OBJECTIVE: To evaluate the potential effect of computer support on general practitioners' prescribing, and to compare the effectiveness of three different support levels. DESIGN: Crossover experiment with balanced block design. SUBJECTS: Random sample of 50 general practitioners (42 agreed to participate) from 165 in a geographically defined area of Oxfordshire. INTERVENTIONS: Doctors prescribed for 36 simulated cases constructed from real consultations. Levels of computer support were control (alphabetical list of drugs), limited support (list of preferred drugs), and full support (the same list with explanations available for suggestions). MAIN OUTCOME MEASURES: Percentage of cases where doctors ignored a cheaper, equally effective drug; prescribing score (a measure of how closely prescriptions matched expert recommendations); interview to elicit doctors' views of support system. RESULTS: Computer support significantly improved the quality of prescribing. Doctors ignored a cheaper, equally effective drug in a median 50% (range 25%-75%) of control cases, compared with 36% (8%-67%) with limited support and 35% (0-67%) with full support (P < 0.001). The median prescribing score rose from 6.0 units (4.2-7.0) with control support to 6.8 (5.8 to 7.7) and 6.7 (5.6 to 7.8) with limited and full support (P < 0.001). Of 41 doctors, 36 (88%) found the system easy to use and 24 (59%) said they would be likely to use it in practice. CONCLUSIONS: Computer support improved compliance with prescribing guidelines, reducing the occasions when doctors ignored a cheaper, equally effective drug. The system was easy to operate, and most participating doctors would be likely to use it in practice.
RCT Entities:
OBJECTIVE: To evaluate the potential effect of computer support on general practitioners' prescribing, and to compare the effectiveness of three different support levels. DESIGN: Crossover experiment with balanced block design. SUBJECTS: Random sample of 50 general practitioners (42 agreed to participate) from 165 in a geographically defined area of Oxfordshire. INTERVENTIONS: Doctors prescribed for 36 simulated cases constructed from real consultations. Levels of computer support were control (alphabetical list of drugs), limited support (list of preferred drugs), and full support (the same list with explanations available for suggestions). MAIN OUTCOME MEASURES: Percentage of cases where doctors ignored a cheaper, equally effective drug; prescribing score (a measure of how closely prescriptions matched expert recommendations); interview to elicit doctors' views of support system. RESULTS: Computer support significantly improved the quality of prescribing. Doctors ignored a cheaper, equally effective drug in a median 50% (range 25%-75%) of control cases, compared with 36% (8%-67%) with limited support and 35% (0-67%) with full support (P < 0.001). The median prescribing score rose from 6.0 units (4.2-7.0) with control support to 6.8 (5.8 to 7.7) and 6.7 (5.6 to 7.8) with limited and full support (P < 0.001). Of 41 doctors, 36 (88%) found the system easy to use and 24 (59%) said they would be likely to use it in practice. CONCLUSIONS: Computer support improved compliance with prescribing guidelines, reducing the occasions when doctors ignored a cheaper, equally effective drug. The system was easy to operate, and most participating doctors would be likely to use it in practice.
Authors: Guy Haller; Paul S Myles; Johannes Stoelwinder; Mark Langley; Hugh Anderson; John McNeil Journal: J Am Med Inform Assoc Date: 2007-01-09 Impact factor: 4.497
Authors: Annette Moxey; Jane Robertson; David Newby; Isla Hains; Margaret Williamson; Sallie-Anne Pearson Journal: J Am Med Inform Assoc Date: 2010 Jan-Feb Impact factor: 4.497