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An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach

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Abstract

Given the perennial imbalance and chronic scarcity between the demand for and supply of available organs, organ allocation is one of the most critical decisions in the management of organ transplantation networks. Organ allocation systems undergo rapid revisions for the sake of improved outcomes in terms of both equity and medical efficiency. This paper presents a Data Envelopment Analysis (DEA)-based model to evaluate the efficiency of possible patient-organ pairs for kidney allocation in order to enhance the fitness of organ allocation under inherent uncertainty in such problem. Eligible patient-kidney pairs are regarded as decision making units (DMUs) in a Credibility-based Fuzzy Common Weights DEA (CFCWDEA) approach and are ranked based on efficiency scores. Using a common set of weights for all DMUs ensures a high degree of fairness in the assessment and ranking of DMUs. The proposed model is also the first allocation method capable of coping with the vague and intervallic medical and nonmedical allocation factors by the aid of fuzzy programming. Verification and validation of the proposed approach are performed in two steps using a real case study from the Iranian kidney allocation system. First, the superiority of the proposed deterministic model in enhancing allocation outcomes is demonstrated and analyzed. Second, the applicability of the proposed fuzzy DEA method is demonstrated using a series of data realizations for different credibility levels.

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Notes

  1. “When two people share the same HLAs, they are said to be a “match”, that is, their tissues are immunologically compatible with each other. HLA are proteins that are located on the surface of the white blood cells and other tissues in the body.” For more details visit: http://www.stanford.edu/dept/HPS/transplant/html/hla.html

References

  1. WHO (2014) World Health Organization. http://www.who.int/topics/transplantation/en/

  2. OPTN (2016) Organ Procurement and Transplantation Network. https://optn.transplant.hrsa.gov/

  3. OPTN National Data (2017) Organ Procurement and Transplantation Network. https://optn.transplant.hrsa.gov/data/view-data-reports/national-data/. 2017

  4. OPTN Data. (2017) Organ Procurement and Transplantation Network. https://optn.transplant.hrsa.gov/data/. 2017

  5. Rouchi AH, Ghaemi F, Aghighi M (2014) Outlook of organ transplantation in Iran: a time for quality assessment. Iran J Kidney Dis 8(3):185

    Google Scholar 

  6. Kazemeini SM, Bagheri Chime A, Heidari A (2004) Worldwide cadaveric organ donation systems (transplant organ procurement)

  7. MOHME. (2016) Ministry of Health and Medical Education (Iran). http://www.behdasht.gov.ir/

  8. Thompson D, Waisanen L, Wolfe R, Merion RM, McCullough K, Rodgers A (2004) Simulating the allocation of organs for transplantation. Health Care Manag Sci 7(4):331–338

    Article  Google Scholar 

  9. Çay P (2012) Organ transplantation logistics: case for Turkey. BILKENT UNIVERSITY

  10. UNOS. (2016) United Network for Organ Sharing. https://www.unos.org/data/

  11. Lamont J, Favor C (1996) Distributive Justice. https://plato.stanford.edu/entries/justice-distributive/

  12. Bioethic Tools: Principles of Bioethics. (2017). https://depts.washington.edu/bioethx/tools/princpl.html

  13. Benjamin M (1988) Medical ethics and economics of organ transplantation. Health prog 69(2):47–52

    Google Scholar 

  14. Douglas DD (2003) Should everyone have equal access to organ transplantation?: an argument in favor. Arch Intern Med 163(16):1883–1885

    Article  Google Scholar 

  15. Neuberger J (2003) Should liver transplantation be made available to everyone?: the case against. Arch Intern Med 163(16):1881–1883

    Article  Google Scholar 

  16. Williams A, Evans JG (1997) The rationing debate. Rationing health care by age. BMJ. Br Med J 314(7083):820

    Article  Google Scholar 

  17. Ubel PA, Arnold RM, Caplan AL (1993) Rationing failure: the ethical lessons of the retransplantation of scarce vital organs. JAMA 270(20):2469–2474

    Article  Google Scholar 

  18. Bertsimas D, Farias VF, Trichakis N (2013) Fairness, efficiency, and flexibility in organ allocation for kidney transplantation. Oper Res 61(1):73–87

    Article  Google Scholar 

  19. Szolovits P (1995) Uncertainty and decisions in medical informatics. Methods Inf Med 34(1):111–121

    Article  Google Scholar 

  20. Charnes A, Cooper WW, Rhodes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444

    Article  Google Scholar 

  21. Karsak EE, Ahiska SS (2007) A common-weight MCDM framework for decision problems with multiple inputs and outputs. In: International Conference on Computational Science and Its Applications, Springer, pp 779–790

  22. Genç R (2008) The logistics management and coordination in procurement phase of organ transplantation. Tohoku J Exp Med 216(4):287–296

