PURPOSE To improve clinic efficiency through development of an ophthalmology scheduling template developed using simulation models and electronic health record (EHR) data. DESIGN We created a computer simulation model of 1 pediatric ophthalmologist's clinic using EHR timestamp data, which was used to develop a scheduling template based on appointment length (short, medium, or long). We assessed its impact on clinic efficiency after implementation in the practices of 5 different pediatric ophthalmologists. PARTICIPANTS We observed and timed patient appointments in person (n = 120) and collected EHR timestamps for 2 years of appointments (n = 650). We calculated efficiency measures for 172 clinic sessions before implementation vs. 119 clinic sessions after implementation. METHODS We validated clinic workflow timings calculated from EHR timestamps and the simulation models based on them with observed timings. From simulation tests, we developed a new scheduling template and evaluated it with efficiency metrics before vs. after implementation. MAIN OUTCOME MEASURES Measurements of clinical efficiency (mean clinic volume, patient wait time, examination time, and clinic length). RESULTS Mean physician examination time calculated from EHR timestamps was 13.8±8.2 minutes and was not statistically different from mean physician examination time from in-person observation (13.3±7.3 minutes; P = 0.7), suggesting that EHR timestamps are accurate. Mean patient wait time for the simulation model (31.2±10.9 minutes) was not statistically different from the observed mean patient wait times (32.6±25.3 minutes; P = 0.9), suggesting that simulation models are accurate. After implementation of the new scheduling template, all 5 pediatric ophthalmologists showed statistically significant improvements in clinic volume (mean increase of 1-3 patients/session; P ≤ 0.05 for 2 providers; P ≤ 0.008 for 3 providers), whereas 4 of 5 had improvements in mean patient wait time (average improvements of 3-4 minutes/patient; statistically significant for 2 providers, P ≤ 0.008). All of the ophthalmologists' examination times remained the same before and after implementation. CONCLUSIONS Simulation models based on big data from EHRs can test clinic changes before real-life implementation. A scheduling template using predicted appointment length improves clinic efficiency and may generalize to other clinics. Electronic health records have potential to become tools for supporting clinic operations improvement.

中文翻译：

---

数据驱动的计划，以提高眼科诊所的患者效率。

目的通过开发使用模拟模型和电子健康记录（EHR）数据开发的眼科调度模板来提高临床效率。设计我们使用EHR时间戳数据创建了一个儿科眼科医生诊所的计算机仿真模型，该模型用于基于约会长度（短，中或长）开发时间表模板。在5位不同的儿科眼科医生的实践中，我们评估了其对临床效率的影响。参加者我们亲自观察并安排了患者预约时间（n = 120），并收集了2年预约时间（n = 650）的EHR时间戳。我们计算了实施前172次临床会议与实施后119次临床会议的效率指标。方法我们验证了根据EHR时间戳和基于观察到的时间的模拟模型计算出的临床工作流程时间。通过仿真测试，我们开发了一个新的调度模板，并在实施前后对比了效率指标。主要观察指标临床效率的指标（平均门诊量，患者等待时间，检查时间和门诊时间）。结果根据EHR时间戳计算得出的医生平均检查时间为13.8±8.2分钟，与现场观察得出的平均医生检查时间（13.3±7.3分钟； P = 0.7）在统计学上无差异，表明EHR时间戳是准确的。模拟模型的平均患者等待时间（31.2±10.9分钟）与观察到的平均患者等待时间（32.6±25.3分钟； P = 0.9）在统计学上没有差异，说明仿真模型是准确的。实施新的计划模板后，所有5名儿科眼科医生的临床表现均有统计学上的显着改善（平均增加1-3名患者/会话； 2名提供者P≤0.05； 3名提供者P≤0.008），而5名中的4名平均患者等待时间的改善（每位患者平均3-4分钟的改善； 2位提供者的统计显着性，P≤0.008）。在实施之前和之后，所有眼科医生的检查时间均保持不变。结论基于电子病历的大数据的仿真模型可以在实际实施之前测试诊所的变化。使用预测的约会长度的调度模板可以提高诊所效率，并且可以推广到其他诊所。