D L O'Connell1, D Henry, R Tomlins. 1. Discipline of Clinical Pharmacology, Faculty of Medicine and Health Sciences, University of Newcastle, New South Wales, Australia. doconnel@mail.newcastle.edu.au
Abstract
OBJECTIVE: To evaluate the effect on general practitioners' prescribing of feedback on their levels of prescribing. DESIGN: Randomised controlled trial. SETTING:General practice in rural Australia. PARTICIPANTS: 2440 full time recognised general practitioners practising in non-urban areas. INTERVENTION: Two sets of graphical displays (6 months apart) of their prescribing rates for 2 years, relative to those of their peers, were posted to participants. Data were provided for five main drug groups and were accompanied by educational newsletters. The control group received no information on their prescribing. MAIN OUTCOME MEASURES: Prescribing rates in the intervention and control groups for the five main drug groups, total prescribing and potential substitute prescribing and ordering before and after the interventions. RESULTS: The intervention and control groups had similar baseline characteristics (age, sex, patient mix, practices). Median prescribing rates for the two groups were almost identical before and after the interventions. Any changes in prescribing observed in the intervention group were also seen in the control group. There was no evidence that feedback reduced the variability in prescribing nor did it differentially affect the very high or very low prescribers. CONCLUSIONS: The form of feedback evaluated here-mailed, unsolicited, centralised, government sponsored, and based on aggregate data-had no impact on the prescribing levels of general practitioners.
RCT Entities:
OBJECTIVE: To evaluate the effect on general practitioners' prescribing of feedback on their levels of prescribing. DESIGN: Randomised controlled trial. SETTING: General practice in rural Australia. PARTICIPANTS: 2440 full time recognised general practitioners practising in non-urban areas. INTERVENTION: Two sets of graphical displays (6 months apart) of their prescribing rates for 2 years, relative to those of their peers, were posted to participants. Data were provided for five main drug groups and were accompanied by educational newsletters. The control group received no information on their prescribing. MAIN OUTCOME MEASURES: Prescribing rates in the intervention and control groups for the five main drug groups, total prescribing and potential substitute prescribing and ordering before and after the interventions. RESULTS: The intervention and control groups had similar baseline characteristics (age, sex, patient mix, practices). Median prescribing rates for the two groups were almost identical before and after the interventions. Any changes in prescribing observed in the intervention group were also seen in the control group. There was no evidence that feedback reduced the variability in prescribing nor did it differentially affect the very high or very low prescribers. CONCLUSIONS: The form of feedback evaluated here-mailed, unsolicited, centralised, government sponsored, and based on aggregate data-had no impact on the prescribing levels of general practitioners.
Authors: Wim H J M Verstappen; Trudy van der Weijden; Willy I Dubois; Ivo Smeele; Jan Hermsen; Frans E S Tan; Richard P T M Grol Journal: Ann Fam Med Date: 2004 Nov-Dec Impact factor: 5.166
Authors: Nathan R Shively; Deanna J Buehrle; Marilyn M Wagener; Cornelius J Clancy; Brooke K Decker Journal: Antimicrob Agents Chemother Date: 2019-12-20 Impact factor: 5.191