    Article  Google Scholar 

  23. Ahmadvand S, Pishvaee MS (2016) Design and planning organ transplantation network. In: Topcu YI, Kahraman C (eds) Operations Research Applications in Health Care Management. Springer

  24. Beliën J, De Boeck L, Colpaert J, Devesse S, Van den Bossche F (2013) Optimizing the facility location design of organ transplant centers. Decis Support Syst 54(4):1568–1579

    Article  Google Scholar 

  25. Zahiri B, Tavakkoli-Moghaddam R, Pishvaee MS (2014) A robust possibilistic programming approach to multi-period location–allocation of organ transplant centers under uncertainty. Comput Ind Eng 74:139–148

    Article  Google Scholar 

  26. Bruni ME, Conforti D, Sicilia N, Trotta S (2006) A new organ transplantation location–allocation policy: a case study of Italy. Health Care Manag Sci 9(2):125–142

    Article  Google Scholar 

  27. Demirci MC, Schaefer AJ, Romeijn HE, Roberts MS (2012) An exact method for balancing efficiency and equity in the liver allocation hierarchy. INFORMS J Comput 24(2):260–275

    Article  Google Scholar 

  28. Kong N, Schaefer AJ, Hunsaker B, Roberts MS (2010) Maximizing the efficiency of the US liver allocation system through region design. Manag Sci 56(12):2111–2122

    Article  Google Scholar 

  29. Stahl JE, Kong N, Shechter SM, Schaefer AJ, Roberts MS (2005) A methodological framework for optimally reorganizing liver transplant regions. Med Decis Mak 25(1):35–46

    Article  Google Scholar 

  30. Alagoz O, Schaefer AJ, Roberts MS (2009) Optimizing organ allocation and acceptance. In: Handbook of Optimization in Medicine. Springer, pp 1–24

  31. Alagoz O, Maillart LM, Schaefer AJ, Roberts MS (2004) The optimal timing of living-donor liver transplantation. Manag Sci 50(10):1420–1430

    Article  Google Scholar 

  32. Su X, Zenios SA (2005) Patient choice in kidney allocation: a sequential stochastic assignment model. Oper Res 53(3):443–455

    Article  Google Scholar 

  33. Su X, Zenios SA (2006) Recipient choice can address the efficiency-equity trade-off in kidney transplantation: a mechanism design model. Manag Sci 52(11):1647–1660

    Article  Google Scholar 

  34. Alagoz O, Maillart LM, Schaefer AJ, Roberts MS (2007) Determining the acceptance of cadaveric livers using an implicit model of the waiting list. Oper Res 55(1):24–36

    Article  Google Scholar 

  35. Zenios SA (1999) Modeling the transplant waiting list: a queueing model with reneging. Queueing syst 31(3–4):239–251

    Article  Google Scholar 

  36. Roth AE, Sonmez T, Unver MU (2003) Kidney exchange. National Bureau of Economic Research

  37. David I, Yechiali U (1985) A time-dependent stopping problem with application to live organ transplants. Oper Res 33(3):491–504

    Article  Google Scholar 

  38. David I, Yechiali U (1990) Sequential assignment match processes with arrivals of candidates and offers. Probab Eng Inf Sci 4(04):413–430

    Article  Google Scholar 

  39. David I, Yechiali U (1995) One-attribute sequential assignment match processes in discrete time. Oper Res 43(5):879–884

    Article  Google Scholar 

  40. Ahn J-H, Hornberger JC (1996) Involving patients in the cadaveric kidney transplant allocation process: a decision-theoretic perspective. Manag Sci 42(5):629–641

    Article  Google Scholar 

  41. Zenios SA, Chertow GM, Wein LM (2000) Dynamic allocation of kidneys to candidates on the transplant waiting list. Oper Res 48(4):549–569

    Article  Google Scholar 

  42. Fix M (2016) HLA Matching, Antibodies, and You. http://web.stanford.edu/dept/HPS/transplant/html/hla.html

  43. Wolfe R, McCullough K, Schaubel D, Kalbfleisch J, Murray S, Stegall MD, Leichtman A (2008) Calculating life years from transplant (LYFT): methods for kidney and kidney-pancreas candidates. Am J Transplant 8(4p2):997–1011

    Article  Google Scholar 

  44. 2007 Annual Data Report (2007) Scientific Registry of Transplant Recipients. http://srtr.transplant.hrsa.gov/annual_reports/Default.aspx

  45. About CPRA - OPTN. (2016). https://optn.transplant.hrsa.gov/resources/allocation-calculators/about-cpra/

  46. Roll Y, Cook WD, Golany B (1991) Controlling factor weights in data envelopment analysis. IIE Trans 23(1):2–9

    Article  Google Scholar 

  47. Cook WD, Kress M (1990) A data envelopment model for aggregating preference rankings. Manag Sci 36(11):1302–1310

    Article  Google Scholar 

  48. Cook WD, Kress M (1991) A multiple criteria decision model with ordinal preference data. Eur J Oper Res 54(2):191–198

    Article  Google Scholar 

  49. Ganley JA, Cubbin JS (1992) Public sector efficiency measurement: Applications of data envelopment analysis. Elsevier Science Inc.

