NEW STATISTICAL METHODS TO BETTER LEVERAGE EMERGING HEALTH CARE UTILIZATION DATA

dc.contributor.advisorSmith, Paul Jen_US
dc.contributor.advisorGolden, Bruce Len_US
dc.contributor.authorZhang, Xuen_US
dc.contributor.departmentMathematicsen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2020-11-13T06:30:11Z
dc.date.available2020-11-13T06:30:11Z
dc.date.issued2020en_US
dc.description.abstractImproving the healthcare system is an important task that is always both socially and individually beneficial, and statistics is one of the useful tools that have been applied in pursuit of this goal. However, limitations on current methods and the introduction of new forms of data have created many new challenges and research opportunities. It is therefore crucial to explore and extend statistical methods to better understand and leverage healthcare utilization data, particularly recent and emerging data in new forms. In this dissertation, we develop and apply various innovative statistical methods to address five specific healthcare issues. First, we successfully develop a novel approach to model the length of hospital stay using mixture distributions through an EM algorithm. Second, we extend a two-state continuous time Markov chain to estimate patient readmission risk at a large academic hospital in the U.S. Third, we study changes in accessibility in emergency departments from 2016 to 2018 among 21 hospitals in Maryland Region III. Fourth, we investigate the impact of the global budget payment model on emergency department accessibility. Lastly, we use a multi-state Markov model to explore cascading events during emergency room crowding, also in Region III of Maryland.en_US
dc.identifierhttps://doi.org/10.13016/pjw8-60xi
dc.identifier.urihttp://hdl.handle.net/1903/26674
dc.language.isoenen_US
dc.subject.pqcontrolledStatisticsen_US
dc.titleNEW STATISTICAL METHODS TO BETTER LEVERAGE EMERGING HEALTH CARE UTILIZATION DATAen_US
dc.typeDissertationen_US

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