title: A Pharmacist-Physician Intervention Model Using a Computerized Alert System to Reduce High-Risk Medication Use in Elderly Inpatients.
abstract: BACKGROUND
  Prescription is a complex challenge facing clinicians caring for elderly inpatients. Potentially inappropriate medication (PIM) use frequently leads to adverse drug events and geriatric syndromes. Strategies to reduce PIM use are thus urgently needed.
  
  
  OBJECTIVE
  The objectives of this study were to assess (1) the applicability of a pharmacist-physician intervention model to reduce the use of high-risk medications; and (2) the clinical relevance of the alerts generated by a computerized alert system (CAS).
  
  
  METHODS
  The study was conducted in patients aged 65 years or older admitted to a teaching hospital between April and June 2014. In the intervention model, the pharmacist determined the clinical relevance of the Beers criteria-based CAS alerts, analyzed the patient's pharmacotherapy, and developed a geriatric pharmacotherapeutic plan to be discussed with the treating physician. The main outcome was the change rate, defined as the number of patient-days with a change in at least one medication out of the number of patient-days with a pharmacist intervention.
  
  
  RESULTS
  The CAS identified at least one alert in 200 patient-days, i.e., 4.3% of screened patient-days. In 74.5% of those patient-days, at least one alert was judged to be clinically relevant. The change rate was 77.7%. The most frequent changes were drug discontinuation (42.4%) and dose reduction (29.1%). The inpatient geriatric consultation team was involved in only 24% of the hospitalizations with at least one change in medication.
  
  
  CONCLUSIONS
  The intervention model reduced high-risk medication use in older inpatients. Most of the vulnerable inpatients identified by CAS alerts would not have otherwise had a geriatric medication review.
authors.affiliation: Faculty of Pharmacy, Université de Montréal, Montréal, QC, Canada.
authors.forename: Karolann
authors.initials: K
authors.lastname: Arvisais
authors.forename: Sabrina
authors.initials: S
authors.lastname: Bergeron-Wolff
authors.forename: Christine
authors.initials: C
authors.lastname: Bouffard
authors.forename: Anne-Sophie
authors.initials: AS
authors.lastname: Michaud
authors.forename: Josée
authors.initials: J
authors.lastname: Bergeron
authors.forename: Louise
authors.initials: L
authors.lastname: Mallet
authors.forename: Serge
authors.initials: S
authors.lastname: Brazeau
authors.forename: Thomas
authors.initials: T
authors.lastname: Joly-Mischlich
authors.forename: Nora
authors.initials: N
authors.lastname: Bernier-Filion
authors.forename: Luc
authors.initials: L
authors.lastname: Lanthier
authors.forename: Geneviève
authors.initials: G
authors.lastname: Ricard
authors.forename: Marie-Claude
authors.initials: MC
authors.lastname: Rodrigue
authors.forename: Benoit
authors.initials: B
authors.lastname: Cossette
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D064420:Drug-Related Side Effects and Adverse Reactions / Q000517:prevention & control*; D005260:Female; D006784:Hospitals, Teaching; D006801:Humans; D007297:Inpatients; D008297:Male; D010595:Pharmacists / Q000458:organization & administration*; D010820:Physicians / Q000458:organization & administration*; D010865:Pilot Projects; D012017:Referral and Consultation; D012306:Risk