Abstract：
BACKGROUND: Medication reconciliation (MedRec) in hospitals is an important tool to enhance the continuity of care, but completing MedRec is challenging.
OBJECTIVE: The aim of this study was to investigate whether queueing theory could be used to compare various interventions to optimise the MedRec process to ultimately reduce the number of patients discharged prior to MedRec being completed. Queueing theory, the mathematical study of waiting lines or queues, has not been previously applied in hospital pharmacies but enables comparisons without interfering with the baseline workflow.
METHODS: Possible interventions to enhance the MedRec process (replacing in-person conversations with telephone conversations, reallocating pharmacy technicians (PTs) or adjusting their working schedule) were compared in a computer experiment. The primary outcome was the percentage of patients with an incomplete discharge MedRec. Due to the COVID-19 pandemic, it was possible to add a real-life post hoc intervention (PTs starting their shift later) to the theoretical interventions. Descriptive analysis was performed.
RESULTS: The queueing model showed that the number of patients with an incomplete discharge MedRec decreased from 37.2% in the original scenario to approximately 16% when the PTs started their shift 2 h earlier and 1 PT was reassigned to prepare the discharge MedRec. The number increased with the real-life post hoc intervention (PTs starting later), which matches a decrease in the computer experiment when started earlier.
CONCLUSIONS: Using queueing theory in a computer experiment could identify the most promising theoretical intervention to decrease the percentage of patients discharged prior to MedRec being completed.
OBJECTIVE: The aim of this study was to investigate whether queueing theory could be used to compare various interventions to optimise the MedRec process to ultimately reduce the number of patients discharged prior to MedRec being completed. Queueing theory, the mathematical study of waiting lines or queues, has not been previously applied in hospital pharmacies but enables comparisons without interfering with the baseline workflow.
METHODS: Possible interventions to enhance the MedRec process (replacing in-person conversations with telephone conversations, reallocating pharmacy technicians (PTs) or adjusting their working schedule) were compared in a computer experiment. The primary outcome was the percentage of patients with an incomplete discharge MedRec. Due to the COVID-19 pandemic, it was possible to add a real-life post hoc intervention (PTs starting their shift later) to the theoretical interventions. Descriptive analysis was performed.
RESULTS: The queueing model showed that the number of patients with an incomplete discharge MedRec decreased from 37.2% in the original scenario to approximately 16% when the PTs started their shift 2 h earlier and 1 PT was reassigned to prepare the discharge MedRec. The number increased with the real-life post hoc intervention (PTs starting later), which matches a decrease in the computer experiment when started earlier.
CONCLUSIONS: Using queueing theory in a computer experiment could identify the most promising theoretical intervention to decrease the percentage of patients discharged prior to MedRec being completed.
摘要：
背景：医院中的药物和解（MedRec）是增强护理连续性的重要工具，但完成MedRec是一项挑战.
目的：本研究的目的是调查排队论是否可用于比较各种干预措施，以优化MedRec流程，最终减少MedRec完成之前的出院患者数量。排队论,等待排队或排队的数学研究，以前未在医院药房应用，但可以在不干扰基线工作流程的情况下进行比较。
方法：增强MedRec流程的可能干预措施（用电话交谈代替面对面交谈，在计算机实验中比较了重新分配药房技术人员（PT）或调整其工作时间表）。主要结果是MedRec不完全出院患者的百分比。由于COVID-19大流行，有可能在理论干预的基础上增加现实生活中的事后干预(PT稍后开始转变).进行描述性分析。
结果：排队模型显示，不完全出院MedRec的患者人数从原来的37.2％下降到大约16％，当PT提前2小时开始转移时，1个PT被重新分配以准备MedRec出院。随着现实生活中的事后干预(PT开始较晚)，这与较早开始时计算机实验的减少相匹配。
结论：在计算机实验中使用排队理论可以确定最有希望的理论干预措施，以降低MedRec完成前出院患者的百分比。
目的：本研究的目的是调查排队论是否可用于比较各种干预措施，以优化MedRec流程，最终减少MedRec完成之前的出院患者数量。排队论,等待排队或排队的数学研究，以前未在医院药房应用，但可以在不干扰基线工作流程的情况下进行比较。
方法：增强MedRec流程的可能干预措施（用电话交谈代替面对面交谈，在计算机实验中比较了重新分配药房技术人员（PT）或调整其工作时间表）。主要结果是MedRec不完全出院患者的百分比。由于COVID-19大流行，有可能在理论干预的基础上增加现实生活中的事后干预(PT稍后开始转变).进行描述性分析。
结果：排队模型显示，不完全出院MedRec的患者人数从原来的37.2％下降到大约16％，当PT提前2小时开始转移时，1个PT被重新分配以准备MedRec出院。随着现实生活中的事后干预(PT开始较晚)，这与较早开始时计算机实验的减少相匹配。
结论：在计算机实验中使用排队理论可以确定最有希望的理论干预措施，以降低MedRec完成前出院患者的百分比。
