Authors (including presenting author) :
LO LY(1), TO, HHF(1)
Affiliation :
(1)Department of Pharmacy, NTWC
Introduction :
Fast queue service, designed for single-item prescriptions, aims to reduce patient waiting time in outpatient pharmacy. Traditional dispensing workflow involves dispensers collecting printed labels and walking around the pharmacy to locate medications, which may increase the risk of medication incidents, particularly with Look-Alike Sound-Alike (LASA) medications. While label triage system has been successfully utilized in multiple-item prescriptions by automatically generating labels at designated drug shelf, its application in fast queue service remains unexplored.
Objectives :
This study aims to investigate the feasibility and effectiveness of implementing label triage system in the fast queue service. By introducing this modification, we aim to enhance medication safety by reducing the risk of LASA-related incidents while streamlining the dispensing process. The project will assess both safety outcomes and operational efficiency to determine the overall impact of this workflow transformation in single-item prescription processing.
Methodology :
he implementation process began with infrastructure enhancement, including installation of additional label printers and introduction of colored drug label to distinguish fast queue item from normal queue item during drug assembling. Workflow and staff training were carefully planned to ensure smooth operation. A pilot period was conducted to evaluate its stability and effectiveness in fast queue dispensing. To assess the impact of the implementation, we conducted a staff satisfaction survey (n=24) focusing on key aspects including medication safety, workflow efficiency, and overall system performance. The survey evaluated staff perspectives on wrong drug picking risk reduction, medication safety improvement, reduced walking distance, and enhanced dispensing efficiency.
Result & Outcome :
The implementation demonstrated positive outcomes in both safety and efficiency metrics. Notable findings include zero medication incidents in fast queue prescriptions during the study period. Waiting time analysis showed consistent performance: fast queue average waiting times in June 2022, 2023, and 2024 were 10, 23, and 12 minutes respectively, while normal queue waiting times were 29, 34, and 27 minutes respectively. The system implementation after June 2023 did not negatively impact waiting times, addressing initial concerns about potential delays from the additional drug assembling step. Staff satisfaction survey revealed high acceptance with an overall satisfaction score of 8.14/10. The maintenance of efficient processing times while enhancing safety measures demonstrated successful system implementation without compromising service quality.
