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Studies on Using Data-Driven Decision Support Systems to Improve Personalized Medicine Processes

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서명/저자사항Studies on Using Data-Driven Decision Support Systems to Improve Personalized Medicine Processes.
개인저자Cameron, Kellas Ross.
단체저자명Boston University. Management.
발행사항[S.l.]: Boston University., 2018.
발행사항Ann Arbor: ProQuest Dissertations & Theses, 2018.
형태사항170 p.
기본자료 저록Dissertation Abstracts International 79-11A(E).
Dissertation Abstract International
ISBN9780438146891
학위논문주기Thesis (Ph.D.)--Boston University, 2018.
일반주기 Source: Dissertation Abstracts International, Volume: 79-11(E), Section: A.
Adviser: Nitin R. Joglekar.
요약This dissertation looks at how new sources of information should be incorporated into medical decision-making processes to improve patient outcomes and reduce costs. There are three fundamental challenges that must be overcome to effectively use
요약The first study looks at how we can infer which patients will receive the most value from genomic testing. The difficult statistical problem is how to separate the distribution of patients, based on ex-ante factors, to identify the best candidat
요약The second study focuses on understanding how technology-enabled continuity of care (TECC) for Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF) patients can be utilized to improve patient engagement, measured in te
요약The third study looks at how data-driven decision support systems can allow physicians to more accurately understand which patients are at high-risk of readmission. We look at how we can use available patient-specific information for patients ad
요약Taken together, these three studies allow us to build a robust theory to tackle these challenges, both operational and policy-related, that need to be addressed for physicians to take advantage of the growing availability of patient-specific inf
일반주제명Management.
Health care management.
언어영어
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