EURO Journal on Decision Processes

, Volume 4, Issue 3–4, pp 245–267 | Cite as

Fuzzy decision making in health systems: a resource allocation model

  • Tahir Ekin
  • Ozan Kocadagli
  • Nathaniel D. Bastian
  • Lawrence V. Fulton
  • Paul M. Griffin
Original Article

Abstract

The efficient use of resources in health systems is important due to the increasing demand and limited funding. Large health systems often have fixed input resources (such as budget and staffing) to be allocated among individual hospitals/clinics with particular target output levels. We propose an optimization model with fuzzy constraints that can be used for automatic resource re-allocation with respect to different levels of risk preferences. We illustrate its applicability using data from a U.S. Army hospital network. The implications of the proposed fuzzy decision-making model for healthcare decision makers and its relevance to healthcare policy and management are also discussed.

Keywords

Multi-objective optimization Fuzzy modeling Resource allocation Health systems Military medicine 

Notes

Acknowledgments

This work was supported in part by the National Science Foundation under Grant No. DGE1255832. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation, United States Army, Texas State University, Mimar Sinan Fine Arts University, Pennsylvania State University, Texas Tech University, or Georgia Institute of Technology.

References

  1. Aktas E, Ulengin F, Sahin SO (2007) A decision support system to improve the efficiency of resource allocation in healthcare management. Socio-Econ Plan Sci 41(2):130–146CrossRefGoogle Scholar
  2. Arenas M, Bilbao A, Rodríguez Uría MV, Jimenez M (2001) A fuzzy goal programming model for evaluating a hospital service performance. Fuzzy Sets in Management, Economics and Marketing, pp 19–33Google Scholar
  3. Bastian N, Fulton L, Shah V, Ekin T (2014) Resource allocation decision-making in the military health system. IIE Trans Healthc Syst Eng 4(2):80–87CrossRefGoogle Scholar
  4. Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Manag Sci 17(4):141–164CrossRefGoogle Scholar
  5. Charnes A, Cooper WW, Rhodes E (1978) Measuring efficiency of decision making units. Eur J Oper Res 2(6):429–444CrossRefGoogle Scholar
  6. Charnes A, Cooper WW, Golany B, Seiford L, Stutz J (1985) Foundations of data envelopment analysis for Pareto–Koopmans efficient empirical production functions. J Econom 30(1):91–107CrossRefGoogle Scholar
  7. Charnes A, Cooper WW, Lewin AY, Seiford LM (1994) Data envelopment analysis: theory, methodology, and applications. Kluwer Academic Publishers, LondonCrossRefGoogle Scholar
  8. Charnes A, Cooper W, Dieck-Assad M, Golany B, Wiggins D (1985) Efficiency analysis of medical care resources in the U.S. Army Health Service Command. The University of Texas at Austin, Center for Cybernetic Studies. Washington, DC: Defense Technical Information Service (ADA 159742)Google Scholar
  9. Cooper W, Seifer L, Tone K (2007) Data envelopment analysis, 2nd edn. Springer, New YorkGoogle Scholar
  10. Drud A (1992) CONOPT a large-scale GRG code. ORSA J Comput 6(2):207–216CrossRefGoogle Scholar
  11. Eichler HG, Kong SX, Gerth WC, Mavros P, Jonsson B (2004) Use of cost-effectiveness analysis in health-care resource allocation decision-making: how are cost-effectiveness thresholds expected to emerge? Value Health 7(5):518–528CrossRefGoogle Scholar
  12. Emrouznejad A, Mustafa A, Al-Eraqi AS (2010) Aggregating preference ranking with fuzzy data envelopment analysis. Knowl Based Syst 23(6):512–519CrossRefGoogle Scholar
  13. Emrouznejad A, Tavana M (eds) (2014) Performance measurement with fuzzy data envelopment analysis. Springer, ChicagoGoogle Scholar
  14. Fulton L, Lasdon L, McDaniel R (2007) Cost drivers and resource allocation in military health care systems. Mil Med 172(3):244–249CrossRefGoogle Scholar
  15. Fulton L, Lasdon L, McDaniel R, Coppola N (2008) Including quality, access and efficiency in health care cost models. Hosp Top 86(4):3–16CrossRefGoogle Scholar
  16. GAMS Development Corporation (2014) The general algebraic modeling system (GAMS). http://www.gams.com. Accessed 26 Jan 2015
  17. Grigoroudis E, Orfanoudaki E, Zopounidis C (2012) Strategic performance measurement in a healthcare organisation: a multiple criteria approach based on balanced scorecard. Omega 40(1):104–119CrossRefGoogle Scholar
  18. Hatami-Marbini A, Emrouznejad A, Tavana M (2011) A taxonomy and review of the fuzzy data envelopment analysis literature: two decades in the making. Eur J Oper Res 214(3):457–472CrossRefGoogle Scholar
  19. Hussein ML, Abo-Sinna MA (1995) A fuzzy dynamic approach to the multicriterion resource allocation problem. Fuzzy Sets Syst 69(2):115–124CrossRefGoogle Scholar
