BACKGROUND: Computerized decision support reduces medication errors in inpatients, but limited evidence supports its effectiveness in reducing the coprescribing of interacting medications, especially in the outpatient setting. The usefulness of academic detailing to enhance the effectiveness of medication interaction alerts also is uncertain. METHODS: This study used an interrupted time series design. In a health maintenance organization with an electronic medical record, we evaluated the effectiveness of electronic medical record alerts and group academic detailing to reduce the coprescribing of warfarin and interacting medications. Participants were 239 primary care providers at 15 primary care clinics and 9910 patients takingwarfarin. All 15 clinics received electronic medical record alerts for the coprescription of warfarin and 5 interacting medications: acetaminophen, nonsteroidal anti-inflammatory medications, fluconazole, metronidazole, and sulfamethoxazole. Seven clinics were randomly assigned to receive group academic detailing. The primary outcome, the interacting prescription rate (ie, the number of coprescriptions of warfarin-interacting medications per 10 000 warfarin users per month), was analyzed with segmented regression models, controlling for preintervention trends. RESULTS: At baseline, nearly a third of patients had an interacting prescription. Coinciding with the alerts, there was an immediate and continued reduction in the warfarin-interacting medication prescription rate (from 3294.0 to 2804.2), resulting in a 14.9% relative reduction (95% confidence interval, -19.5 to -10.2) at 12 months. Group academic detailing did not enhance alert effectiveness. CONCLUSIONS: This study, using a strong and quasi-experimental design in ambulatory care, found that medication interaction alerts modestly reduced the frequency of coprescribing of interacting medications. Additional efforts will be required to further reduce rates of inappropriate prescribing of warfarin with interacting drugs.
RCT Entities:
BACKGROUND: Computerized decision support reduces medication errors in inpatients, but limited evidence supports its effectiveness in reducing the coprescribing of interacting medications, especially in the outpatient setting. The usefulness of academic detailing to enhance the effectiveness of medication interaction alerts also is uncertain. METHODS: This study used an interrupted time series design. In a health maintenance organization with an electronic medical record, we evaluated the effectiveness of electronic medical record alerts and group academic detailing to reduce the coprescribing of warfarin and interacting medications. Participants were 239 primary care providers at 15 primary care clinics and 9910 patients taking warfarin. All 15 clinics received electronic medical record alerts for the coprescription of warfarin and 5 interacting medications: acetaminophen, nonsteroidal anti-inflammatory medications, fluconazole, metronidazole, and sulfamethoxazole. Seven clinics were randomly assigned to receive group academic detailing. The primary outcome, the interacting prescription rate (ie, the number of coprescriptions of warfarin-interacting medications per 10 000 warfarin users per month), was analyzed with segmented regression models, controlling for preintervention trends. RESULTS: At baseline, nearly a third of patients had an interacting prescription. Coinciding with the alerts, there was an immediate and continued reduction in the warfarin-interacting medication prescription rate (from 3294.0 to 2804.2), resulting in a 14.9% relative reduction (95% confidence interval, -19.5 to -10.2) at 12 months. Group academic detailing did not enhance alert effectiveness. CONCLUSIONS: This study, using a strong and quasi-experimental design in ambulatory care, found that medication interaction alerts modestly reduced the frequency of coprescribing of interacting medications. Additional efforts will be required to further reduce rates of inappropriate prescribing of warfarin with interacting drugs.
Authors: Erika L Abramson; David W Bates; Chelsea Jenter; Lynn A Volk; Yolanda Barrón; Jill Quaresimo; Andrew C Seger; Elisabeth Burdick; Steven Simon; Rainu Kaushal Journal: J Am Med Inform Assoc Date: 2011-12-01 Impact factor: 4.497
Authors: Brian L Strom; Rita Schinnar; Warren Bilker; Sean Hennessy; Charles E Leonard; Eric Pifer Journal: J Am Med Inform Assoc Date: 2010 Jul-Aug Impact factor: 4.497
Authors: Robert J Fortuna; Fang Zhang; Dennis Ross-Degnan; Francis X Campion; Jonathan A Finkelstein; Jamie B Kotch; Adrianne C Feldstein; David H Smith; Steven R Simon Journal: J Gen Intern Med Date: 2009-05-28 Impact factor: 5.128
Authors: Erika L Abramson; Sameer Malhotra; Karen Fischer; Alison Edwards; Elizabeth R Pfoh; S Nena Osorio; Adam Cheriff; Rainu Kaushal Journal: J Gen Intern Med Date: 2011-04-16 Impact factor: 5.128
Authors: Sallie-Anne Pearson; Annette Moxey; Jane Robertson; Isla Hains; Margaret Williamson; James Reeve; David Newby Journal: BMC Health Serv Res Date: 2009-08-28 Impact factor: 2.655