Literature DB >> 19469452

Patient mix optimisation and stochastic resource requirements: a case study in cardiothoracic surgery planning.

Ivo Adan1, Jos Bekkers, Nico Dellaert, Jan Vissers, Xiaoting Yu.   

Abstract

Cardiothoracic surgery planning involves different resources such as operating theatre time, beds, IC beds and nursing staff. In the daily practice of the Thorax Centre case study setting, the planning focuses on optimal use of operating theatre time, though the performance of the Thorax Centre as a whole is often more limited by other resources. For operating theatres a master surgical schedule is used to allocate operating theatre resources at tactical level for a longer period. Operational schedules at weekly level are derived from this master schedule. Within cardiothoracic surgery different categories of patients can be distinguished based on their requirement of resources. The mix of patients operated is, therefore, an important decision variable for the Thorax Centre to manage the use of these resources. In this paper we will consider the planning problem at the tactical level to generate a master surgical schedule that realises a given target of patient throughput and optimises an objective function for the utilisation of resources. The problem can be mathematically approached by mixed integer linear programming, which we already demonstrated in a previous paper. The specific topic of the current paper is to investigate the influence of using a stochastic instead of a deterministic length of stay. We will discuss the new mathematical model developed for this planning problem. The results obtained by the model indicate that we can generate master surgical schedules with a better performance on target utilization levels of resources by considering the stochastic length of stay.

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Year:  2009        PMID: 19469452     DOI: 10.1007/s10729-008-9080-9

Source DB:  PubMed          Journal:  Health Care Manag Sci        ISSN: 1386-9620


  4 in total

1.  Tactical increases in operating room block time based on financial data and market growth estimates from data envelopment analysis.

Authors:  Liam O'Neill; Franklin Dexter
Journal:  Anesth Analg       Date:  2007-02       Impact factor: 5.108

Review 2.  Tactical increases in operating room block time for capacity planning should not be based on utilization.

Authors:  Ruth E Wachtel; Franklin Dexter
Journal:  Anesth Analg       Date:  2008-01       Impact factor: 5.108

3.  Queuing theory accurately models the need for critical care resources.

Authors:  Michael L McManus; Michael C Long; Abbot Cooper; Eugene Litvak
Journal:  Anesthesiology       Date:  2004-05       Impact factor: 7.892

4.  Variability in surgical caseload and access to intensive care services.

Authors:  Michael L McManus; Michael C Long; Abbot Cooper; James Mandell; Donald M Berwick; Marcello Pagano; Eugene Litvak
Journal:  Anesthesiology       Date:  2003-06       Impact factor: 7.892

  4 in total
  14 in total

1.  Operational research in the management of the operating theatre: a survey.

Authors:  Francesca Guerriero; Rosita Guido
Journal:  Health Care Manag Sci       Date:  2010-11-20

2.  Simulation-Based Optimization for Surgery Scheduling in Operation Theatre Management Using Response Surface Method.

Authors:  Feng Liang; Yuanyuan Guo; Richard Y K Fung
Journal:  J Med Syst       Date:  2015-09-18       Impact factor: 4.460

Review 3.  Case mix planning in hospitals: a review and future agenda.

Authors:  Sebastian Hof; Andreas Fügener; Jan Schoenfelder; Jens O Brunner
Journal:  Health Care Manag Sci       Date:  2015-09-19

4.  Scheduling elective surgeries: the tradeoff among bed capacity, waiting patients and operating room utilization using goal programming.

Authors:  Xiangyong Li; N Rafaliya; M Fazle Baki; Ben A Chaouch
Journal:  Health Care Manag Sci       Date:  2015-07-17

5.  Scheduling admissions and reducing variability in bed demand.

Authors:  René Bekker; Paulien M Koeleman
Journal:  Health Care Manag Sci       Date:  2011-06-11

6.  Admission and capacity planning for the implementation of one-stop-shop in skin cancer treatment using simulation-based optimization.

Authors:  H L Romero; N P Dellaert; S van der Geer; M Frunt; M H Jansen-Vullers; G A M Krekels
Journal:  Health Care Manag Sci       Date:  2012-09-09

7.  Tactical resource allocation and elective patient admission planning in care processes.

Authors:  Peter J H Hulshof; Richard J Boucherie; Erwin W Hans; Johann L Hurink
Journal:  Health Care Manag Sci       Date:  2013-01-04

8.  Recovery bed planning in cardiovascular surgery: a simulation case study.

Authors:  Yariv N Marmor; Thomas R Rohleder; David J Cook; Todd R Huschka; Jeffrey E Thompson
Journal:  Health Care Manag Sci       Date:  2013-03-19

9.  Surgery scheduling heuristic considering OR downstream and upstream facilities and resources.

Authors:  Rafael Calegari; Flavio S Fogliatto; Filipe R Lucini; Michel J Anzanello; Beatriz D Schaan
Journal:  BMC Health Serv Res       Date:  2020-07-23       Impact factor: 2.655

10.  Bed Capacity Planning Using Stochastic Simulation Approach in Cardiac-surgery Department of Teaching Hospitals, Tehran, Iran.

Authors:  Amin Torabipour; Hojjat Zeraati; Mohammad Arab; Arash Rashidian; Ali Akbari Sari; Mahmuod Reza Sarzaiem
Journal:  Iran J Public Health       Date:  2016-09       Impact factor: 1.429

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