Showing Your Work: Impact of annotating electronic prescriptions with decision support results

Department of Biomedical Informatics, Vanderbilt University, 2209 Garland Ave., Room 428, Nashville, TN 37232, USA.
Journal of Biomedical Informatics (Impact Factor: 2.48). 12/2009; 43(2):321-5. DOI: 10.1016/j.jbi.2009.11.008
Source: PubMed

ABSTRACT e-Prescribing systems with decision support do not routinely communicate an adequate amount of information regarding the prescribers' decision to pharmacists. To address this communication gap in the e-prescribing process, we implemented a system called Show Your Work (SYW) that appends alerts and override comments to e-prescriptions generated by an e-prescribing system. To assess the quantitative impact of this system, we conducted a randomized, double-blinded, controlled study to assess pharmacy callback rates and types, and to uncover any unintended consequences of the annotations. Each day, SYW output across the enterprise was turned "on" or "off" randomly for all e-prescriptions. A convenience sample of three pharmacies, blinded to SYW status, submitted callback logs each day. These logs were used to calculate the rate of and reason for callbacks. At the conclusion of the study, we surveyed the 50 most frequently used pharmacies in our area to assess the impact of SYW on satisfaction and communication. A total of 202 callbacks had occurred yielding a callback rate of 45 callbacks/1000 prescriptions for SYW "on" days and 40 callbacks/1000 prescriptions for "off" days (p=0.4). We received 38 surveys (76% response rate) with 33 respondents commenting about SYW. Most respondents agreed (69%) that SYW favorably impacted callbacks--especially with pediatric prescriptions (82%). Comments suggested that SYW increased callbacks where necessary and decreased them in other situations, but did not contribute to unnecessary callbacks. These findings support the continued and potentially expanded use of SYW by e-prescribing systems to enhance communication with pharmacists.

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