Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form


Nemati Proon, Sepehr (2015) IMPROVING HEALTHCARE DELIVERY: LIVER HEALTH UPDATING AND SURGICAL PATIENT ROUTING. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

Primary Text

Download (991kB) | Preview


Growing healthcare expenditures in the United States require improved healthcare delivery practices. Organ allocation has been one of the most controversial subjects in healthcare due to the scarcity of donated human organs and various ethical concerns. The design of efficient surgical suites management systems and rural healthcare delivery are long-standing efforts to improve the quality of care. In this dissertation, we consider practical models in both domains with the goal of improving the quality of their services. In the United States, the liver allocation system prioritizes among patients on the waiting list based on the patients' geographical locations and their medical urgency. The prioritization policy within a given geographic area is based on the most recently reported health status of the patients, although blood type compatibility and waiting time on the list are used to break ties. Accordingly, the system imposes a health-status updating scheme, which requires patients to update their health status within a timeframe that depends on their last
reported health. However, the patients' ability to update their health status at any time point within this timeframe induces information asymmetry in the system. We study the problem of mitigating this information asymmetry in the liver allocation system. Specifically, we consider a joint patient and societal perspective to determine a set of Pareto-optimal updating schemes that minimize information asymmetry and data-processing burden. This approach combines three methodologies: multi-objective optimization, stochastic programming and Markov decision processes (MDPs). Using the structural properties of our proposed modeling approach, an efficient decomposition algorithm is presented to identify the exact efficient frontier of the Pareto-optimal updating schemes within any given degree of accuracy.
Many medical centers offer transportation to eligible patients. However, patients' transportation considerations are often ignored in the scheduling of medical appointments. In this dissertation, we propose an integrated approach that simultaneously considers routing and scheduling decisions of a set of elective outpatient surgery requests in the available operating
rooms (ORs) of a hospital. The objective is to minimize the total service cost that incorporates transportation and hospital waiting times for all patients. Focusing on the need of specialty or low-volume hospitals, we propose a computationally tractable model formulated as a set partitioning based problem. We present a branch-and-price algorithm to solve this problem, and discuss several algorithmic strategies to enhance the efficiency of the solution method. An extensive computational test using clinical data demonstrates the efficiency of our proposed solution method. This also shows the value of integrating routing and scheduling decisions, indicating that the healthcare providers can substantially improve the quality
of their services under this unified framework.


Social Networking:
Share |


Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Nemati Proon, Sepehrsen12@pitt.eduSEN12
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Thesis AdvisorSchaefer, Andrew J.schaefer@ie.pitt.eduSCHAEFER
Committee MemberMaillart, Lisa M.maillart@pitt.eduMAILLART
Committee MemberProkopyev, Oleg A.prokopyev@engr.pitt.eduDROLEG
Committee MemberRajgopal, Jayantrajgopal@pitt.eduRAJGOPAL
Committee MemberMirchandani, Prakashpmirchan@katz.pitt.eduPMIRCHAN
Committee MemberShylo, Oleg
Date: 9 April 2015
Date Type: Publication
Defense Date: 18 October 2013
Approval Date: 9 April 2015
Submission Date: 2 April 2014
Access Restriction: 5 year -- Restrict access to University of Pittsburgh for a period of 5 years.
Number of Pages: 106
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: Organ allocation, Operating rooms scheduling problem, Markov decision processes, branch-and-price, multi objective decision making, two-stage stochastic programming.
Date Deposited: 09 Apr 2016 05:00
Last Modified: 09 Apr 2020 05:15


Monthly Views for the past 3 years

Plum Analytics

Actions (login required)

View Item View Item