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

ContextComputerized 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.ObjectiveTo 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.DesignCluster randomized controlled trial of 81 family physicians and 5628 of their patients aged 65 and older who were prescribed psychotropic medication.InterventionIntervention 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.Main outcome measuresInjury 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.ResultsMean 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).ConclusionPatient-specific risk estimates provide an effective method of reducing the risk of injury for high-risk older people.Trial registration numberclinicaltrials.gov Identifier: NCT00818285.

Recommendations for selecting drug–drug interactions for clinical decision support

“…Research shows that providing clinicians with alerts containing patient-specific risk factors can reduce the risk of injury. 47 Known modifying factors (such as patients’ genetic information, ethnicity, concomitant diseases, etc.) should be included in DDI alerts, and when factors are not known, the lack of information should also be stated.…”

Effects of drug pharmacokinetic/pharmacodynamic properties, characteristics of medication use, and relevant pharmacological interventions on fall risk in elderly patients

“…The intervention reduced the risk of injury by 1.7 injuries per 1,000 patients (95% CI 0.2/1,000–3.2/1,000, P =0.02). The effect of the intervention was greater for patients with higher baseline risks of injury ( P <0.03) 72. A study by Tzeng et al determined the correlations between hospital-acquired injurious fall rates in US acute care hospitals and these institutions’ implementation levels of computerized systems.…”

Effects of drug pharmacokinetic/pharmacodynamic properties, characteristics of medication use, and relevant pharmacological interventions on fall risk in elderly patients

“…The effect of the intervention was greater for patients with higher baseline risks of injury (P,0.03). 72 A study by Tzeng et al determined the correlations between hospital-acquired injurious fall rates in US acute care hospitals and these institutions' implementation levels of computerized systems. The results showed that computerized decision-support systems for DDI alerts, drug allergy alerts, and drug-laboratory interaction alerts were effective to inform practice for better interventions to reduce fall risk.…”