  50. Sinuany-Stern Z, Mehrez A, Barboy A (1994) Academic departments efficiency via DEA. Comput Oper Res 21(5):543–556

    Article  Google Scholar 

  51. Sinuany-Stern Z, Friedman L (1998) DEA and the discriminant analysis of ratios for ranking units. Eur J Oper Res 111(3):470–478

    Article  Google Scholar 

  52. Liu F-HF, Peng HH (2008) Ranking of units on the DEA frontier with common weights. Comput Oper Res 35(5):1624–1637

    Article  Google Scholar 

  53. Charnes A, Cooper WW, Rhodes E (1987) Measuring efficiency of decision making units. Eur J Oper Res 2:429–444

    Article  Google Scholar 

  54. Hollingsworth B (2008) The measurement of efficiency and productivity of health care delivery. Health Econ 17(10):1107–1128

    Article  Google Scholar 

  55. Ineveld M, Oostrum J, Vermeulen R, Steenhoek A, Klundert J (2016) Productivity and quality of Dutch hospitals during system reform. Health Care Manag Sci 19(3):279–290

  56. Ozcan YA, Begun JW, McKinney MM (1999) Benchmarking organ procurement organizations: a national study. Health Serv Res 34(4):855

    Google Scholar 

  57. Li X-B, Reeves GR (1999) A multiple criteria approach to data envelopment analysis. Eur J Oper Res 115(3):507–517

    Article  Google Scholar 

  58. Karsak E, Ahiska S (2005) Practical common weight multi-criteria decision-making approach with an improved discriminating power for technology selection. Int J Prod Res 43(8):1537–1554

    Article  Google Scholar 

  59. Tavana M, Khalili-Damghani K (2014) A new two-stage Stackelberg fuzzy data envelopment analysis model. Measurement 53:277–296

    Article  Google Scholar 

  60. Zadeh LA (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets Syst 1(1):3–28

    Article  Google Scholar 

  61. Lertworasirikul S, Fang S-C, Joines JA, Nuttle HL (2003) Fuzzy data envelopment analysis (DEA): a possibility approach. Fuzzy Sets Syst 139(2):379–394

    Article  Google Scholar 

  62. Lertworasirikul S, Fang S-C, Joines JA, Nuttle HL (2003) Fuzzy data envelopment analysis: A credibility approach. In: Fuzzy sets based heuristics for optimization. Springer, pp 141–158

  63. Liu B, Liu Y-K (2002) Expected value of fuzzy variable and fuzzy expected value models. IEEE Trans Fuzzy Syst 10(4):445–450

    Article  Google Scholar 

  64. Liu B (2004) Uncertainty theory: an introduction to its axiomatic foundations. Springer-Verlag, Berlin

    Book  Google Scholar 

  65. Pishvaee M, Razmi J, Torabi S (2014) An accelerated benders decomposition algorithm for sustainable supply chain network design under uncertainty: a case study of medical needle and syringe supply chain. Transp Res E Logist Transp Rev 67:14–38

    Article  Google Scholar 

  66. Prade DDH, Dubois D (1988) Possibility theory: an approach to computerized processing of uncertainty. NY: Plenum

  67. Zhu H, Zhang J (2009) A credibility-based fuzzy programming model for APP problem. In: Artificial Intelligence and Computational Intelligence, AICI'09. International Conference on, 2009. IEEE, pp 455–459

  68. Rouhani S (2016) Robust organ transplant logistics network design under uncertainty in Iran. Iran University of Science and Technology

  69. Charnes A, Cooper WW (1959) Chance-constrained programming. Manag Sci 6(1):73–79

    Article  Google Scholar 

  70. Zhu J (2014) Quantitative models for performance evaluation and benchmarking: data envelopment analysis with spreadsheets, vol 213. Springer

  71. Babazadeh R, Razmi J, Pishvaee MS (2016) Sustainable cultivation location optimization of the Jatropha Curcas L. under uncertainty: a unified fuzzy data envelopment analysis approach. Measurement 89:252–260

    Article  Google Scholar 

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  1. School of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran

    Sahar Ahmadvand & Mir Saman Pishvaee

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  1. Sahar Ahmadvand
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  2. Mir Saman Pishvaee
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Correspondence to Mir Saman Pishvaee.

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Ahmadvand, S., Pishvaee, M.S. An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach. Health Care Manag Sci 21, 587–603 (2018). https://doi.org/10.1007/s10729-017-9414-6

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