DMCA
Evaluating Provider Adherence in a Trial of a Guideline-Based Decision Support System for Hypertension
| Citations: | 2 - 0 self |
BibTeX
@MISC{Chan_evaluatingprovider,
author = {A.S. Chan and R.W. Coleman and S.B. Martins and A. Advani and M.A. Musen and H.B. Bosworth and E.Z. Oddone and M.G. Shlipak and B.B. Hoffman and For Hypertension},
title = {Evaluating Provider Adherence in a Trial of a Guideline-Based Decision Support System for Hypertension},
year = {}
}
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Abstract
Measurement of provider adherence to a guideline-based decision support system (DSS) presents a number of important challenges. Establishing a causal relationship between the DSS and change in concordance requires consideration of both the primary intention of the guideline and different ways providers attempt to satisfy the guideline. During our work with a guideline-based decision support system for hypertension, ATHENA DSS, we document a number of subtle deviations from the strict hypertension guideline recommendations that ultimately demonstrate provider adherence. We believe that understanding these complexities is crucial to any valid evaluation of provider adherence. We also describe the development of an advisory evaluation engine that automates the interpretation of clinician adherence with the DSS on multiple levels, facilitating the high volume of complex data analysis that is created in a clinical trial of a guideline-based DSS.
Keyphrases
provider adherence guideline-based decision support system strict hypertension guideline recommendation advisory evaluation engine multiple level complex data analysis guideline-based ds subtle deviation primary intention valid evaluation athena ds causal relationship high volume important challenge clinical trial clinician adherence different way provider
