Pharmacy Services, OhioHealth Corporation, Columbus, OH, USA.
Division of Outcomes and Translational Sciences, College of Pharmacy, The Ohio State University, Columbus, OH, USA.
J Pharm Pract. 2023 Dec;36(6):1404-1411. doi: 10.1177/08971900221118159. Epub 2022 Aug 11.
To determine the impact of a business intelligence dashboard tool to optimize automated dispensing cabinets (ADCs). A pre-post implementation design was used to evaluate key performance indicators (KPI) before and after the implementation of a dashboard tool to optimize ADCs. Eleven ADCs were optimized in 2 phases according to dashboard recommendations: (1) removal of unused medications over 90 days, (2) adjusting periodic automatic replenishment (PAR) levels, and (3) addition of commonly dispensed medications. The KPI measures that were assessed included inventory cost, no. of stocked medications, stockout percentage, vend to refill ratio, and missing dose messages from nursing. An interrupted-time-series regression was used to quantify the impact of ADCs on the means of measured KPIs. Differences in mean distribution of all KPIs, except missing dose, between the pre- and post-ADC periods during the Phase 1 period were statistically significant: inventory cost (54.2 vs 56), stockout percentage (1.55 vs 1.12), vend to refill ratio (6.83 vs 6.14), and missing dose messages (221 vs 229). Only the mean ADC utilization (57.3 vs 64) and missing dose (228 vs 179) were statistically different between the pre- and post-ADC periods in Phase 2. The interrupted-time-series analysis showed that Phase 1 optimization significantly reduced the cost of inventory (β = -$1.238.00, < .01), no. Stocked medications (β = -8.2, < .01), percent stockout (β = -.49%, < .01), vend-to-refill ratio (β = -1.29%, P<.01) and ADC utilization (β = -.2, < .01). Automated dispensing cabinets optimization, through the use of a dashboard tool, had a positive impact on almost all measured KPIs.
为了确定商业智能仪表板工具对优化自动化配药柜（ADC）的影响。采用实施前后设计，在实施仪表板工具优化 ADC 之前和之后评估关键绩效指标（KPI）。根据仪表板建议，分两个阶段优化了 11 个 ADC：（1）清除超过 90 天未使用的药物，（2）调整定期自动补货（PAR）水平，以及（3）添加常用药物。评估的 KPI 措施包括库存成本、库存药物数量、缺货百分比、销售补充比例以及护理人员的漏服剂量信息。使用中断时间序列回归来量化 ADC 对测量 KPI 的平均值的影响。在第 1 阶段，除了漏服剂量之外，所有 KPI 的平均值分布在 ADC 前后期间的差异均具有统计学意义：库存成本（54.2 比 56），缺货百分比（1.55 比 1.12），销售补充比例（6.83 比 6.14），以及漏服剂量信息（221 比 229）。只有 ADC 利用率（57.3 比 64）和漏服剂量（228 比 179）在第 2 阶段的 ADC 前后期间具有统计学差异。中断时间序列分析表明，第 1 阶段的优化显著降低了库存成本（β = -$1.238.00，<.01），库存药物数量（β = -8.2，<.01），缺货百分比（β = -.49%，<.01），销售补充比例（β = -1.29%，P<.01）和 ADC 利用率（β = -.2，<.01）。通过使用仪表板工具对自动化配药柜进行优化，对几乎所有测量的 KPI 都产生了积极影响。
