Division of Cardiovascular Medicine, Vanderbilt Medical Center - Nashville TN, United States.
Department of Biomedical Informatics; Vanderbilt Medical Center - Nashville TN, United States.
Int J Med Inform. 2018 Jan;109:49-54. doi: 10.1016/j.ijmedinf.2017.11.001. Epub 2017 Nov 10.
Assessment of outpatient clinic performance is important to optimize patient access. Metrics based on schedule data may assist with assessment of operational efficiency and recovering cancelled appointments.
To define schedule-based characteristics of clinic operations and to evaluate potential for recovery of cancelled appointments.
Sixty-seven weekly cardiology clinics from a single provider over 18 months at an academic medical center were analyzed. Parameters included clinic slots eligible to have patients scheduled (available), slots occupied by appointments (scheduled), and slots for which patients attended the associated visit (appeared). Rates of usage (scheduled/available), appearance (appeared/scheduled), and utilization (appeared/available=usage rate*appearance rate) were calculated. Surplus slots were defined as the difference between available slots and slots occupied by patients that appeared. Cancellation lag-time was defined as the interval between a cancellation and the appointment time. If a patient did not notify the clinic regarding a non-appearance, cancellation lag-time was set to zero. To quantify the impact of a change in clinic operations on efficiency, these metrics were used to evaluate a different cardiologist's clinic before and after its physical location moved.
For approximately 900 patient visits, usage and appearance rates were∼80%, yielding a utilization rate of ∼2/3. On average, there were nearly 8 surplus slots per clinic. Approximately 30% of cancellation lag-times had positive values and nearly half of positive cancellation lag-times were >3h, indicating potential for recovery of those appointments. The intervention analysis showed that usage rate decreased and surplus slots per clinic increased significantly after a change in clinic location.
Schedule-based analysis provides a framework to assess changes to clinic operations, identify mechanisms underlying inefficiency, and suggest solutions for improving clinic performance (i.e. more schedulers in response to low usage rates). Cancellation lag-time analysis suggests recovering a portion of same-day cancellations is plausible.
评估门诊绩效对于优化患者就诊流程至关重要。基于排班数据的指标可以辅助评估运营效率和弥补取消的预约。
定义诊所运营的基于排班的特征，并评估弥补取消预约的潜力。
对一家学术医疗中心的一名医生在 18 个月内的 67 个每周心内科门诊进行分析。参数包括有资格安排患者就诊的诊室数（可预约）、预约占用的诊室数（已预约）和患者实际就诊的诊室数（已到场）。使用率（已预约/可预约）、到场率（已到场/已预约）和利用率（已到场/可预约=使用率×到场率）。剩余诊室数为可预约诊室数与实际到场患者占用的诊室数之差。取消滞后时间定义为取消预约与预约时间之间的间隔。如果患者未通知诊所取消预约，则将取消滞后时间设置为 0。为了量化诊所运营变化对效率的影响，使用这些指标在一位不同的医生的诊所搬迁前后进行评估。
在大约 900 次就诊中，使用率和到场率约为 80%，利用率约为 2/3。平均每个诊所约有 8 个剩余诊室。约 30%的取消滞后时间具有正值，近一半的正值取消滞后时间>3 小时，表明这些预约有恢复的可能。干预分析显示，诊所位置改变后，使用率降低，每个诊所的剩余诊室数增加。
基于排班的分析为评估诊所运营变化、确定效率低下的根本原因以及提出改善诊所绩效的解决方案提供了框架（即增加调度员以应对低使用率）。取消滞后时间分析表明，恢复当天的部分取消预约是可行的。
