Julie Hias1, Lorenz Van der Linden2,3, Isabel Spriet2,3, Peter Vanbrabant4, Ludo Willems2,3, Jos Tournoy5,6, Sabrina De Winter2,3. 1. Pharmacy Department, University Hospitals Leuven, Leuven, Belgium. julie.1.hias@uzleuven.be. 2. Pharmacy Department, University Hospitals Leuven, Leuven, Belgium. 3. Department of Pharmaceutical and Pharmacological Sciences, Clinical Pharmacology and Pharmacotherapy, University of Leuven, Leuven, Belgium. 4. Department of General Internal Medicine, University of Leuven, University Hospitals Leuven, Leuven, Belgium. 5. Department of Geriatric Medicine, University Hospitals Leuven, Leuven, Belgium. 6. Department of Clinical and Experimental Medicine, University of Leuven, Leuven, Belgium.
Abstract
PURPOSE: Discrepancies in preadmission medication (PAM) are common and potentially harmful. Medication reconciliation is able to reduce the discrepancy rate, yet implementation is challenging. In order for reconciliation efforts to be more cost-effective, patients at high risk for reconciliation errors should be identified. The purpose of this systematic review is to identify predictors for unintentional discrepancies in PAM. METHODS: Medline and Embase were searched systematically until June 2017. Only studies concerning adult subjects were retained. Quantitative studies were included if predictors for unintentional discrepancies in the PAM had been determined on hospital admission. Variables were divided into patient-, medication-, and setting-related predictors based on a thematic analysis. Studies on identification of predictors for discrepancies and potentially harmful discrepancies were handled separately. RESULTS: Thirty-five studies were eligible, of which 5 studies focused on potentially harmful discrepancies. The following 16 significant variables were identified using multivariable prediction models: number of preadmission drugs, patient's age, availability of a drug list, patients' understanding of medication, usage of different outpatient pharmacies, number of high-risk drugs, discipline for which the patient is admitted, admitting physician's experience, number and type of consulted sources, patient's gender, type of care before admission, number of outpatient visits during the past year, class of medication, number of reimbursements, use of an electronic prescription system, and type of admission (elective vs emergency). The number of preadmission drugs was identified as a predictor in 20 studies. Potentially harmful discrepancies were ascertained in 5 studies with age found to have a predictive value in all 5 studies. CONCLUSION: Multiple suitable predictors for PAM-related discrepancies were identified of which higher age and polypharmacy were reported most frequently.
PURPOSE: Discrepancies in preadmission medication (PAM) are common and potentially harmful. Medication reconciliation is able to reduce the discrepancy rate, yet implementation is challenging. In order for reconciliation efforts to be more cost-effective, patients at high risk for reconciliation errors should be identified. The purpose of this systematic review is to identify predictors for unintentional discrepancies in PAM. METHODS: Medline and Embase were searched systematically until June 2017. Only studies concerning adult subjects were retained. Quantitative studies were included if predictors for unintentional discrepancies in the PAM had been determined on hospital admission. Variables were divided into patient-, medication-, and setting-related predictors based on a thematic analysis. Studies on identification of predictors for discrepancies and potentially harmful discrepancies were handled separately. RESULTS: Thirty-five studies were eligible, of which 5 studies focused on potentially harmful discrepancies. The following 16 significant variables were identified using multivariable prediction models: number of preadmission drugs, patient's age, availability of a drug list, patients' understanding of medication, usage of different outpatient pharmacies, number of high-risk drugs, discipline for which the patient is admitted, admitting physician's experience, number and type of consulted sources, patient's gender, type of care before admission, number of outpatient visits during the past year, class of medication, number of reimbursements, use of an electronic prescription system, and type of admission (elective vs emergency). The number of preadmission drugs was identified as a predictor in 20 studies. Potentially harmful discrepancies were ascertained in 5 studies with age found to have a predictive value in all 5 studies. CONCLUSION: Multiple suitable predictors for PAM-related discrepancies were identified of which higher age and polypharmacy were reported most frequently.
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