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

Rosy Tsopra (1, 2) , Karima Sedki (3) , Mélanie Courtine (3) , Hector Falcoff (4) , Antoine de Beco (4) , Ronni Madar (5) , Frédéric Mechaï (6, 7) , Jean-Baptiste Lamy (3)

1 HEGP - Hôpital Européen Georges Pompidou [APHP]
2 CRC (UMR_S_1138 / U1138) - Centre de Recherche des Cordeliers
3 LIMICS - Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé
4 SFTG - Société de Formation Thérapeutique du Généraliste
5 UFR SMBH - UFR Santé, Médecine et Biologie Humaine
6 Hôpital Avicenne [AP-HP]
7 IAME (UMR_S_1137 / U1137) - Infection, Anti-microbiens, Modélisation, Evolution

Introduction: Clinical 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 Anti-bioHelp V R 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 V R 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 Methods: We 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 V R. We compared error rates, confidence levels, and response times. Results: We included 64 GPs. When no explicit recommendation existed for a particular situation, AntibioHelp V R significantly decreased the error rate (À41%, P value ¼ 6x10 À13), and significantly increased GP confidence (þ8%, P value ¼ .02). This CDSS was considered to be usable by GPs (SUS score ¼ 64), despite a longer interaction time (þ9-22 seconds). By contrast, AntibioHelp V R had no significant effect if there was an explicit recommendation. Discussion/Conclusion: The 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 V R on antibiotic prescriptions in real clinical practice.

Mots clés: clinical decision support system; clinical practice guidelines; antibiotics; infectious diseases; primary care; visualization

Domaines: Santé publique et épidémiologie; Intelligence artificielle [cs.AI]

Rosy Tsopra, Karima Sedki, Mélanie Courtine, Hector Falcoff, Antoine de Beco, et al.. 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. Journal of the American Medical Informatics Association, 2019, 26 (10), pp.1010 - 1019. ⟨10.1093/jamia/ocz057⟩. ⟨hal-03479057⟩