Objectives To explore factors influencing hospital pharmacy staff acceptance of a pharmacy robotic dispensing system during implementation and over time. Methods A single centred, prospective, longitudinal cohort quantitative study was conducted in an Australian tertiary public hospital using the Extended Technology Acceptance Model (ETAM). Staff were surveyed during the implementation of a pharmacy dispensing robot (May 2016) and again after working with the system for fifteen months (August 2017). Fishers exact test and correlation analysis of paired responses were used to identify significant factors influencing use of the system between the two time points. Key findings Sixty four respondents completed surveys during implementation (n=64) and 34-paired surveys were collected fifteen months later. Respondents were predominantly young, female with a tertiary qualification. Initial perceptions did not change over time, with the exception of reliability. Departmental leaders had greatest influence on technology acceptance during implementation and over time. Other key factors correlating with acceptance included: how useful the robot was perceived to be; ease of use and how relevant the robot was for an individual role. Higher levels of education had a negative association with usage during implementation and age was not a factor. Conclusion This study identified critical insights influencing staff acceptance of pharmacy robots that will help inform future implementation. The influence of pharmacy leaders emerged as key influence on technology acceptance. Leveraging on this influence a communication strategy prior to implementation should include information on useful functions and known benefits of the system customised for individual roles.

Background: Pharmacy robotics have been implemented globally to create medication management efficiencies. However, translation to the Australian public hospital environment has not been evaluated. Aim: To evaluate the impact of introducing robotics in an Australian public hospital on pharmacy imprest and dispensary tasks. Method: A single-centred, prospective, longitudinal time in motion study was conducted in an Australian tertiary public hospital using mixed methods during robot implementation (phase 1, May 2016) and 15 months later (phase 2, August 2017). Time-stamped video footage of dispensary activities was collected, observed and analysed; Fitbit Zip ® anonymously tracked pharmacy assistant movement. Dispensing software (iPharmacy ® ) provided the location of stocked medication and electronic tracking databases provided imprest turnaround times (ethics approval: HREC/16/QGC/66, HREC/17/QGC/18). Results: Medication stored in the robot was limited to 46% (n = 20 771 full packs) of total pharmacy holdings (n = 45 437 full packs). At baseline, 774 orders were received in the dispensary over five days increasing by 13% to 887 in phase 2 (p < 0.01). Dispensary workload increased, staff levels remained constant and movement was reduced. However, there were no significant changes to dispensing rates and turnaround times. Conclusion: Pharmacy robotics has the potential to absorb increased workload and reduce staff movement in the dispensary when staffing levels remain constant. However, turnaround times alone are too simplistic as a sole measure of benefits of robotics in Australian public hospital pharmacy.