title: The effectiveness of a new generation of computerized drug alerts in reducing the risk of injury from drug side effects: a cluster randomized trial.
abstract: BACKGROUND
  Computerized drug alerts for psychotropic drugs are expected to reduce fall-related injuries in older adults. However, physicians over-ride most alerts because they believe the benefit of the drugs exceeds the risk.
  
  
  OBJECTIVE
  To determine whether computerized prescribing decision support with patient-specific risk estimates would increase physician response to psychotropic drug alerts and reduce injury risk in older people.
  
  
  METHODS
  Cluster randomized controlled trial of 81 family physicians and 5628 of their patients aged 65 and older who were prescribed psychotropic medication.
  
  
  METHODS
  Intervention physicians received information about patient-specific risk of injury computed at the time of each visit using statistical models of non-modifiable risk factors and psychotropic drug doses. Risk thermometers presented changes in absolute and relative risk with each change in drug treatment. Control physicians received commercial drug alerts.
  
  
  METHODS
  Injury risk at the end of follow-up based on psychotropic drug doses and non-modifiable risk factors. Electronic health records and provincial insurance administrative data were used to measure outcomes.
  
  
  RESULTS
  Mean patient age was 75.2 years. Baseline risk of injury was 3.94 per 100 patients per year. Intermediate-acting benzodiazepines (56.2%) were the most common psychotropic drug. Intervention physicians reviewed therapy in 83.3% of visits and modified therapy in 24.6%. The intervention reduced the risk of injury by 1.7 injuries per 1000 patients (95% CI 0.2/1000 to 3.2/1000; p=0.02). The effect of the intervention was greater for patients with higher baseline risks of injury (p<0.03).
  
  
  CONCLUSIONS
  Patient-specific risk estimates provide an effective method of reducing the risk of injury for high-risk older people.
  
  
  BACKGROUND
  clinicaltrials.gov Identifier: NCT00818285.
authors.affiliation: Department of Epidemiology & Biostatistics, McGill University, Montreal, Quebec, Canada. robyn.tamblyn@mcgill.ca
authors.forename: Robyn
authors.initials: R
authors.lastname: Tamblyn
authors.forename: Tewodros
authors.initials: T
authors.lastname: Eguale
authors.forename: David L
authors.initials: DL
authors.lastname: Buckeridge
authors.forename: Allen
authors.initials: A
authors.lastname: Huang
authors.forename: James
authors.initials: J
authors.lastname: Hanley
authors.forename: Kristen
authors.initials: K
authors.lastname: Reidel
authors.forename: Sherry
authors.initials: S
authors.lastname: Shi
authors.forename: Nancy
authors.initials: N
authors.lastname: Winslade
mesh_terms: D000058:Accidental Falls / Q000517:prevention & control*; D000368:Aged; D003196:Computer Graphics; D020000:Decision Support Systems, Clinical; D004360:Drug Therapy, Computer-Assisted; D005260:Female; D006801:Humans; D008297:Male; D050316:Medical Order Entry Systems; D010818:Practice Patterns, Physicians'; D011619:Psychotropic Drugs / Q000009:adverse effects*; D011792:Quebec; D018570:Risk Assessment
chemical_list: D011619:Psychotropic Drugs