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Development and validation of a score to assess risk of medication errors detected during medication reconciliation process at admission in internal medicine unit: SCOREM study

Yohan Audurier, C. Roubille, F. Manna, L. Zerkowski, Marie Faucanié, Valérie Macioce, Audrey Castet‐Nicolas, Anne Jalabert, Maxime Villiet, Pierre Fesler, Laura Lohan‐Descamps, Cyril Breuker

2020International Journal of Clinical Practice12 citationsDOI

Abstract

BACKGROUND: Medication errors (ME) can be reduced through preventive strategies such as medication reconciliation. Such strategies are often limited by human resources and need targeting high risk patients. AIMS: To develop a score to identify patients at risk of ME detected during medication reconciliation in a specific population from internal medicine unit. METHODS: Prospective observational study conducted in an internal medicine unit of a French University Hospital from 2012 to 2016. Adult hospitalised patients were eligible for inclusion. Medication reconciliation was conducted by a pharmacist and consisted in comparing medication history with admission prescription to identify MEs. Risk factors of MEs were analysed using multivariate stepwise logistic regression model. A risk score was constructed using the split-sample approach. The split was done at random (using a fixed seed) to define a development data set (N = 1256) and a validation sample (N = 628). A regression coefficient-base scoring system was used adopting the beta-Sullivan approach (Sullivan's scoring). RESULTS: Pharmacists detected 740 MEs in 368/1884 (19.5%) patients related to medication reconciliation. Female gender, number of treatments >7, admission from emergency department and during night or weekend were significantly associated with a higher risk of MEs. Risk score was constructed by attributing 1 or 2 points to these variables. Patients with a score ≥3 (OR [95% CI] 3.10 [1.15-8.37]) out of 5 (OR [95% CI] 8.11 [2.89-22.78]) were considered at high risk of MEs. CONCLUSIONS: Risk factors identified in our study may help prioritising patients admitted in internal medicine units who may benefit the most from medication reconciliation (ClinicalTrials.gov number NCT03422484).

Topics & Concepts

MedicineLogistic regressionMedical prescriptionObservational studyFramingham Risk ScorePharmacistEmergency departmentPopulationEmergency medicineInternal medicineRisk assessmentStepwise regressionRisk factorPharmacyFamily medicineComputer securityPsychiatryComputer sciencePharmacologyDiseaseEnvironmental healthPharmaceutical Practices and Patient OutcomesPatient Safety and Medication ErrorsElectronic Health Records Systems
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