A Quantitative and Qualitative Analysis of Electronic Prescribing Incidents Reported by Community Pharmacists

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Applied Clinical Informatics


Background Electronic prescribing (e-prescribing) technology was introduced as an alternative to handwritten prescriptions allowing health care professionals to send prescriptions directly to pharmacies. While the technology has many advantages, such as improving pharmacy workflow and reducing medication errors, some limitations have been realized. Objective The objective of this study was to examine the frequency, type, and contributing factors of e-prescribing quality-related incidents reported to two national error-reporting databases in the United States. Methods This was a retrospective analysis of voluntarily reports of e-prescribing quality-related incidents. A quantitative and qualitative analysis was conducted of incidents reported between 2011 and 2015 to the Pharmacy Quality Commitment (PQC) and the Pharmacy Provider e-prescribing Experience Reporting Portal (PEER) databases. For the qualitative analysis, events were combined from the PQC and PEER portal and a 10% random sample of events were analyzed. Results A total of 589 events were reported to the PEER Portal. Of these, problems with patient directions were the most frequent incident type (n = 210) of which 10% (n = 21) reached the patient. Quantity selection (n = 158) and drug selection (n = 96) were the next most frequently reported events, 20% of which reached the patient. The PQC system received 550 reports. The most frequent event type reported to this system was incorrect directions (23.3%, n = 128) followed by incorrect prescriber (17%), incorrect drug (15%), and incorrect strength (12%). The most common theme in the qualitative analysis was a perceived increased likelihood of patient receiving incorrect drug therapy due to e-prescribing. Another theme identified included confusion and frustration of pharmacy personnel as result of e-prescription quality-related events. Conclusion The use of qualitative and quantitative incident data revealed that patient directions and quantity selection were the most common quality issues with e-prescribing. In turn, this may increase the likelihood of patients receiving incorrect drug therapy.

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