Computational results indicate that the ADP approach provides an accurate approximation of the value functions, and that it is suitable for large problem instances at hospitals, in which the ADP approach performs significantly better than two other heuristic approaches. Our ADP algorithm is generic, as various cost functions and basis functions can be used in various settings of tactical hospital management.
Original languageEnglish
Place of PublicationEnschede
PublisherUniversity of Twente, Department of Applied Mathematics
Number of pages32
Publication statusPublished - Sep 2013

Publication series

NameMemorandum
PublisherUniversity of Twente, Department of Applied Mathematics
No.2014
ISSN (Print)1874-4850
ISSN (Electronic)1874-4850

Fingerprint

Dynamic programming
Planning
Cost functions
Resource allocation
Decision making

Keywords

  • METIS-297833
  • Approximate Dynamic Programming (ADP)
  • Dynamic Programming (DP)
  • Health Care
  • IR-87252
  • Patient admission planning
  • Tactical planning
  • EWI-23712
  • Resource capacity planning

Cite this

Hulshof, P. J. H., Mes, M. R. K., Boucherie, R. J., & Hans, E. W. (2013). Tactical planning in healthcare using approximate dynamic programming. (Memorandum; No. 2014). Enschede: University of Twente, Department of Applied Mathematics.
Hulshof, P.J.H. ; Mes, Martijn R.K. ; Boucherie, Richardus J. ; Hans, Elias W. / Tactical planning in healthcare using approximate dynamic programming. Enschede : University of Twente, Department of Applied Mathematics, 2013. 32 p. (Memorandum; 2014).
@book{68d59f3c565449ea86d5f2aaabfb17db,
title = "Tactical planning in healthcare using approximate dynamic programming",
abstract = "Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to serve the strategically agreed number of patients, and to use resources efficiently. We propose a method to develop a tactical resource allocation and patient admission plan that takes stochastic elements into consideration, thereby providing robust plans. Our method is developed in an Approximate Dynamic Programming (ADP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital and an uncertain number of arrivals in each time period, thereby integrating decision making for a chain of hospital resources. Computational results indicate that the ADP approach provides an accurate approximation of the value functions, and that it is suitable for large problem instances at hospitals, in which the ADP approach performs significantly better than two other heuristic approaches. Our ADP algorithm is generic, as various cost functions and basis functions can be used in various settings of tactical hospital management.",
keywords = "METIS-297833, Approximate Dynamic Programming (ADP), Dynamic Programming (DP), Health Care, IR-87252, Patient admission planning, Tactical planning, EWI-23712, Resource capacity planning",
author = "P.J.H. Hulshof and Mes, {Martijn R.K.} and Boucherie, {Richardus J.} and Hans, {Elias W.}",
year = "2013",
month = "9",
language = "English",
series = "Memorandum",
publisher = "University of Twente, Department of Applied Mathematics",
number = "2014",

}

Hulshof, PJH, Mes, MRK, Boucherie, RJ & Hans, EW 2013, Tactical planning in healthcare using approximate dynamic programming. Memorandum, no. 2014, University of Twente, Department of Applied Mathematics, Enschede.

Tactical planning in healthcare using approximate dynamic programming. / Hulshof, P.J.H.; Mes, Martijn R.K.; Boucherie, Richardus J.; Hans, Elias W.

Enschede : University of Twente, Department of Applied Mathematics, 2013. 32 p. (Memorandum; No. 2014).

Research output: Book/ReportReportProfessional

TY - BOOK

T1 - Tactical planning in healthcare using approximate dynamic programming

AU - Hulshof, P.J.H.

AU - Mes, Martijn R.K.

AU - Boucherie, Richardus J.

AU - Hans, Elias W.

PY - 2013/9

Y1 - 2013/9

N2 - Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to serve the strategically agreed number of patients, and to use resources efficiently. We propose a method to develop a tactical resource allocation and patient admission plan that takes stochastic elements into consideration, thereby providing robust plans. Our method is developed in an Approximate Dynamic Programming (ADP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital and an uncertain number of arrivals in each time period, thereby integrating decision making for a chain of hospital resources. Computational results indicate that the ADP approach provides an accurate approximation of the value functions, and that it is suitable for large problem instances at hospitals, in which the ADP approach performs significantly better than two other heuristic approaches. Our ADP algorithm is generic, as various cost functions and basis functions can be used in various settings of tactical hospital management.

AB - Tactical planning of resources in hospitals concerns elective patient admission planning and the intermediate term allocation of resource capacities. Its main objectives are to achieve equitable access for patients, to serve the strategically agreed number of patients, and to use resources efficiently. We propose a method to develop a tactical resource allocation and patient admission plan that takes stochastic elements into consideration, thereby providing robust plans. Our method is developed in an Approximate Dynamic Programming (ADP) framework and copes with multiple resources, multiple time periods and multiple patient groups with various uncertain treatment paths through the hospital and an uncertain number of arrivals in each time period, thereby integrating decision making for a chain of hospital resources. Computational results indicate that the ADP approach provides an accurate approximation of the value functions, and that it is suitable for large problem instances at hospitals, in which the ADP approach performs significantly better than two other heuristic approaches. Our ADP algorithm is generic, as various cost functions and basis functions can be used in various settings of tactical hospital management.

KW - METIS-297833

KW - Approximate Dynamic Programming (ADP)

KW - Dynamic Programming (DP)

KW - Health Care

KW - IR-87252

KW - Patient admission planning

KW - Tactical planning

KW - EWI-23712

KW - Resource capacity planning

M3 - Report

T3 - Memorandum

BT - Tactical planning in healthcare using approximate dynamic programming

PB - University of Twente, Department of Applied Mathematics

CY - Enschede

ER -

Hulshof PJH, Mes MRK, Boucherie RJ, Hans EW. Tactical planning in healthcare using approximate dynamic programming. Enschede: University of Twente, Department of Applied Mathematics, 2013. 32 p. (Memorandum; 2014).