A pharmacist-physician intervention model using a computerized alert system to reduce high-risk medication use in primary care View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-03-21

AUTHORS

Benoit Cossette, Ryeyan Taseen, Jacynthe Roy-Petit, Marie-Pier Villemure, Martine Grondin, Geneviève Ricard, François Goyer, Caroline Blanchard, Thomas Joly-Mischlich, Jean-François Éthier

ABSTRACT

PURPOSE: Potentially inappropriate medications (PIMs) have been associated with a greater risk of adverse drug events and hospitalizations. To reduce PIMs use, a family health team (FHT) implemented a knowledge translation (KT) strategy that included a pharmacist-physician intervention model based on alerts from a computerized alert system (CAS). METHODS: Our pragmatic, single-site, pilot study was conducted in an FHT clinic in Quebec, Canada. We included community-dwelling older adults (≥ 65 years), with at least 1 alert for selected PIMs and a medical appointment during the study period. PIMs were selected from the Beers and STOPP criteria. The primary outcome was PIMs cessation, decreased dose, or replacement. The secondary outcome was the clinical relevance of the alerts as assessed by the pharmacists. RESULTS: During the 134 days of the study, the CAS screened 369 individuals leading to the identification of 65 (18%) patients with at least 1 new alert. For those 65 patients, the mean age was 77 years, men accounted for 29% of the group and 55% were prescribed 10 or more drugs. One or more clinically relevant alerts were generated for 27 of 65 included patients for an overall clinical relevance of the alerts of 42%. Of the 27 patients with at least 1 relevant alert, 17 (63%) had at least 1 medication change as suggested by the pharmacist. CONCLUSION: An interdisciplinary pharmacist-physician intervention model, based on alerts generated by a CAS, reduced the use of PIMs in community-dwelling older adults followed by an FHT. More... »

PAGES

1-7

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URI

http://scigraph.springernature.com/pub.10.1007/s00228-019-02660-x

DOI

http://dx.doi.org/10.1007/s00228-019-02660-x

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112918577

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30899989


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