Data-Driven Management of Post-transplant Medications: An Ambiguous Partially Observable Markov Decision Process Approach

References

• Ahn D, Choi S, Gale D, Kariv S (2014) Estimating ambiguity aversion in a portfolio choice experiment. Quant. Econom. 5(2):195–223.Crossref, Google Scholar
• Alagoz O, Bryce CL, Shechter S, Schaefer A, Chang CCH, Angus DC, Roberts MS (2005) Incorporating biological natural history in simulation models: empirical estimates of the progression of end-stage liver disease. Medical Decision Making 25(6):620–632.Crossref, Google Scholar
• American Diabetes Association (2012) Standards of medical care in diabetes. Diabetes Care 35:S11–S63.Crossref, Google Scholar
• American Heart Association (2018) Understanding blood pressure readings. Accessed May 5, 2017, http://www.heart.org/HEARTORG/Conditions/HighBloodPressure/KnowYourNumbers/Understanding-Blood-Pressure-Readings_UCM_301764_Article.jsp#.WzQibadKg2w.Google Scholar
• Arad A, Gayer G (2012) Imprecise data sets as a source of ambiguity: A model and experimental evidence. Management Sci. 58(1):188–202.Link, Google Scholar
• Ata B, Skaro A, Tayur S (2016) OrganJet: Overcoming geographical disparities in access to deceased donor kidneys in the United States. Management Sci. 63(9):2776–2794.Link, Google Scholar
• Ayer T, Alagoz O, Stout NK (2012) OR forum—A POMDP approach to personalize mammography screening decisions. Oper. Res. 60(5):1019–1034.Link, Google Scholar
• Bazin C, Guinedor A, Barau C, Gozalo C, Grimbert P, Duvoux C, Furlan V, Massias L, Hulin A (2010) Evaluation of the Architect tacrolimus assay in kidney, liver, and heart transplant recipients. J. Pharmaceutical Biomedical Anal. 53(4):997–1002.Crossref, Google Scholar
• Bennett CM, Guo M, Dharmage SC (2007) HbA1c as a screening tool for detection of type 2 diabetes: A systematic review. Diabetic Medicine 24(4):333–343.Crossref, Google Scholar
• Bentley TS, Hanson SG (2011) 2011 U.S. organ and tissue transplant cost estimates and discussion. Report, Milliman, Brookfield, WI.Google Scholar
• Berger L, Bleichrodt H, Eeckhoudt L (2013) Treatment decisions under ambiguity. J. Health Econom. 32(3):559–569.Crossref, Google Scholar
• Bertsimas D, Farias VF, Trichakis N (2013) Fairness, efficiency, and flexibility in organ allocation for kidney transplantation. Oper. Res. 61(1):73–87.Link, Google Scholar
• Boloori A, Saghafian S, Chakkera HA, Cook CB (2015) Characterization of remitting and relapsing hyperglycemia in post-renal-transplant recipients. PLoS One 10(11):e0142363.Crossref, Google Scholar
• Bowman LJ, Brennan DC (2008) The role of tacrolimus in renal transplantation. Expert Opinion Pharmacotherapy 9(4):635–643.Crossref, Google Scholar
• Buuren S, Groothuis-Oudshoorn K (2011) MICE: Multivariate imputation by chained equations in R. J. Statist. Software 45(3):1–67.Crossref, Google Scholar
• Chakkera HA, Weil EJ, Castro J, Heilman RL, Reddy KS, Mazur MJ, Hamawi K, et al.. (2009) Hyperglycemia during the immediate period after kidney transplantation. Clinical J. Amer. Soc. Nephrology 4(4):853–859.Crossref, Google Scholar
• Chen Y, Katuščák P, Ozdenoren E (2007) Sealed bid auctions with ambiguity: Theory and experiments. J. Econom. Theory 136(1):513–535.Crossref, Google Scholar
• Delage E, Mannor S (2010) Percentile optimization for Markov decision processes with parameter uncertainty. Oper. Res. 58(1):203–213.Link, Google Scholar
• Denton BT, Kurt M, Shah ND, Bryant SC, Smith SA (2009) Optimizing the start time of statin therapy for patients with diabetes. Medical Decision Making 29:351–367.Crossref, Google Scholar
• Erenay FS, Alagoz O, Said A (2014) Optimizing colonoscopy screening for colorectal cancer prevention and surveillance. Manufacturing Service Oper. Management 16(3):381–400.Link, Google Scholar
• Ghirardato P, Maccheroni F, Marinacci M (2004) Differentiating ambiguity and ambiguity attitude. J. Econom. Theory 118(2):133–173.Crossref, Google Scholar
• Ghisdal L, Van Laecke S, Abramowicz MJ, Vanholder R, Abramowicz D (2012) New-onset diabetes after renal transplantation risk assessment and management. Diabetes Care 35(1):181–188.Crossref, Google Scholar
• Goh J, Bayati M, Zenios SA, Singh S, Moore D (2018) Data uncertainty in Markov chains: Application to cost-effectiveness analyses of medical innovations. Oper. Res. 66(3):697–715.Link, Google Scholar
• Han PKJ, Reeve BB, Moser RP, Klein WMP (2009) Aversion to ambiguity regarding medical tests and treatments: Measurement, prevalence, and relationship to sociodemographic factors. J. Health Comm. 14(6):556–572.Crossref, Google Scholar
