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The perils of meta-regression to identify clinical decision support system success factors.


ABSTRACT: Clinical decision support interventions are typically heterogeneous in nature, making it difficult to identify why some interventions succeed while others do not. One approach to identify factors important to the success of health information systems is the use of meta-regression techniques, in which potential explanatory factors are correlated with the outcome of interest. This approach, however, can result in misleading conclusions due to several issues. In this manuscript, we present a cautionary case study in the context of clinical decision support systems to illustrate the limitations of this type of analysis. We then discuss implications and recommendations for future work aimed at identifying success factors of medical informatics interventions. In particular, we identify the need for head-to-head trials in which the importance of system features is directly evaluated in a prospective manner.

SUBMITTER: Fillmore CL 

PROVIDER: S-EPMC4866642 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

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The perils of meta-regression to identify clinical decision support system success factors.

Fillmore Christopher L CL   Rommel Casey A CA   Welch Brandon M BM   Zhang Mingyuan M   Kawamoto Kensaku K  

Journal of biomedical informatics 20150518


Clinical decision support interventions are typically heterogeneous in nature, making it difficult to identify why some interventions succeed while others do not. One approach to identify factors important to the success of health information systems is the use of meta-regression techniques, in which potential explanatory factors are correlated with the outcome of interest. This approach, however, can result in misleading conclusions due to several issues. In this manuscript, we present a cautio  ...[more]

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