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

Abstract

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 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 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®. We compared error rates, confidence levels, and response times.

Results: We 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/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® on antibiotic prescriptions in real clinical practice.

Keywords: antibiotics; clinical decision support system; clinical practice guidelines; infectious diseases; primary care; visualization.

Figure 1.

Visualization of the weighted drug properties with rainbow boxes. Example of otitis in a child over the age of 6 years, without allergy at the top and with allergy to beta-lactam and sulfonamide at the bottom.

Figure 2.

Diagram of the crossover study (SUS: System Usability Scale).

Figure 3.

Error rate for simple and complex clinical cases by type of disease. The error rate was 24%–38% higher for clinical cases relating to pneumonia and pharyngitis than for other diseases. The missing bar for otitis and sinusitis corresponds to an error rate of 0%.

Figure 4.

Confidence level for simple and complex clinical cases by type of disease.

Figure 5.

Response time for simple and complex clinical cases by type of disease.

Figure 6.

Distribution of answers to each question of the SUS (System Usability Scale).