General practitioners' deprescribing decisions in older adults with polypharmacy: a case vignette study in 31 countries

BACKGROUND: General practitioners (GPs) should regularly review patients' medications and, if necessary, deprescribe, as inappropriate polypharmacy may harm patients' health. However, deprescribing can be challenging for physicians. This study investigates GPs' deprescribing decisions in 31 countries. METHODS: In this case vignette study, GPs were invited to participate in an online survey containing three clinical cases of oldest-old multimorbid patients with potentially inappropriate polypharmacy. Patients differed in terms of dependency in activities of daily living (ADL) and were presented with and without history of cardiovascular disease (CVD). For each case, we asked GPs if they would deprescribe in their usual practice. We calculated proportions of GPs who reported they would deprescribe and performed a multilevel logistic regression to examine the association between history of CVD and level of dependency on GPs' deprescribing decisions. RESULTS: Of 3,175 invited GPs, 54% responded (N = 1,706). The mean age was 50 years and 60% of respondents were female. Despite differences across GP characteristics, such as age (with older GPs being more likely to take deprescribing decisions), and across countries, overall more than 80% of GPs reported they would deprescribe the dosage of at least one medication in oldest-old patients (> 80 years) with polypharmacy irrespective of history of CVD. The odds of deprescribing was higher in patients with a higher level of dependency in ADL (OR =1.5, 95%CI 1.25 to 1.80) and absence of CVD (OR =3.04, 95%CI 2.58 to 3.57). INTERPRETATION: The majority of GPs in this study were willing to deprescribe one or more medications in oldest-old multimorbid patients with polypharmacy. Willingness was higher in patients with increased dependency in ADL and lower in patients with CVD

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

International audienceBackground: Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics.Methods: We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties.Results: The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations.Discussion: This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

International audienceClinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

International audienceBackground: Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics.Methods: We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties.Results: The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations.Discussion: This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs

Mieux comprendre les comptes rendus d’hospitalisation pour mieux les coder. Un exemple en cardiologie

International audienc

Conception et évaluation d’un logiciel pour simplifier et améliorer le codage PMSI par les cliniciens : application aux séjours de prise en charge des patients diabétiques

International audienc

L’usage d’e-cigarette chez les usagers de cannabis et les polyconsommateurs : étude de cohorte

Introduction - There is no evidence in the literature relating to the evolution of e-cigarette use among cannabis users and multi-users (of alcohol, tobacco or cannabis). Objective - To describe the evolution over 12 months of e-cigarette use in cannabis users and multi-users. Methods - A prospective observational cohort study in general practice, between 2015 and 2016. Results - A total of 4.8% of monitored cannabis users remained or became current users of e-cigarettes by the end of the monitoring period versus 4.5% among non-users of cannabis, with no statistically significant difference. A total of 5.1% of monitored multi-users remained or became current users of e-cigarettes by the end of the monitoring period versus 2.4% among the non-multi-users, with no statistically significant difference. Cannabis users and multi-users reported more e-cigarette experimentation through curiosity and following someone's suggestion, compared to non-cannabis users or non multi-users. No statistically significant association was found between cannabis or multi-drug use and staying or becoming a current e-cigarette user over 12 months. Conclusion - Cannabis users and multi-users would tend to experiment with e-cigarettes more than other patients but this use would not be sustained

Level of accuracy of diagnoses recorded in discharge summaries: A cohort study in three respiratory wards

Rationale: One of the key functions of the discharge summary is to convey accurate diagnostic description of patients. Inaccurate or missing diagnoses may result in a false clinical picture, inappropriate management, poor quality of care, and a higher risk of re‐admission. While several studies have investigated the presence or absence of diagnoses within discharge summaries, there are very few published studies assessing the accuracy of these diagnoses. The aim of this study was to measure the accuracy of diagnoses recorded in sample summaries, and to determine if it was correlated with the type of diagnoses (eg, “respiratory” diagnoses), the number of diagnoses, or the length of patient stay. Methods: A prospective cohort study was conducted in three respiratory wards in a large UK NHS Teaching Hospital. We determined the reference list of diagnoses (the closest to the true state of the patient based on consultant knowledge, patient records, and laboratory investigations) for comparison with the diagnoses recorded in a discharge summary. To enable objective comparison, all patient diagnoses were encoded using a standardized terminology (ICD‐10). Inaccuracy of the primary diagnosis alone and all diagnoses in discharge summaries was measured and then correlated with type of diseases, number of diagnoses, and length of patient stay. Results: A total of 107 of 110 consecutive discharge summaries were analysed. The mean inaccuracy rate per discharge summary was 55% [95% CI 52 to 58%]. Primary diagnoses were wrong, inaccurate, missing, or mis‐recorded as a secondary diagnosis in half the summaries. The inaccuracy rate was correlated with the type of disease but not with number of diagnoses nor length of patient stay. Conclusion: Our study showed that diagnoses were not accurately recorded in discharge summaries, highlighting the need to measure and improve discharge summary quality