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Article type: Research Article
Authors: Huttin, Christine C.a; b
Affiliations: [a] ENDEPUsresearch Inc., USA | [b] University Aix Marseille, France | E-mail: [email protected]
Abstract: This paper is the last of a series of five methodological contributions in the field of stated preference studies for disease econometric models. It proposes several advances to integrate in the predictive model new variables on effects of computerization of medical records in clinical practice, adoption of new drug therapies and effect of different types of variables to control physicians’ attributes such as the type of visit disposition (with a variable on the referral process). Different stages of propagation of IT in clinical practice are analyzed for the type of information computerized in the medical records. Results of a clustering analysis on medical practices and the statistical results on the predictive disease models are presented on a diabetes type II analytical data set from the US National Medical Ambulatory Care Survey. The three new independent variables on ebilling, clusters of medical practices with different level of IT confirms previous results with a reduction of drug utilization with e billing and higher drug utilization for the more computerized group of practices. Drug utilization is also much lower when a physician requests a referral. Patient economics and its effects at the point of visit are clearly modified with the diffusion of IT.
Keywords: Innovativeness, patient economics, clinical choices sets, IT in medical practice, clustering
DOI: 10.3233/THC-160769
Journal: Technology and Health Care, vol. 25, no. 5, pp. 1005-1020, 2017
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