Developing a model of psychiatric visit non-adherence

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Developing a model of psychiatric visit non-adherence

Please use this identifier to cite or link to this item: http://hdl.handle.net/10355/8335

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dc.contributor.advisor Savage, Grant T. (Grant Theodore), 1954- en_US
dc.contributor.advisor Gong, Yang, Ph. D. en_US
dc.contributor.author Alafaireet, Patricia E. en_US
dc.coverage.spatial United States
dc.date.accessioned 2010-08-23T16:43:31Z
dc.date.available 2010-08-23T16:43:31Z
dc.date.issued 2010 en_US
dc.date.submitted 2010 Spring en_US
dc.identifier.other AlafaireetP-051410-D3194 en_US
dc.identifier.uri http://hdl.handle.net/10355/8335
dc.description The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. en_US
dc.description Title from PDF of title page (University of Missouri--Columbia, viewed on August 3, 2010). en_US
dc.description Includes bibliographical references en_US
dc.description Vita. en_US
dc.description Thesis advisor: Grant T. Savage. en_US
dc.description Thesis advisor: Yang Gong. en_US
dc.description Ph. D. University of Missouri-Columbia 2010. en_US
dc.description Dissertations, Academic -- University of Missouri--Columbia -- health informatics. en_US
dc.description.abstract Non-adherence to psychiatry visits costs the US mental health care system more than one hundred billion dollars annually. Non-adherent visits undermine improvements to patient care quality, erode patient well-being, and prevent the effective use of technology driven improvements to health care quality. Psychiatric visit non-attendance is often perceived as an intractable problem, because of the direction taken in previous studies of the problem. Previous research into the issue of visit non-adherence focus either on specific patient demographics or on redundant scheduling methods, neither of which addresses quality of care issues or the development of useful tools to decrease visit non-adherence. This formative study addressed the issue of visit non-adherence by leveraging readily available electronic billing and scheduling system data, as well as data from an EMR, to identify and analyze a set of determinants of visit non-adherence. Three strategies, statistical analysis, machine learning/data mining and model comparison, were utilized in the analysis. Results from this multi-phase study provide a parsimonious set of visit non-adherence determinants and a useful model based on those determinants capable of supporting the development of predictive tools suitable for use in ambulatory health care services delivery. en_US
dc.format.extent ii, 238 pages en_US
dc.language.iso en_US en_US
dc.publisher University of Missouri-Columbia en_US
dc.subject.mesh Mental Health Services en_US
dc.subject.mesh Appointments and Schedules en_US
dc.subject.mesh Patient Compliance en_US
dc.subject.mesh Quality Assurance, Health Care en_US
dc.subject.mesh Medical Infomatics Computing en_US
dc.subject.mesh Forecasting en_US
dc.subject.mesh Models, Organizational en_US
dc.title Developing a model of psychiatric visit non-adherence en_US
dc.type Thesis en_US
thesis.degree.discipline Health informatics en_US
thesis.degree.grantor University of Missouri--Columbia en_US
thesis.degree.name Ph. D. en_US
thesis.degree.level Doctoral en_US
dc.identifier.merlin b7742976x en_US
dc.identifier.merlin b7742976x
dc.identifier.oclc 653290662 en_US
dc.relation.ispartofcommunity University of Missouri-Columbia. Graduate School. Theses and Dissertations. Dissertations. 2010 Dissertations


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