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AIM: Inappropriate anticoagulant use increases the risk of bleeding and thrombotic events. We implemented clinical decision rules to promote judicious medication use, as part of the 'Check of Medication Appropriateness' (CMA). The CMA concerns a pharmacist-led review service, targeting potentially inappropriate prescriptions (PIPs). In this analysis, we aimed to evaluate the impact of the CMA on anticoagulant prescribing. METHODS: The number of anticoagulant-related PIPs was evaluated before and after implementation of the intervention in a quasi-experimental interrupted time series analysis. The pre-implementation cohort received usual care. The anticoagulant-focused CMA, comprising 13 clinical rules pertaining to anticoagulation therapies, was implemented in the post-implementation cohort. Segmented regression analysis was used to assess the impact of the intervention on the number of residual PIPs. A residual PIP was defined as a PIP which persisted up to 48h after the CMA intervention. Total number of recommendations and acceptance rate were documented for the 2-year post-implementation period. RESULTS: Pre-implementation, we observed 501 PIPs in 466 inpatients on 36 days, with a median proportion of 78.5% (range: 46.2%-100%) residual PIPs per day. Post-implementation, 538 PIPs were detected in 485 patients over the same number of days. The CMA intervention reduced the median proportion to 18.2% (range: 0-100%) per day. The effect coincided with an immediate relative reduction of 70% (95%CI 0.19-0.46) in anticoagulant-related residual PIPs. Post-implementation, 2778 recommendations were provided and 75.1% were accepted. CONCLUSION: Our CMA approach significantly reduced anticoagulant-related PIPs. Implementing a pharmacist-led intervention, based on clinical rules, may support safer prescribing of anticoagulants. ispartof: British Journal Of Clinical Pharmacology vol:88 issue:6 pages:2959-2968 ispartof: location:England status: accepted

Aims QTc prolongation is a complex problem linked with multiple risk factors. The RISQ-PATH score was previously developed to identify high-risk patients for QTc prolongation. The aim of this study was to optimize and validate this risk score in a large patient cohort, and to propose an algorithm to generate smart QT signals in the electronic medical record. Methods A retrospective study was performed in the Nexus hospital network (n = 17) in Belgium. All electrocardiograms performed in 2015 in both ambulatory and hospitalized patients were collected together with risk factors for QTc prolongation (training database). Multiple logistic regression was performed to obtain the optimal prediction (RISQ-PATH) model. The model was tested in a validation database (electrocardiograms between January and April 2016). Results In total, 60 208 patients (52.8% males, mean age 63 ± 18 years) were included; 3543 patients (5.9%) had a QTc ≥ 450(♂)/470(♀) ms and 453 (0.8%) a QTc ≥ 500 ms. The optimized RISQ-PATH model has an area under the ROC-curve of 0.772 [95% CI 0.763-0.780] to predict QTc ≥ 450(♂)/470(♀)ms. A predicted probability of ≥0.035 was set as cutoff for a high risk of QTc prolongation. This cutoff resulted in a sensitivity of 87.4% [95% CI 86.2-88.5] and a specificity of 46.2% [95% CI 45.8-46.6]. These results could be confirmed for QTc ≥ 500 ms and in the validation database (n = 28 400). Conclusions The RISQ-PATH model, with a cutoff probability of 0.035, predicted a prolonged QTc interval ≥ 450/470 ms or ≥500 ms with a sensitivity of ±87% and a specificity of ±45%. This RISQ-PATH model can be used in clinical decision support systems to create smart QT alerts.