Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-18T05:28:51.306Z Has data issue: false hasContentIssue false
  • English
  • Français

Managing a patient waiting list with time-dependent priorityand adverse events

Published online by Cambridge University Press:  05 December 2013

Daiki Min  and
Yuehwern Yih
Daiki Min
Affiliation:
Assistant Professor, College of Business Administration, Ewha Womans University, 52 Ewhayeodae-gil, Seoul, 120-750, Korea. [email protected]
Yuehwern Yih
Affiliation:
Professor, School of Industrial Engineering, Purdue University, 315 N. Grant Street, West Lafayette, IN, 47906, USA; [email protected]
Get access

Abstract

This paper addresses the problem of managing a waiting list for elective surgery todecide the number of patients selected from the waiting list and to schedule them inaccordance with the operating room capacity in the next period. The waiting listprioritizes patients not only by their initial urgency level but also by their waitingtime. Selecting elective surgery patients requires a balance between the waiting time forurgent patients and that for less urgent patients. The problem is formulated as aninfinite horizon Markov Decision Process. Further, the study proposes a schedulingprocedure based on structural properties of an optimal policy by taking a sampling-basedfinite horizon approximation approach. Finally, we examine the performance of the policyunder various conditions.

Keywords

Waiting list managementtime-dependent priorityadverse events while waitingMarkov Decision Process
Type
Research Article
Information
RAIRO - Operations Research , Volume 48 , Issue 1 , January 2014 , pp. 53 - 74
Copyright
© EDP Sciences, ROADEF, SMAI, 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alden, J.M. and Smith, R.L., Rolling horizon procedures in nonhomogeneous Markov Decision Processes. Oper. Res. 40 (1992) 183–194. Google Scholar
D.P. Bertsekas, Dynamic programming and optimal control, Vol. 2, 2nd edition. Athena Scientific, Belmont, MA (2007).
Bertsekas, D.P. and Castanon, D.A., Rollout algorithms for stochastic scheduling problems. J. Heuristics 5 (1999) 89–108. Google Scholar
Cheevaprawatdomrong, T. and Smith, R.L., Infinite horizon production scheduling in time-varying systems under stochastic demand. Oper. Res. 52 (2004) 105–115. Google Scholar
Chang, H.S., Fu, M.C., Hu, J. and Marcus, S.I., An adaptive sampling algorithm for solving Markov Decision Processes. Oper. Res. 53 (2005) 126–139. Google Scholar
Dexter, F., Macario, A. and Traub, R.D., Which algorithm for scheduling add-on elective cases maximizes operating room utilization? Use of bin packing algorithms and fuzzy constraints in operating room management. Anesthesia and Analgesia 90 (1999) 980–988. Google Scholar
Everett, J., A decision support simulation model for the management of an elective surgery waiting system. Health Care Manag. Sci. 5 (2002) 89–95. Google Scholar
Gerchak, Y., Gupta, D. and Henig, M., Reservation planning for elective surgery under uncertain demand for emergency surgery. Manag. Sci. 42 (1996) 321–334. Google Scholar
Green, L., Savin, S. and Wang, B., Managing patient service in a diagnostic medical facility. Oper. Res. 54 (2006) 11–25. Google Scholar
Gupta, D., Surgical Suites Operations Management. Prod. Oper. Manag. 16 (2007) 689–700. Google Scholar
Hans, E., Wullink, G., Houdenhoven, M.V. and Kazemier, G., Robust surgery loading. Eur. J. Oper. Res. 185 (2008) 1038–1050. Google Scholar
Hernandez-Lerma, O. and Lasserre, J.B., Error bounds for rolling horizon policies in discrete-time Markov control processes. IEEE Trans. Autom. Control 35 (1990) 1118–1124. Google Scholar
J. Hurst and L. Sicilliani, Tackling excessive waiting times for elective surgery: A comparison of policies in twelve OECD countries. OECD Health Work. Pap. 2003 (2003).
