Simulation Trials for Evaluating Clinical Decision Support Systems

The evaluation of clinical decision support systems (CDSS) during randomized clinical trials in very long and complex to set up. Simulation trials consist of evaluating the CDSS on fictitious patients. While they cannot entirely replace clinical trials, they are simpler to perform and offer addition...

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Published inStudies in health technology and informatics Vol. 327; p. 213
Main Authors Lamy, Jean-Baptiste, Falcoff, Hector, Dubois, Sophie, Meneton, Pierre, Tsopra, Rosy, Saab, Antoine
Format Journal Article
LanguageEnglish
Published Netherlands 15.05.2025
Subjects
Computer Simulation
Decision Support Systems, Clinical
Humans
Randomized Controlled Trials as Topic - methods
Evaluation
Simulation trial
Clinical Decision Support Systems
Online AccessGet more information
ISSN1879-8365
DOI10.3233/SHTI250304

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Abstract The evaluation of clinical decision support systems (CDSS) during randomized clinical trials in very long and complex to set up. Simulation trials consist of evaluating the CDSS on fictitious patients. While they cannot entirely replace clinical trials, they are simpler to perform and offer additional possibilities. In this paper, we present recommendations for the design of simulation trials evaluating CDSS, based on the lessons learned during two recent studies. We also propose a model of protocol that maximizes statistical power and avoids several common biases, and an R code template for statistical analysis using linear mixed models.
AbstractList The evaluation of clinical decision support systems (CDSS) during randomized clinical trials in very long and complex to set up. Simulation trials consist of evaluating the CDSS on fictitious patients. While they cannot entirely replace clinical trials, they are simpler to perform and offer additional possibilities. In this paper, we present recommendations for the design of simulation trials evaluating CDSS, based on the lessons learned during two recent studies. We also propose a model of protocol that maximizes statistical power and avoids several common biases, and an R code template for statistical analysis using linear mixed models.
Author Meneton, Pierre
Falcoff, Hector
Saab, Antoine
Dubois, Sophie
Tsopra, Rosy
Lamy, Jean-Baptiste
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  organization: Quality and Patient Safety Dpt., Lebanese Hospital Geitaoui-UMC, Beirut Lebanon
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SubjectTerms Computer Simulation
Decision Support Systems, Clinical
Humans
Randomized Controlled Trials as Topic - methods
Title Simulation Trials for Evaluating Clinical Decision Support Systems
URI https://www.ncbi.nlm.nih.gov/pubmed/40380416
Volume 327
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