Predicting the use of electronic prescribing among early adopters in primary care.

OBJECTIVE To identify the factors that can predict physicians' use of electronic prescribing. DESIGN All primary care physicians who practised in a single geographic region in Quebec were invited to use a free, advanced, research-based electronic prescribing and drug management system. This natural experiment was studied with an expansion of the Technology Acceptance Model (TAM), which was used to explain early adopters' use of this electronic prescribing technology. SETTING Quebec city region. PARTICIPANTS A total of 61 primary care physicians who practised in a single geographic region where there was no electronic prescribing. MAIN OUTCOME MEASURES Actual use of electronic prescribing; physicians' perceptions of and intentions to use electronic prescribing; physician and practice characteristics. RESULTS During the 9-month study period, 61 primary care physicians located in 26 practice sites used electronic prescribing to write 15 160 electronic prescriptions for 18 604 patients. Physician electronic prescribing rates varied considerably, from a low of 0 to a high of 75 per 100 patient visits, with a mean utilization rate of 30 per 100 patient visits. Overall, 34% of the variance in the use of electronic prescribing was explained by the expanded TAM. Computer experience (P=.001), physicians' information-acquisition style (P=.01), and mean medication use in the practice (P=.02) were significant predictors. Other TAM factors that generally predict new technology adoption (eg, intention to use, perceived ease of use, and perceived usefulness) were not predictive in this study. CONCLUSION The adoption of electronic prescribing was a highly challenging task, even among early adopters. The insight that this pilot study provides into the determinants of the adoption of electronic prescribing suggests that novel physician-related factors (eg, information-acquisition style) and practice-related variables (eg, prevalence of medication use) influence the adoption of electronic prescribing.