Aim To evaluate the impact of an emergency department (ED) pharmacist on prescribing errors 24 hours post‐admission. Method A prospective controlled sequential study was conducted in the ED of a metropolitan teaching hospital. In the control period, ED patients admitted were followed‐up by ward pharmacists (standard practice). In the active period, they were seen first by the ED pharmacist. Targets of 50 patients were recruited into each study period. All medication charts were reviewed by a senior clinical pharmacist (reviewing pharmacist) at 24 hours post‐admission. Errors were risk‐assessed by a blinded independent physician. The number and type of errors were compared. Results The profile, type and complexity of patients and number of medications ordered per patient were similar in both periods. There was a 71% relative reduction in errors per patient (p < 0.0001) and a 76% relative reduction in errors per drug order (p < 0.0001) between the control and active periods. The number of errors rated as high‐extreme, moderate or minor, decreased by 64%, 71% and 90% respectively. Overall, the most common types of error were drug omissions (63%); and the most common drugs involved were cardiovascular (31.5%), central nervous system (18%), respiratory (12.6%) and endocrine (10.8%). Conclusion An ED pharmacist providing timely medication histories resulted in admitted patients significantly more likely to receive an accurate medication chart early in their hospital stay.

Background Our health service is introducing an electronic medication management system (eMMs). Obtaining baseline data on the work patterns of pharmacists will allow assessment of the impact of the eMMs on pharmacists' work patterns. Aim To quantify the time clinical pharmacists spend on various activities over their working day prior to the implementation of an eMMs. Method During this continuous observational time‐and‐motion study (23 November to 17 December 2009), clinical pharmacists assigned to general medical and surgical wards were shadowed by two independent observers over their entire working days. A customised Access application was used to log times and calculate average times spent on each activity. Other data collected included time from admission to interview and opportunities for medication chart review. Results 9 pharmacists were observed for 265.3 hours over 30 separate pharmacist observation days. Clinical activities (56% of total time) included professional communication (20%), medication chart review (9.6%), medication history interview (9.5%), clinical review (9.1%), providing information to patients/carers (5.5%), ascertaining discharge drugs required (1.6%), and obtaining drug information (0.5%). Non‐clinical activities (44% of total time) included social activities/breaks (13%), meetings (6.9%), ordering/distribution (6.6%), discharge dispensing (6.3%), walking between wards/pharmacy (5.2%), looking for something (3.1%), and other activities (2.8%). On an average day, each pharmacist reviewed 21 of a possible 38 medication charts (55%), spent 20 minutes on clinical interventions and completed 4.5 medication history interviews. Average time from admission to interview was 67 hours. 18% of pharmacists' time was taken up with discharge/transfer of patients. Most patients 130/141 (93%) at discharge did not require further medication history clarification. Conclusion This study provides baseline data for comparison of the impact of the eMMs on pharmacist workflow.

Aim:To evaluate a pharmacist-initiated e-script transcription service for discharged patients. Method: A sequential prospective study of 2 groups of 40 eligible medical patients recruited from the neurology and respiratory wards. Pre-implementation of the service, baseline data were collected from 40 consecutive medical patients. After the new service was implemented and allowing for a 2 week run-in period, data were collected from a further 40 consecutive medical patients. The outcome indicators were the time taken to discharge patients and the number of prescribing errors. Results: The pharmacist-initiated e-script transcription service was successfully implemented. The discharge process was faster with the time taken from decision to discharge to actual discharge decreased by 34% (p = 0.02). The time spent by dispensing pharmacists in clarifying and amending discharge prescriptions decreased from 9.5 to 1.5 minutes per patient. The time spent by doctors in preparing discharge prescriptions fell from 15 to 2 minutes per patient. There were also fewer prescribing errors -number of errors decreased from 0.83 to 0.1 per patient (p = 0.0005) and from 0.0962 to 0.0137 per item (p = 0.011). Conclusion: Combining a prescribing role with the medication safety elements of electronic prescribing and medication reconciliation has resulted in significant improvements in the quality, accuracy and timeliness of discharge prescriptions. The centralised discharge transcription service is transferable to a wide variety of health settings. The principles of workforce substitution and process change is important as the health system struggles to meet ever increasing demands.

The findings suggest an increased prevalence of AIH among BC's First Nations community. A disproportionate First Nations representation was found on independent review of two databases. Future studies are needed to determine the true prevalence of AIH in this community, and to uncover the genetic predisposition and the environmental triggers explaining this phenomenon.