Evaluating provider adherence in a trial of a guideline-based decision support system for hypertension.
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.
Chan
A S
AS
Stanford Medical Informatics, Stanford University School of Medicine, MSOB X-215, Stanford, CA 94305, USA.
Coleman
R W
RW
Martins
S B
SB
Advani
A
A
Musen
M A
MA
Bosworth
H B
HB
Oddone
E Z
EZ
Shlipak
M G
MG
Hoffman
B B
BB
Goldstein
M K
MK
D020000:Decision Support Systems, Clinical; D004360:Drug Therapy, Computer-Assisted; D019983:Guideline Adherence; D006801:Humans; D006973:Hypertension / Q000188:drug therapy*; D016347:Medical Records Systems, Computerized; D017410:Practice Guidelines as Topic; D014481:United States; D014493:United States Department of Veterans Affairs; D014584:User-Computer Interface