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Long term staff scheduling of physicians with different experience levels in hospitals using column generation

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Abstract

We present a strategic model to solve the long-term staffing problem of physicians in hospitals using flexible shifts. The objective is to minimize the total number of staff subject to several labor agreements. A wide range of legal restrictions and facility-specific staffing policies are considered. In general, the model is capable to incorporate different experience levels. In the simplest version the model decides about the number of staff for two experience levels, i.e. the number of residents (low experience) versus specialists (high experience). Shifts are constructed implicitly by the model and may have different starting times and several lengths. This allows more flexibility in the scheduling process. We formulate the problem as a mixed-integer program and solve it applying a column generation based heuristic. Using data provided by an anesthesia department of an 1100-bed hospital, computational results demonstrate the usage of the model as decision supporting tool when staffing decision are made by hospital management.

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References

  1. Bard JF, Purnomo HW (2005) Preference scheduling for nurses using column generation. Eur J Oper Res 164(1):510–534

    Article  Google Scholar 

  2. Beaulieu H, Ferland J, Gendron B, Michelon P (2000) A mathematical programming approach for scheduling physicians in the emergency room. Health Care Manage Sci 3(3):193–200

    Article  Google Scholar 

  3. Bechtold SE, Jacobs LW (1990) Implicit modeling of flexible break assignments in optimal shift scheduling. Manage Sci 36(11):1339–1351

    Article  Google Scholar 

  4. Beliën J, Demeulemeester E (2006) Scheduling trainees at a hospital department using a branch-and-price approach. Eur J Oper Res 175(1):258–278

    Article  Google Scholar 

  5. Beliën J, Demeulemeester E (2007) On the trade-off between staff decomposed and activity-decomposed column generation for a staff scheduling problem. Ann Oper Res 155(1):143–166

    Article  Google Scholar 

  6. Beliën J, Demeulemeester E (2008) A branch-and-price approach for integrating nurse and surgery scheduling. Eur J Oper Res 189(3):652–668

    Article  Google Scholar 

  7. Blöchliger I (2004) Modeling staff scheduling problems: a tutorial. Eur J Oper Res 158(3):533–542

    Article  Google Scholar 

  8. Blum K, Offermanns M, Perner P (2008) Krankenhaus Barometer kompakt – Umfrage 2008. Technical report. Deutsches Krankenhaus Institut e.V, Düsseldorf

    Google Scholar 

  9. Brunner JO, Bard JF, Kolisch R (2009) Flexible shift scheduling of physicians. Health Care Manage Sci 12(3):285–305

    Article  Google Scholar 

  10. Brunner JO, Bard JF, Kolisch R (2011) Midterm scheduling of physicians with flexible shifts using branch-and-price. IIE Trans 43(2):84–109

    Article  Google Scholar 

  11. Burke EK, De Causmaecker P, Berghe GV, Van Landeghem H (2004) The state of the art of nurse rostering. J Sched 7(6):441–499

    Article  Google Scholar 

  12. Carter MW, Lapierre SD (2001) Scheduling emergency room physicians. Health Care Manage Sci 4(4):347–360

    Article  Google Scholar 

  13. Cezik T, Gunluk O, Luss H (2001) An integer programming model for the weekly tour scheduling problem. Nav Res Logist 48(7):607–624

    Article  Google Scholar 

  14. Cheang B, Li H, Lim A, Rodrigues B (2003) Nurse rostering problems – A bibliographic survey. Eur J Oper Res 151(1):447–460

    Article  Google Scholar 

  15. Cohn A, Root S, Esses J, Kymissis C, Westmoreland N (2006) Using mathematical programming to schedule medical residents. Working paper, Department of Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI. Available at http://ioe.engin.umich.edu/techrprt/pdf/TR06-06.pdf

  16. Desaulniers G, Desrosiers J, Solomon MM (eds) (2005) Column generation. Springer, New York

    Google Scholar 

  17. Ernst AT, Jiang H, Krishnamoorthy M, Sier D (2004) Staff scheduling and rostering: a review of applications, methods and models. Eur J Oper Res 153(1):3–27

    Article  Google Scholar 

  18. Ernst AT, Jiang A, Krishnamoorthy M, Owens B, Sier D (2004) An annotated bibliography of personnel scheduling and rostering. Ann Oper Res 127(1):21–144

    Article  Google Scholar 

  19. Franz LS, Miller JL (1993) Scheduling medical residents to rotations: solving large-scale multiperiod staff assignment problem. Oper Res 41(2):269–279

    Article  Google Scholar 

  20. Jaumard B, Semet F, Vovor T (1998) A generalized linear programming model for nurse scheduling. Eur J Oper Res 107(1):1–18

    Article  Google Scholar 

  21. Marburger Bund (2006) Der Arztspezifische Tarifvertrag für die Universitätsärzte. http://www.marburger-bund.de/marburgerbund/bundesverband/unsere_themen/tarifpolitik/tdl/tdl-028.php

