Data Driven Scheduling for Improving Patient Efficiency in Ophthalmology Clinics.

OBJECTIVE: 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 one pediatric ophthalmologist's clinic utilizing 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 five different pediatric ophthalmologists.

SUBJECTS: Participants, and/or Controls: We observed and timed patient appointments in-person (n=120) and collected EHR timestamps for two years of appointments (n=650). We calculated efficiency measures for 172 clinic sessions pre-implementation vs. 119 clinic sessions post-implementation.

METHODS: Intervention, or Testing: 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 pre- vs. post-implementation.

MAIN OUTCOME MEASURES: Measurements of clinical efficiency (mean clinic volume, patient wait time, exam time, and clinic length).

RESULTS: Mean physician exam time calculated from EHR timestamps was 13.8 ± 8.2 minutes, and was not statistically different from mean physician exam 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 five pediatric ophthalmologists showed statistically-significant improvements in clinic volume (mean increase of 1-3 patients/session, p≤0.05 for 2, p≤0.008 for 3), while four of five 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' exam times remained the same pre- and post-implementation.

CONCLUSIONS: and Relevance: 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. EHRs have potential to become tools for supporting clinic operations improvement.