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<p>This study investigated pharmacist task optimization strategies in community pharmacies using discrete-event simulation (DES). A 5-day observational survey was conducted on weekdays at a community pharmacy in Japan, and a DES model was created based on the observation data. During the study period, 652 patients visited the pharmacy, and 638 complete datasets were collected. The results of the constructed model were compared with real-world observation data to verify the predicted patient total stay time and model behavior, thereby confirming its validity. The validated model was defined as the baseline model and then used to simulate changes in patient total stay time under the following scenarios: pharmacist staffing adjustments, reduced dispensing time assuming dispensing automation, increased medication counseling time, and a combination of these scenarios. The simulation results indicated that redistributing pharmacists from the counseling area to the dispensing floor reduced patient total stay time from 18.9&#xa0;min (95% confidence interval [CI]: 18.5–19.2) in the baseline model to 14.4&#xa0;min (95% CI: 14.3–14.5), and it increased the proportion of counseling time from 21.0% to 27.6%. Reducing the dispensing time through assumed automation further decreased the patient total stay time to 11.8&#xa0;min and increased the counseling time to 33.6%. Furthermore, the combination of staffing optimization and automation produced the most efficient simulated workflow, enabling extended counseling without substantially increasing the patient total stay time. This study exhibits the potential utility of DES in optimizing pharmacy operations, offering a practical approach to enhancing patient-centered pharmacy services in diverse pharmacy settings and supporting efficient healthcare delivery.</p>

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Optimization of pharmacist operations in community pharmacies using a discrete event simulation model

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月9日

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  • Daisuke Furushima,
  • Atsunori Makita,
  • Daiki Tsuji,
  • Shinya Watanabe,
  • Hiroshi Yamada

摘要

This study investigated pharmacist task optimization strategies in community pharmacies using discrete-event simulation (DES). A 5-day observational survey was conducted on weekdays at a community pharmacy in Japan, and a DES model was created based on the observation data. During the study period, 652 patients visited the pharmacy, and 638 complete datasets were collected. The results of the constructed model were compared with real-world observation data to verify the predicted patient total stay time and model behavior, thereby confirming its validity. The validated model was defined as the baseline model and then used to simulate changes in patient total stay time under the following scenarios: pharmacist staffing adjustments, reduced dispensing time assuming dispensing automation, increased medication counseling time, and a combination of these scenarios. The simulation results indicated that redistributing pharmacists from the counseling area to the dispensing floor reduced patient total stay time from 18.9 min (95% confidence interval [CI]: 18.5–19.2) in the baseline model to 14.4 min (95% CI: 14.3–14.5), and it increased the proportion of counseling time from 21.0% to 27.6%. Reducing the dispensing time through assumed automation further decreased the patient total stay time to 11.8 min and increased the counseling time to 33.6%. Furthermore, the combination of staffing optimization and automation produced the most efficient simulated workflow, enabling extended counseling without substantially increasing the patient total stay time. This study exhibits the potential utility of DES in optimizing pharmacy operations, offering a practical approach to enhancing patient-centered pharmacy services in diverse pharmacy settings and supporting efficient healthcare delivery.