Background We describe the introduction, use, and evaluation of an automation and integration pharmacy development program in a private facility in Saudi Arabia. The project was specifically undertaken to increase throughput, reduce medication dispensing error rates, improve patient satisfaction, and free up pharmacists’ time to allow for increased face-to-face consultations with patients. Objective We forecasted growth of our outpatient service at 25% per annum over 5- and 10-year horizons and set out to prepare our outpatient pharmacy service to meet this demand. Initial project goals were set as a 50% reduction in the average patient wait time, a 15% increase in patient satisfaction regarding pharmacy wait time and pharmacy services, a 25% increase in pharmacist productivity, and zero dispensing errors. This was expected to be achieved within 10 months of go-live. Realignment of pharmacist activity toward counseling and medication review with patients was a secondary goal, along with the rapid development of a reputation in the served community for patient-centered care. Methods Preimplementation data for patient wait time for dispensing of prescribed medications as a specific measure of patient satisfaction was gathered as part of wider ongoing data collection in this field. Pharmacist activity and productivity in terms of patient interaction time were gathered. Reported and discovered dispensing errors per 1000 prescriptions were also aggregated. All preimplementation data was gathered over an 11-month period. Results From go-live, data were gathered on the above metrics in 1-month increments. At the 10-month point, there had been a 53% reduction in the average wait time, a 20% increase in patient satisfaction regarding pharmacy wait time, with a 22% increase in overall patient satisfaction regarding pharmacy services, and a 33% increase in pharmacist productivity. A zero dispensing error rate was reported. Conclusions The robotic pharmacy solution studied was highly effective, but a robust upstream supply chain is vital to ensure stock levels, particularly when automated filling is planned. The automation solution must also be seamlessly and completely integrated into the facility’s software systems for appointments, medication records, and prescription generation in order to garner its full benefits. Overall patient satisfaction with pharmacy services is strongly influenced by wait time and follow-up studies are required to identify how to use this positive effect and make optimal use of freed-up pharmacist time. The extra time spent by pharmacists with patients and the opportunity for complete overview of the patient’s medication history, which full integration provides, may allow us to address challenging issues such as medication nonadherence. Reduced wait times may also allow for smaller prescription fill volumes, and more frequent outpatient department visits, allowing patients to have increased contact time with pharmacists.

BACKGROUND We describe the introduction, use and evaluation of an automation and integration pharmacy development program in a private facility in Saudi Arabia. The project was undertaken to meet specific challenges of increasing throughput, reducing medication dispensing error, increasing patient satisfaction, and freeing up pharmacists’ time for increased face-to-face consultations with patients. OBJECTIVE To reduce outpatient waiting times for dispensing of medications, to help to free up time to meet patient expectations for pharmacy services including medication education, to reduce the volume of non-value-added pharmacist tasks, to reduce dispensing error rates, and to aid with the rapid development of a reputation in the served community for patient-centred care for a new facility. METHODS Pre-implementation data for patient wait-time for dispensing of prescribed medications as one measure of patient satisfaction, pharmacist activity and productivity in terms of patient interaction time were gathered. Reported and discovered dispensing errors per 1,000 prescriptions were also aggregated. All pre-implementation data was gathered over an eleven- month period. Initial project goals were set as a 50% reduction in the average patient wait-time, a 15% increase in patient satisfaction regarding pharmacy waiting time and pharmacy services, a 25% increase in pharmacist productivity and zero dispensing errors. This was expected to be achieved within ten months of go-live. RESULTS From go-live, data was gathered on the above metrics in one-month increments. At the 10-month point there had been a 53% reduction in the average waiting time, a 20% increase in patient satisfaction regarding pharmacy waiting time, with a 22% increase in overall patient satisfaction regarding pharmacy services, and a 33% increase in pharmacist productivity. There was a zero-rate dispensing error reported. CONCLUSIONS The robotic pharmacy solution studied was highly effective, but upstream supply chain is vital to throughput maintenance, particularly when automated filling is planned. The automation solution must also be seamlessly and completely integrated into the facility’s software systems for appointments, medication records and prescription in order to garner its full benefits. Patient overall satisfaction with pharmacy services is strongly influenced by waiting time and follow up studies ae required to identify how to use this positive effect and how to optimally use ‘freed-up’ pharmacist time. The extra time spent with patients by pharmacists, and the complete overview of the patient’s medication history, that full integration gives, creates opportunities for tackling challenging issues such as medication nonadherence. Reduced waiting times may also allow for smaller prescription fill volumes, and more frequent outpatient department visits, allowing increased contact time with pharmacists.