INTRODUCTION: This paper aims to illustrate the use of computer simulation in evaluating the impact of a prototype automated dispensing system on waiting time in an outpatient pharmacy and its potential as a routine tool in pharmacy management. MATERIALS AND METHODS: A discrete event simulation model was developed to investigate the impact of a prototype automated dispensing system on operational efficiency and service standards in an outpatient pharmacy. RESULTS: The simulation results suggest that automating the prescription-filing function using a prototype that picks and packs at 20 seconds per item will not assist the pharmacy in achieving the waiting time target of 30 minutes for all patients. Regardless of the state of automation, to meet the waiting time target, 2 additional pharmacists are needed to overcome the process bottleneck at the point of medication dispense. However, if the automated dispensing is the preferred option, the speed of the system needs to be twice as fast as the current configuration to facilitate the reduction of the 95th percentile patient waiting time to below 30 minutes. The faster processing speed will concomitantly allow the pharmacy to reduce the number of pharmacy technicians from 11 to 8. CONCLUSION: Simulation was found to be a useful and low cost method that allows an otherwise expensive and resource intensive evaluation of new work processes and technology to be completed within a short time.
INTRODUCTION: This paper aims to illustrate the use of computer simulation in evaluating the impact of a prototype automated dispensing system on waiting time in an outpatient pharmacy and its potential as a routine tool in pharmacy management. MATERIALS AND METHODS: A discrete event simulation model was developed to investigate the impact of a prototype automated dispensing system on operational efficiency and service standards in an outpatient pharmacy. RESULTS: The simulation results suggest that automating the prescription-filing function using a prototype that picks and packs at 20 seconds per item will not assist the pharmacy in achieving the waiting time target of 30 minutes for all patients. Regardless of the state of automation, to meet the waiting time target, 2 additional pharmacists are needed to overcome the process bottleneck at the point of medication dispense. However, if the automated dispensing is the preferred option, the speed of the system needs to be twice as fast as the current configuration to facilitate the reduction of the 95th percentile patient waiting time to below 30 minutes. The faster processing speed will concomitantly allow the pharmacy to reduce the number of pharmacy technicians from 11 to 8. CONCLUSION: Simulation was found to be a useful and low cost method that allows an otherwise expensive and resource intensive evaluation of new work processes and technology to be completed within a short time.
Authors: Matthew F Toerper; Michael A Veltri; Eric Hamrock; Nicole L Mollenkopf; Kristen Holt; Scott Levin Journal: J Pediatr Pharmacol Ther Date: 2014-04
Authors: Benjamin C Loh; Kheng F Wah; Carolyn A Teo; Nadia M Khairuddin; Fairenna B Fairuz; Jerry E Liew Journal: Pharm Pract (Granada) Date: 2017-03-15
Authors: Friday E Okonofua; Rosemary N Ogu; Lorretta F Ntoimo; Mohammed Gana; Ola N Okike; Adetoye Durodola; Hadiza S Galadanci Journal: Ghana Med J Date: 2018-03