BackgroundPreventive strategies to reduce clinically significant medication errors (MEs), such as medication review, are often limited by human resources. Identifying high-risk patients to allow for appropriate resource allocation is of the utmost importance. To this end, we developed a predictive model to identify high-risk patients and assessed its impact on clinical decision-making.MethodsFrom March 1st to April 31st 2014, we conducted a prospective cohort study on adult inpatients of a 1,644-bed University Hospital Centre. After a clinical evaluation of identified MEs, we fitted and internally validated a multivariate logistic model predicting their occurrence. Through 5,000 simulated randomized controlled trials, we compared two clinical decision pathways for intervention: one supported by our model and one based on the criterion of age.ResultsAmong 1,408 patients, 365 (25.9%) experienced at least one clinically significant ME. Eleven variables were identified using multivariable logistic regression and used to build a predictive model which demonstrated fair performance (c-statistic: 0.72). Major predictors were age and number of prescribed drugs. When compared with a decision to treat based on the criterion of age, our model enhanced the interception of potential adverse drug events by 17.5%, with a number needed to treat of 6 patients.ConclusionWe developed and tested a model predicting the occurrence of clinically significant MEs. Preliminary results suggest that its implementation into clinical practice could be used to focus interventions on high-risk patients. This must be confirmed on an independent set of patients and evaluated through a real clinical impact study.

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Background: Elderly patients with chronic kidney disease (CKD) frequently present comorbidities that put them at risk of polypharmacy and medication-related problems. This study aims to describe the overall medication profile of patients aged ≥75 years with advanced CKD from a multicenter French study and specifically the renally (RIMs) and potentially inappropriate-for-the-elderly medications (PIMs) that they take.Methods: This is a cross-sectional analysis of medication profiles of individuals aged ≥75 years with eGFR < 20 ml/min/1.73 m2 followed by a nephrologist, who collected their active prescriptions at the study inclusion visit. Medication profiles were first analyzed according to route of administration, therapeutic classification. Second, patients were classified according to their risk of potential medication-related problems, based on whether the prescription was a RIM or a PIM. RIMs and PIMs have been defined according to renal appropriateness guidelines and to Beer's criteria in the elderly. RIMs were subclassified by 4 types of category: (a) contraindication; (b) dose modification is recommended based on creatinine clearance (CrCl); (c) dose modification based on CrCl is not recommended but a maximum daily dose is mentioned, (d) no specific recommendations based on CrCl: "use with caution", "avoid in severe impairment", "careful monitoring of dose is required" "reduce the dose". Results:We collected 5196 individual medication prescriptions for 556 patients, for a median of 9 daily medications [7][8][9][10][11]. Antihypertensive agents, antithrombotics, and antianemics were the classes most frequently prescribed. Moreover, 77.0% of patients had at least 1 medication classified as a RIM. They accounted 31.3% of the drugs prescribed and 9.25% was contraindicated drugs. At least 1 PIM was taken by 57.6 and 45.5% of patients had at least one medication classified as RIM and PIM. The prescriptions most frequently requiring reassessment due to potential adverse effects were for proton pump inhibitors and allopurinol. The PIMs for which deprescription is especially important in this population are rilmenidine, long-term benzodiazepines, and anticholinergic drugs such as hydroxyzine.(Continued on next page) Conclusion: We showed potential drug-related problems in elderly patients with advanced CKD. Healthcare providers must reassess each medication prescribed for this population, particularly the specific medications identified here.Trial registration: NCT02910908.