Date of Award

Spring 2014

Degree Type

Thesis

Degree Name

Master of Science (MS)

Department

Industrial Engineering

First Advisor

Nan Kong

Committee Member 1

Andrew Liu

Abstract

More than 145 million people live with at least one chronic condition, and almost half of them have multiple conditions. As a result, many managed care and integrated delivery systems have taken a great interest in alleviating the many deficiencies in managing the current care system that spans across various care delivery settings. In addition, many Americans have to rely on some social health insurance plan to cover her care expenses. As a result, these patients often may not been sufficiently cured but have to be transitioned to less expensive but less medically intensive facilities, due to the increasing pressure on the social health insurance programs to save their total spending. This in turns increases the risk of being readmitted to more expensive facilities sooner. In this thesis, we systematically study stochastic transitions within a system of care delivery. We investigate how to modify insurable length of stay to reduce the total care spending and improve the quality of care to individual patients.

We first develop a chronic care cycle model to optimize the transitions between two types of settings: the inpatient care setting and the home- and community-based care setting. By optimizing the number of covered episodes, and the coverage LOS for each episode, this model is intended to balance the tradeoff between the cost of staying and the cost of (forced) transition, as well as the tradeoff between current cost and future (opportunity) cost. The results indicate that as a public insurer, the best strategy will be only focusing on the early episodes and covering them unlimitedly.

We also develop a three-layer rehabilitation service process model and use discrete event simulation to study the transitions among three levels of rehabilitations: primary rehab, secondary rehab, and tertiary rehab. We test different values for on the coverage LOS for primary rehab and secondary rehab to balance the tradeoff between the current cost and future cost. We assume some relationship between the quantity of care and care transition probability, and observe their joint effect on cost and rehospitalization incidences in the given length of period. The results indicate that as a public insurer, the best strategy will be remaining current coverage on primary rehab but limiting coverage on secondary rehab.

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