There has been an almost 60 percent increase in health care expenditures in the US in the past seven years. Employer-sponsored health coverage premiums have increased significantly (87 percent) in this same period. Besides the cost of care for chronic conditions such as migraine, arthritis and diabetes, absenteeism linked to these diseases also adds financial strain. Current health financial models focus on past spending instead of modeling based on current health burdens and future trends. This approach leads to suboptimal health maintenance and cost management. Identifying the diseases which affect the most employees and are also the most costly (in terms of productivity, work-loss-days, treatment etc) is necessary, since this allows the employer to identify which combination of policies may best address the health burdens. The current predictive health model limits the amount of diseases it models since it ignores incomplete data sets. This research investigated if by using Bayesian methodology it will be possible to create a comprehensive predictive model of the health burdens being faced by corporations, allowing for health decision makers to have comprehensive information when choosing policies. The first specific aim was to identify which diseases were the most costly to employers both directly and indirectly, and the pathogenesis of these diseases. Co-morbidity of diseases was also taken into account as in many cases these diseases are not treated independently. This information was taken into account when designing the models as the inference was disease specific. One of the contributions of this thesis is coherent incorporation of prior information into the proposed expert model. The Bayesian models were able to estimate the predicted disease burdens for corporations, including predicting the percentage of individuals with multiple diseases. The model was also comparable to, or better than current estimators on the market with limited input. The outputs of the model were also able to give further insight into the disease interactions which creates an avenue for further research in disease management.

This paper considers the adoption of Health Information Technology (HIT) by physician clinics with ten or fewer physicians. The paper considers the theoretical economics literature on technology adoption for a new technology and has a place in the empirical tests of these models. The two major hypotheses tested in the paper are that the probability of adopting HIT increases with the number of physicians working at the clinic and if the clinic is part of a chain of clinics, and that it also increases with increased competition at the market level measured by the number of clinics per 10,000 residents in a county. To test these hypotheses, the paper first estimates a baseline logit model followed by three hazard rate models. In each case, clinic size is found to have positive though not significant effect on the probability of adoption (in the logit model) or to decrease the predicted time to adoption for the clinic (in the hazard rate models), being in a chain of clinics is found to have a strong positive and significant on the probability of adoption, and increased competition is found to have a positive though not significant effect on the probability of adoption.

Thesis (Ph. D.)--University of Sydney, 2009. / Title from title screen (viewed Nov. 3, 2009) Includes tables and questionnaires. Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Public Health, Faculty of Medicine. Includes bibliography. Also available in print form.

Thesis (M.A.)--Humboldt State University, 2009. / Includes bibliographical references (leaves 51-56). Also available via Humboldt Digital Scholar.

Thesis (M.Sc.)--University of Alberta, 2010. / A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Master of Science in Speech Language Pathology, Department of Speech Pathology and Audiology. Title from pdf file main screen (viewed on January 24, 2010). Includes bibliographical references.

Thesis (Ph. D.)--UCLA, 2009. / Vita. Description based on print version record. Includes bibliographical references (leaves 145-167).

Thesis--University of California, San Francisco. / eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 255-260).

Thesis (Ph.D.)--Brown University, 2008. / Vita. Includes bibliographical references.

Diss. (sammanfattning) Stockholm : Karolinska institutet, 2007. / Härtill 4 uppsatser.

Thesis (Ph.D.)--University of Western Sydney, 2009. / A thesis presented to the University of Western Sydney, College of Health and Science, School of Computing and Mathematics, in fulfilment of the requirements for the degree of Doctor of Philosophy. Includes bibliographies.