OBJECTIVE: To assess whether a multifaceted intervention can reduce the number of prescriptions for antimicrobials for suspected urinary tract infections in residents of nursing homes. DESIGN: Cluster randomised controlled trial. SETTING: 24 nursing homes in Ontario, Canada, and Idaho, United States. PARTICIPANTS: 12 nursing homes allocated to amultifaceted intervention and 12 allocated to usual care. Outcomes were measured in 4217 residents. INTERVENTIONS: Diagnostic and treatment algorithm for urinary tract infections implemented at the nursing home level using a multifaceted approach--small group interactive sessions for nurses, videotapes, written material, outreach visits, and one on one interviews with physicians. MAIN OUTCOME MEASURES: Number of antimicrobials prescribed for suspected urinary tract infections, total use of antimicrobials, admissions to hospital, and deaths. RESULTS: Fewer courses of antimicrobials for suspected urinary tract infections per 1000 resident days were prescribed in the intervention nursing homes than in the usual care homes (1.17 v 1.59 courses; weighted mean difference -0.49, 95% confidence intervals -0.93 to -0.06). Antimicrobials for suspected urinary tract infection represented 28.4% of all courses of drugs prescribed in the intervention nursing homes compared with 38.6% prescribed in the usual care homes (weighted mean difference -9.6%, -16.9% to -2.4%). The difference in total antimicrobial use per 1000 resident days between intervention and usual care groups was not significantly different (3.52 v 3.93; weighted mean difference -0.37, -1.17 to 0.44). No significant difference was found in admissions to hospital or mortality between the study arms. CONCLUSION: A multifaceted intervention using algorithms can reduce the number of antimicrobial prescriptions for suspected urinary tract infections in residents of nursing homes.
RCT Entities:
OBJECTIVE: To assess whether a multifaceted intervention can reduce the number of prescriptions for antimicrobials for suspected urinary tract infections in residents of nursing homes. DESIGN: Cluster randomised controlled trial. SETTING: 24 nursing homes in Ontario, Canada, and Idaho, United States. PARTICIPANTS: 12 nursing homes allocated to a multifaceted intervention and 12 allocated to usual care. Outcomes were measured in 4217 residents. INTERVENTIONS: Diagnostic and treatment algorithm for urinary tract infections implemented at the nursing home level using a multifaceted approach--small group interactive sessions for nurses, videotapes, written material, outreach visits, and one on one interviews with physicians. MAIN OUTCOME MEASURES: Number of antimicrobials prescribed for suspected urinary tract infections, total use of antimicrobials, admissions to hospital, and deaths. RESULTS: Fewer courses of antimicrobials for suspected urinary tract infections per 1000 resident days were prescribed in the intervention nursing homes than in the usual care homes (1.17 v 1.59 courses; weighted mean difference -0.49, 95% confidence intervals -0.93 to -0.06). Antimicrobials for suspected urinary tract infection represented 28.4% of all courses of drugs prescribed in the intervention nursing homes compared with 38.6% prescribed in the usual care homes (weighted mean difference -9.6%, -16.9% to -2.4%). The difference in total antimicrobial use per 1000 resident days between intervention and usual care groups was not significantly different (3.52 v 3.93; weighted mean difference -0.37, -1.17 to 0.44). No significant difference was found in admissions to hospital or mortality between the study arms. CONCLUSION: A multifaceted intervention using algorithms can reduce the number of antimicrobial prescriptions for suspected urinary tract infections in residents of nursing homes.
Authors: Mark B Loeb; Sharon Craven; Allison J McGeer; Andrew E Simor; Suzanne F Bradley; Donald E Low; Maxine Armstrong-Evans; Lorraine A Moss; Stephen D Walter Journal: Am J Epidemiol Date: 2003-01-01 Impact factor: 4.897
Authors: Nick Daneman; Michael A Campitelli; Vasily Giannakeas; Andrew M Morris; Chaim M Bell; Colleen J Maxwell; Lianne Jeffs; Peter C Austin; Susan E Bronskill Journal: CMAJ Date: 2017-06-26 Impact factor: 8.262