Medication discrepancies and potentially inadequate prescriptions in elderly adults with polypharmacy in ambulatory care.

Abstract

The objective of this study is to describe the frequency and type of medication discrepancies (MD) through medication reconciliation and to describe the frequency of potentially inadequate prescription (PIP) medications using screening tool of older persons' prescriptions criteria. Cross-sectional comparison of electronic medical record (EMR) medication lists and patient's self-report of their comprehensive medication histories obtained through telephone interviews. Elderly individuals (>65 years old) with more than ten medications recorded in their EMR, who had not been hospitalized in the past year and were not under domiciliary care, affiliated to a private community hospital. The primary outcomes were the proportion of patients with MD and PIP. Secondary outcomes were the proportion of types of discrepancies and PIP. We analyzed possible associations between these variables and other demographic and clinical variables. Out of 214 randomly selected individuals, 150 accepted to participate (70%). The mean number of medications referred to be consumed by patients was 9.1 (95% confidence interval [CI] =8.6-9.6), and the mean number of prescribed medications in their EMR was 13.9 (95% CI = 13.3-14.5). Ninety-nine percent had at least one discrepancy (total 1252 discrepancies); 46% consumed at least one prescription not documented in their EMR and 93% did not consume at least one of the prescriptions documented in their EMR. In 77% of the patients, a PIP was detected (total 186), 87% of them were at least within one of the following categories: Prolonged used of benzodiazepines or proton pump inhibitors and the use of aspirin for the primary prevention of cardiovascular disease. There was a high prevalence of MD and PIP within the community of elderly adults affiliated to a Private University Hospital. Future interventions should be aimed at reducing the number of PIP to prevent adverse drug events and improve EMR accuracy by lowering medications discrepancies.