@article{10701, author = {Nidhi Shah and Andrew C. Seger and Diane L. Seger and Julie M. Fiskio and Gilad J. Kuperman and Barry Blumenfeld and Elaine G. Recklet and David W. Bates and Tejal K. Gandhi}, title = {Improving acceptance of computerized prescribing alerts in ambulatory care.}, abstract = {

Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. Our objective was to improve clinician acceptance of drug alerts by designing a selective set of drug alerts for the ambulatory care setting and minimizing workflow disruptions by designating only critical to high-severity alerts to be interruptive to clinician workflow. The alerts were presented to clinicians using computerized prescribing within an electronic medical record in 31 Boston-area practices. There were 18,115 drug alerts generated during our six-month study period. Of these, 12,933 (71%) were noninterruptive and 5,182 (29%) interruptive. Of the 5,182 interruptive alerts, 67% were accepted. Reasons for overrides varied for each drug alert category and provided potentially useful information for future alert improvement. These data suggest that it is possible to design computerized prescribing decision support with high rates of alert recommendation acceptance by clinicians.

}, year = {2006}, journal = {J Am Med Inform Assoc}, volume = {13}, pages = {5-11}, month = {12/2006}, issn = {1067-5027}, language = {eng}, }