Kearns, M., Mansour, Y. and Ng, A.Y., A sparse sampling algorithm for near-optimal planning in large Markov Decision Processes. Machine Learn. 49 (2002) 193–208. Google Scholar
M. Lans, E. Hans, J.L. Hurink, G. Wullink, M. Houdenhoven and G. Kazemier, Anticipating urgent surgery in operating room departments, Working Paper, University of Twente, The Netherlands (2006).
Liu, L. and Liu, X., Dynamic and static job allocation for multi-server systems. IIE Trans. 30 (1998) 845–854. Google Scholar
N. Liu, S. Ziya and V.G. Kulkarni, Dynamic scheduling of outpatient appointments under patient no-shows and cancellations. Manufacturing and Service Oper. Manag. Published online (2009).
Lovejoy, W.S. and Li, Y., Hospital operating room capacity expansion. Manag. Sci. 48 (2002) 1369–1387. Google Scholar
MacCormick, A.D., Collecutt, W.G. and Parry, B.R., Prioritizing patients for elective surgery: A systematic review. ANZ J. Surgery, 73 (2003) 633–642. Google Scholar
Marcon, E., Kharraja, S. and Simonnet, G., The operating theatre planning by the follow-up of the risk of no realization. Int. J. Prod. Econ. 85 (2003) 83–90. Google Scholar
Min, D. and Yih, Y., An elective surgery scheduling problem considering patient priority. Comput. Oper. Res. 37 (2010) 1091–1099. Google Scholar
Mullen, P.M., Prioritizing waiting lists: how and why? Eur. J. Oper. Res. 150 (2003) 32–45. Google Scholar
Muthuraman, K. and Lawley, M., A stochastic overbooking model for outpatient clinical scheduling with no-shows. IIE Trans. 40 (2008) 820–837. Google Scholar
Olivares, M., Terwiesch, C. and Cassorla, L., Structural estimation of the newsvendor model: an application to reserving operating room time. Manag. Sci. 54 (2008) 41–55. Google Scholar
Patrick, J., Puterman, M. and Queyranne, M., Dynamic multi-priority patient scheduling for a diagnostic resource. Oper. Res. 56 (2008) 1507–1525. Google Scholar
W.B. Powell, Approximate dynamic programming: Solving the curses of dimensionality. John Wiley and Sons, Inc., New York (2007).
Schochetman, I.E. and Smith, R.L., Infinite horizon optimization. Math. Oper. Res. 14 (1989) 559–574. Google Scholar
Smith, L.R. and Zhang, Q.R., Infinite horizon production planning in time-varying systems with convex production and inventory costs. Manag. Sci. 44 (1998) 1313–1320. Google Scholar
Sobolev, B., Kuramoto, L., Levy, A. and Hayden, R., Cumulative incidence for wait-list death in relation to length of queue for coronary-artery bypass grafting: a cohort study. J. Cardiothoracic Surgery 1 (2006) 1–10. Google ScholarPubMed
B. Sobolev and L. Kuramoto, Analysis of waiting-time data in health services research. New York, Springer (2007).
Sobolev, B., Sanchez, V., Kuramoto, L., Levy, A.R. Schechter, M. and FitzGerald, M., Evaluation of booking systems for elective surgery using simulation experiments. Healthcare Policy 3 (2008) 113–124. Google ScholarPubMed
Strum, D.P., Varga, L.G., May, J.H. and Bashein, G., Surgical suite utilization and capacity planning: a minimal cost analysis model. J. Medical Systems 21 (1997) 309–322. Google ScholarPubMed
Testi, A., Tanfani, E. and Torre, G., A three-phase approach for operating theatre schedules. Health Care Manag. Sci. 10 (2007) 163–172. Google ScholarPubMed
Thompson, S., Nunez, M., Garfinkel, R. and Dean, M.D., Efficient short-term allocation and reallocation of patients to floors of a hospital during demand surges. Oper. Res. 57 (2009) 261–273. Google Scholar
Vasilakis, C., Sobolev, B., Kuramoto, L. and Levy, A., A simulation study of scheduling clinic appointments in surgical care: individual surgeon versus pooled lists. J. Oper. Res. Soc. 58 (2007) 202–211. Google Scholar