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Essays on the management of appointments for chronic conditions

Nenova, Zlatana (2017) Essays on the management of appointments for chronic conditions. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Treating chronic conditions is a fairly complex task, which requires well-timed appointments to control one's disease progression. In my dissertation I would like to optimize the monitoring strategies and better predict the demand-for-care of patients with chronic kidney disease (CKD). To do that I design a chronic disease monitoring framework which consists of forecasting, survival analysis and Markov Decision Process (MDP) models. First, I propose a forecasting model which quantifies the impact of CKD-related doctor's appointments on patient's disease progression. The model accounts for patient's comorbidities, vital signs, and important laboratory values. Second, I propose a survival analysis model, which estimates the expected life days of a patient given his or her current health status. Finally, I use the information gained from the first two models to parametrize and solve the MDP, which can suggest monitoring strategies and predict medium-term demand for CKD-patient-care in a clinic. In addition to the chronic disease monitoring framework, I examine CKD patient characteristics associated with a higher resource utilization.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Nenova, Zlatanaznenova@katz.pitt.eduzdn3
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairShang, JenniferSHANG@katz.pitt.eduSHANG
Committee MemberMay, Jerroldjerrymay@katz.pitt.edujerrymay
Committee MemberHotchkiss,
Committee MemberVargas, LuisLGVARGAS@pitt.eduLGVARGAS
Committee MemberMaillart, Lisamaillart@pitt.edumaillart
Date: 28 September 2017
Date Type: Publication
Defense Date: 5 June 2017
Approval Date: 28 September 2017
Submission Date: 31 July 2017
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 144
Institution: University of Pittsburgh
Schools and Programs: Joseph M. Katz Graduate School of Business > Business Administration
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: optimal appointment allocation, chronic disease, Markov Decision Process
Date Deposited: 28 Sep 2017 15:08
Last Modified: 28 Sep 2017 15:08


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