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Optimal Policies for the Acceptance of Living- and Cadaveric-Donor Livers

Alagoz, Oguzhan (2004) Optimal Policies for the Acceptance of Living- and Cadaveric-Donor Livers. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Transplantation is the only viable therapy for end-stage liverdiseases (ESLD) such as hepatitis B. In the United States,patients with ESLD are placed on a waiting list. When organsbecome available, they are offered to the patients on this waitinglist. This dissertation focuses on the decision problem faced bythese patients: which offer to accept and which to refuse? Thisdecision depends on two major components: the patient's currentand future health, as well as the current and future prospect fororgan offers. A recent analysis of liver transplant data indicatesthat 60\% of all livers offered to patients for transplantationare refused.This problem is formulated as a discrete-time Markov decisionprocess (MDP). This dissertation analyzes three MDP models, eachrepresenting a different situation. The Living-Donor-Only Modelconsiders the problem of optimal timing of living-donor livertransplantation, which is accomplished by removing an entire lobeof a living donor's liver and implanting it into the recipient.The Cadaveric-Donor-Only Model considers the problem ofaccepting/refusing a cadaveric liver offer when the patient is onthe waiting list but has no available living donor. In this model,the effect of the waiting list is incorporated into the decisionmodel implicitly through the probability of being offered a liver.The Living-and-Cadaveric-Donor Model is the most general model.This model combines the first two models, in that the patient isboth listed on the waiting list and also has an available livingdonor. The patient can accept the cadaveric liver offer, declinethe cadaveric liver offer and use the living-donor liver, ordecline both and continue to wait.This dissertation derives structural properties of all threemodels, including several sets of conditions that ensure theexistence of intuitively structured policies such as control-limitpolicies. The computational experiments use clinical data, andshow that the optimal policy is typically of control-limit type.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairSchaefer, Andrewschaefer@ie.pitt.eduSCHAEFER
Committee MemberBryce,
Committee MemberMaillart ,
Committee MemberMainak Mazumdar, Lisammazumd@engr.pitt.eduMMAZUMD
Committee MemberRoberts,
Committee MemberBailey, Matthewmdbailey@pitt.eduMDBAILEY
Date: 13 September 2004
Date Type: Completion
Defense Date: 12 July 2004
Approval Date: 13 September 2004
Submission Date: 26 July 2004
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Industrial Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Control-limit policy; Markov decision processes; medical decision making; organ transplantation; service operations
Other ID:, etd-07262004-183027
Date Deposited: 10 Nov 2011 19:53
Last Modified: 15 Nov 2016 13:46


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