  20. IBM ILOG (2010) CPLEX 12.1 User manual. http://ampl.com/booklets/amplcplex121userguide.pdf. Accessed 26 Jan 2015
  21. Joro T, Korhonen P, Wallenius J (1998) Structural comparison of data envelopment analysis and multiple objective linear programming. Manag Sci 44(7):962–970CrossRefGoogle Scholar
  22. Kachukhashvili GS, Tsiskarishvili NE, Dubovik MV, Badiashvili GV (1995) The use of fuzzy sets techniques in managing health organizations. Medinfo MEDINFO 8(1):541Google Scholar
  23. Keskin R, Kocadağli O, Cinemre N (2015) A novel fuzzy goal programming approach with preemptive structure for optimal investment decisions. J Intell Fuzzy Syst: Appl Eng Technol 28(2):633–645Google Scholar
  24. Kocadagli O, Keskin R (2013) A novel fuzzy goal programming approach for optimal investment decisions, Fuzzyss13: the 3rd international fuzzy systems symposium, October 24–25, Istanbul, TurkeyGoogle Scholar
  25. Korhonen P, Syrjanen M (2004) Resource allocation based on efficiency analysis. Manag Sci 50(8):1134–1144CrossRefGoogle Scholar
  26. Kwak NK, Chang WL (2002) Business process reengineering for health-care system using multicriteria mathematical programming. Eur J Oper Res 140(2):447–458CrossRefGoogle Scholar
  27. Kwak NK, Lee C (1997) A linear goal programming model for human resource allocation in a health-care organization. J Med Syst 21(3):129–140CrossRefGoogle Scholar
  28. Lai YJ, Hwang CL (1992) Fuzzy mathematical programming. Springer-Verlag, BerlinCrossRefGoogle Scholar
  29. Leon T, Liern V, Ruiz JL, Sirvent I (2003) A fuzzy mathematical programming approach to the assessment of efficiency with DEA models. Fuzzy Sets Syst 139(2):407–419CrossRefGoogle Scholar
  30. Lertworasirikul S, Fang SC, Nuttle HL, Joines JA (2003) Fuzzy BCC model for data envelopment analysis. Fuzzy Optim Decis Mak 2(4):337–358CrossRefGoogle Scholar
  31. MHS Stakeholder‘s Report (2012) The MHS: healthcare to health. MHS Stakeholder‘s Report (2012) http://www.health.mil//media/MHS/Report20Files/Optimized202012_MHS_Stakeholders_Report120207.ashx. Accessed July 29 2014
  32. Mjelde KM (1986) Fuzzy resource allocation. Fuzzy Sets Syst 19(3):239–250CrossRefGoogle Scholar
  33. Murtagh B, Saunders M (1983) MINOS 5.0 user‘s guide. Report SOL 83-20, Department of Operations Research, Stanford UniversityGoogle Scholar
  34. O`Neill L, Rauner M, Heidenberger K, Kraus M (2008) A cross-national comparison and taxonomy of DEA-based hospital efficiency studies. Socio-Econ Plann Sci 42(3):158–189CrossRefGoogle Scholar
  35. Ozcan Y, Bannick R (1994) Trends in Department of Defense hospital efficiency. J Med Syst 18(2):69–83CrossRefGoogle Scholar
  36. Piner T (2006) Improving clinical efficiency of military treatment facilities. Unpublished Master’s Thesis, Naval Postgraduate SchoolGoogle Scholar
  37. Ross T (1995) Fuzzy logic with engineering applications. McGraw-Hill Inc, New YorkGoogle Scholar
  38. Sengupta JK (1992) A fuzzy systems approach in data envelopment analysis. Comput Math Appl 24(8):259–266CrossRefGoogle Scholar
  39. Sengupta JK (1992) Measuring efficiency by a fuzzy statistical approach. Fuzzy Sets Syst 46(1):73–80CrossRefGoogle Scholar
  40. Sheth N, Triantis K (2003) Measuring and evaluating efficiency and effectiveness using goal programming and data envelopment analysis in a fuzzy environment.Yugoslav Journal of. Oper Res 13(1):35–60Google Scholar
  41. Uemura Y (2006) Fuzzy satisfactory evaluation method for covering the ability comparison in the context of DEA efficiency. Control Cybern 35(2):487–495Google Scholar
  42. Wang LX (1997) A course in fuzzy-systems and control. Prentice-Hall, EastbourneGoogle Scholar
  43. Wang HF, Fu CC (1997) A generalization of fuzzy goal programming with preemptive structure. Comput Oper Res 24(9):819–828CrossRefGoogle Scholar
  44. Werners B (1987) Interact Fuzzy Program Syst. Fuzzy Sets Syst 23(1):131–147CrossRefGoogle Scholar
  45. Zadeh L (1965) Fuzzy sets. Inf Control 8(3):338–353CrossRefGoogle Scholar
  46. Zimmermann HJ (1978) Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst 1(1):45–55CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg and EURO - The Association of European Operational Research Societies 2015

Authors and Affiliations

  • Tahir Ekin
    • 1
  • Ozan Kocadagli
    • 2
  • Nathaniel D. Bastian
    • 3
  • Lawrence V. Fulton
    • 4
  • Paul M. Griffin
    • 5
  1. 1.McCoy College of Business AdministrationTexas State UniversitySan MarcosUSA
  2. 2.Department of StatisticsMimar Sinan Fine Arts UniversitySisli, IstanbulTurkey
  3. 3.Department of Industrial and Manufacturing EngineeringPennsylvania State UniversityUniversity ParkUSA
  4. 4.Rawls College of Business AdministrationTexas Tech UniversityLubbockUSA
  5. 5.School of Industrial and Systems EngineeringGeorgia Institute of TechnologyAtlantaUSA

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