Hundley Hayden E, Hudson Mark E, Wasan Ajay D, Emerick Trent D
Department of Anesthesiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA.
Department of Anesthesiology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
J Pain Res. 2018 Dec 17;12:1-8. doi: 10.2147/JPR.S173345. eCollection 2019.
The aim of this study is to identify scheduling inefficiencies and to develop a personalized schedule based on diagnosis, service time (face-to-face time between the patient and the provider), and patient wait time using a Gantt diagram in a chronic pain clinic.
This is an observational prospective cohort quality improvement (QI) study.
This study was carried out at a single outpatient multidisciplinary pain management clinic in a university teaching hospital.
New and established chronic pain patients at the University of Pittsburgh Medical Center (UPMC) Montefiore Chronic Pain Clinic were recruited for this study.
Time tracking data for each phase of clinic visit and pain-related diagnoses were collected from 81 patients on 5 clinic days in March 2016 for patient flow analysis.
A Gantt diagram was created using Microsoft Excel software. Areas of overbooking and underbooking were identified. Median service times (minutes) differed dramatically based on the diagnosis and were highest for facial pain (23 [IQR, 15-31]) and chronic abdominal and/or pelvic pain (21.5 [IQR, 16-27]) and lowest for myalgia. Abdominal and/or pelvic pain and facial pain median service times consistently exceeded the 15-minute allocation for return visits.
Schedule efficiency analysis using the Gantt diagram identified trends of overbooking and underbooking and inefficiencies in examination room utilization. A 15-minute appointment for all return patients is unrealistic due to variation of service times for some diagnoses. Scheduling appointments based on the diagnosis is an innovative approach that may reduce scheduling inefficiencies and improve patient satisfaction and the overall quality of care. To the best of our knowledge, this type of scheduling diagram has not been used in a chronic pain clinic.
本研究旨在识别日程安排效率低下的问题，并使用甘特图为一家慢性疼痛诊所制定基于诊断、服务时间（患者与医护人员面对面交流的时间）和患者等待时间的个性化日程安排。
这是一项观察性前瞻性队列质量改进改进（QI研究。
本研究在一所大学教学医院的单一门诊多学科疼痛管理诊所进行。
招募了匹兹堡大学医学中心（UPMC）蒙特菲奥里慢性疼痛诊所的新老慢性疼痛患者参与本研究。
2016年3月的5个诊日，从81名患者处收集了门诊各阶段的时间跟踪数据以及疼痛相关诊断信息，用于患者流程分析。
使用微软Excel软件创建了甘特图。识别出了预约过多和预约不足的区域。根据诊断不同，中位服务时间（分钟）差异显著，面部疼痛的中位服务时间最高（23[四分位间距，15 - 31]），慢性腹部和/或盆腔疼痛次之（21.5[四分位间距，16 - 27]），肌痛的中位服务时间最低。腹部和/或盆腔疼痛以及面部疼痛的中位服务时间始终超过复诊15分钟的时间分配。
使用甘特图进行日程安排效率分析，识别出了预约过多和预约不足的趋势以及检查室利用效率低下的问题。由于某些诊断的服务时间存在差异，为所有复诊患者安排15分钟的预约是不现实的。根据诊断安排预约是一种创新方法，可能会减少日程安排效率低下的问题，提高患者满意度和整体护理质量。据我们所知，这种类型的日程安排图尚未在慢性疼痛诊所中使用。
