ArticleJournal of the American Medical Informatics Association : JAMIA2019
Helping GPs to extrapolate guideline recommendations to patients for whom there are no explicit recommendations, through the visualization of drug properties. The example of AntibioHelp® in bacterial diseases.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Adoption and Use of Social Media in Health Care Among Medical Residents: Cross-Sectional Study.JMIR medical education · 2026Article
- Article
- Clinical Decision Support Systems for Antibiotic Prescribing: An Inventory of Current French Language Tools.Antibiotics (Basel, Switzerland) · 2022Article
- A Web Interface for Antibiotic Prescription Recommendations in Primary Care: User-Centered Design Approach.Journal of medical Internet research · 2021Article
- Accuracy and Effects of Clinical Decision Support Systems Integrated With BMJ Best Practice-Aided Diagnosis: Interrupted Time Series Study.JMIR medical informatics · 2020Article
- What rationale do GPs use to choose a particular antibiotic for a specific clinical situation?BMC family practice · 2019Article
- Need for innovation in electronic health record-based medication alerts.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- A usability study to improve a clinical decision support system for the prescription of antibiotic drugs.PloS one · 2019Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionClinical decision support systems (CDSS) implementing clinical practice guidelines (CPGs) have 2 main limitations: they target only patients for whom CPGs provide explicit recommendations, and their rationale may be difficult to understand. These 2 limitations result in poor CDSS adoption. We designed AntibioHelp® as a CDSS for antibiotic treatment. It displays the recommended and nonrecommended antibiotics, together with their properties, weighted by degree of importance as outlined in the CPGs. The aim of this study was to determine whether AntibioHelp® could increase the confidence of general practitioners (GPs) in CPG recommendations and help them to extrapolate guidelines to patients for whom CPGs provide no explicit recommendations. MATERIALS AND
methodsWe carried out a 2-stage crossover study in which GPs responded to clinical cases using CPG recommendations either alone or with explanations displayed through AntibioHelp®. We compared error rates, confidence levels, and response times.
resultsWe included 64 GPs. When no explicit recommendation existed for a particular situation, AntibioHelp® significantly decreased the error rate (-41%, P value = 6x10-13), and significantly increased GP confidence (+8%, P value = .02). This CDSS was considered to be usable by GPs (SUS score = 64), despite a longer interaction time (+9-22 seconds). By contrast, AntibioHelp® had no significant effect if there was an explicit recommendation. DISCUSSION/
conclusionThe visualization of weighted antibiotic properties helps GPs to extrapolate recommendations to patients for whom CPGs provide no explicit recommendations. It also increases GP confidence in their prescriptions for these patients. Further evaluations are required to determine the impact of AntibioHelp® on antibiotic prescriptions in real clinical practice.
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