• Hauskrecht M (2000) Value-function approximations for partially observable Markov decision processes. J. Artificial Intelligence Res. 13:33–94.Crossref, Google Scholar
• Iyengar GN (2005) Robust dynamic programming. Math. Oper. Res. 30(2):257–280.Link, Google Scholar
• Kaufman DL, Schaefer AJ, Roberts MS (2011) Living-donor liver transplantation timing under ambiguous health state transition probabilities—Extended abstract. Accessed January 10, 2017, http://www-personal.umich.edu/∼davidlk/pubs/robustLivingDonor.pdf.Google Scholar
• Kromann H, Borch E, Gale EA (1981) Unnecessary insulin treatment for diabetes. British Medical J. 283(6303):1386–1388.Crossref, Google Scholar
• Mason JE, Denton BT, Shah ND, Smith SA (2014) Optimizing the simultaneous management of blood pressure and cholesterol for type 2 diabetes patients. Eur. J. Oper. Res. 233:727–738.Crossref, Google Scholar
• MedPlus (2018) Medical encyclopedia. Accessed May 5, 2017, https://www.nlm.nih.gov/medlineplus/encyclopedia.html.Google Scholar
• Monahan GE (1982) State of the art—A survey of partially observable Markov decision processes: Theory, models, and algorithms. Management Sci. 28(1):1–16.Link, Google Scholar
• Nilim A, El Ghaoui L (2005) Robust control of Markov decision processes with uncertain transition matrices. Oper. Res. 53(5):780–798.Link, Google Scholar
• Organ Procurement and Transplantation Network (2011) OPTN/SRTR annual report: Transplant data 1999–2008. Accessed February 23, 2017, https://srtr.transplant.hrsa.gov/archives.aspx.Google Scholar
• Papadimitriou CH, Tsitsiklis JN (1987) The complexity of Markov decision processes. Math. Oper. Res. 12(3):441–450.Link, Google Scholar
• Peysakhovich A, Karmarkar UR (2015) Asymmetric effects of favorable and unfavorable information on decision making under ambiguity. Management Sci. 62(8):2163–2178.Link, Google Scholar
• Saghafian S (2018) Ambiguous partially observable Markov decision processes: Structural results and applications. J. Econom. Theory 178:1–35.Crossref, Google Scholar
• Sassi F (2006) Calculating QALYs, comparing QALY and DALY calculations. Health Policy Planning 21(5):402–408.Crossref, Google Scholar
• Schiff J, Cole E, Cantarovich M (2007) Therapeutic monitoring of calcineurin inhibitors for the nephrologist. Clinical J. Amer. Soc. Nephrology 2(2):374–384.Crossref, Google Scholar
• Smallwood RD, Sondik EJ (1973) The optimal control of partially observable Markov processes over a finite horizon. Oper. Res. 21(5):1071–1088.Link, Google Scholar
• Staatz CE, Tett SE (2004) Clinical pharmacokinetics and pharmacodynamics of tacrolimus in solid organ transplantation. Clinical Pharmacokinetics 43(10):623–653.Crossref, Google Scholar
• Staatz C, Taylor P, Tett S (2001) Low tacrolimus concentrations and increased risk of early acute rejection in adult renal transplantation. Nephrology Dialysis Transplantation 16(9):1905–1909.Crossref, Google Scholar
• Steimle LN, Kaufman DL, Denton BT (2018) Multi-model Markov decision processes: A new method for mitigating parameter ambiguity. Working paper, University of Michigan, Ann Arbor.Google Scholar
• Su X, Zenios SA (2005) Patient choice in kidney allocation: A sequential stochastic assignment model. Oper. Res. 53(3):443–455.Link, Google Scholar
• United Network of Organ Sharing (2018) Transplant trends. Accessed May 20, 2017, https://unos.org/data/transplant-trends/#transplants_by_organ_type+year+2017.Google Scholar
• Welch LR (2003) Hidden Markov models and the Baum-Welch algorithm. IEEE Inform. Theory Soc. Newsletter 53(4):10–13.Google Scholar
• Whitt W (1982) Multivariate monotone likelihood ratio and uniform conditional stochastic order. J. Appl. Probab. 19(3):695–701.Crossref, Google Scholar
• Xu H, Mannor S (2012) Distributionally robust Markov decision processes. Math. Oper. Res. 37(2):288–300.Link, Google Scholar
• Yasuda SU, Zhang L, Huang SM (2008) The role of ethnicity in variability in response to drugs: Focus on clinical pharmacology studies. Clinical Pharmacology Therapeutics 84(3):417–423.Crossref, Google Scholar
• Zhang J (2011) Partially observable Markov decision processes for prostate cancer screening. PhD thesis, North Carolina State University, Raleigh.Google Scholar
• Zhang Y, Steimle LN, Denton BT (2017) Robust Markov decision processes for medical treatment decisions. Working paper, University of Michigan, Ann Arbor.Google Scholar