  22. Mihm A (2007) Krankenhäuser schlagen Alarm. FrankfurterAllgemeine Zeitung (online) http://www.faz.net/s/RubC43EEA6BF57E4A09925C1D802785495A/Doc~EB9067149F560459D998C1E8F7DE953E6~ATpl~Ecommon~Scontent.html

  23. Moondra SL (1976) An LP model for work force scheduling at banks. J Bank Res 6:299–301

    Google Scholar 

  24. MRI (2010) http://www.med.tu-muenchen.de/sprache/englisch/index.php

  25. Ovchinnikov A, Milner J (2008) Spreadsheet model helps to assign medical residents at the University of Vermont’s college of medicine. Interfaces 38(4):311–323

    Article  Google Scholar 

  26. Quadbeck E (2010) Krankenhäuser in Not: In Kliniken fehlen 5000 Ärzte. RP ONLINE (online). http://www.rp-online.de/panorama/deutschland/In-Kliniken-fehlen-5000-Aerzte_aid_821014.html

  27. Purnomo HW, Bard JF (2007) Cyclic preference scheduling for nurses using branch and price. Nav Res Logist 54(2):200–220

    Article  Google Scholar 

  28. Rousseau L, Pesant G, Gendreau M (2002) A general approach to the physician rostering problem. Ann Oper Res 115(1):193–205

    Article  Google Scholar 

  29. Sherali HD, Ramahi MH, Saifee QJ (2002) Hospital resident scheduling problem. Prod Plan Control 13(2):220–233

    Article  Google Scholar 

  30. Social Code V (2011) § 28 Paragraph 1. Sozialgesetzbuch. http://www.sozialgesetzbuch-sgb.de/sgbv/28.html. Accessed 11 January 2011

  31. Stolletz R, Brunner JO (2010) Fair optimization of the fortnightly physician schedules with flexible shifts, working paper

  32. Thompson G (1995) Improved implicit optimal modeling of the labor shift scheduling problem. Manage Sci 41(4):595–607

    Article  Google Scholar 

  33. Thungjaroenkul P, Cummings GG, Embleton A (2007) The impact of nurse staffing on hospital costs and patient length of stay: a systematic review. Nurs Econ 25(5):255–265

    Google Scholar 

  34. Topaloglu S (2006) A multi-objective programming model for scheduling emergency medicine residents. Comput Ind Eng 51(3):375–388

    Article  Google Scholar 

  35. Topaloglu S (2009) A shift scheduling model for employees with different seniority levels and an application in healthcare. Eur J Oper Res 198(3):943–957

    Article  Google Scholar 

  36. White C, White G (2003) Scheduling doctors for clinical training unit rounds using tabu optimization. In lecture notes in computers science bookseries practice and theory of automated timetabling, vol IV. Springer Heidelberg, pp 120–128

  37. Williams HP (2001) Model building in mathematical programming. Wiley, Chichester

    Google Scholar 

  38. Winston WL (2004) Operations research applications and algorithms. Thomson Brooks/Cole, Belmont

    Google Scholar 

  39. Wosley LA (1998) Integer Programming. Wiley, New York

    Google Scholar 

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Acknowledgement

We gratefully acknowledge the constructive comments of three anonymous referees.

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Correspondence to Jens O. Brunner.

Appendix

Appendix

1.1 Linearization

The linearization for constraints (1b) is as follows [37].

$$ \begin{array}{*{20}{c}} {y_{{eiwp}}^{{shift}} = {x_{{eiwp}}}\left( {1 - {x_{{eiwp - 1}}}} \right),} & {\forall e \in E,i \in {I_e},w \in W,p \in P} \\ \end{array} $$
(1b)
$$ \begin{array}{*{20}{c}} {--{x_{{eiwp}}} + y_{{eiwp}}^{{shift}} \leqslant 0,} & {\forall e \in E,i \in {I_e},w \in W,p \in P} \\ \end{array} $$
(a)
$$ \begin{array}{*{20}{c}} {{x_{{eiwp}}}_{{--{1}}} + y_{{eiwp}}^{{shift}} \leqslant {1},} & {\forall e \in E,i \in {I_e},w \in W,p \in P} \\ \end{array} $$
(b)
$$ \begin{array}{*{20}{c}} {{x_{{eiwp}}}--{x_{{eiwp}}}_{{--{1}}}--y_{{eiwp}}^{{shift}} \leqslant 0,} & {\forall e \in E,i \in {I_e},w \in W,p \in P} \\ \end{array} $$
(c)

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Brunner, J.O., Edenharter, G.M. Long term staff scheduling of physicians with different experience levels in hospitals using column generation. Health Care Manag Sci 14, 189–202 (2011). https://doi.org/10.1007/s10729-011-9155-x

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