ArticleOphthalmology2019
Data-Driven Scheduling for Improving Patient Efficiency in Ophthalmology Clinics.
Article in Ophthalmology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods.Journal of the American Medical Informatics Association : JAMIA · 2020Pooled it
- Patterns of appointment cancellations and no-shows across and within ophthalmology subspecialties.Eye (London, England) · 2026Article
- Surgical capacity in ophthalmology: the unmet need for sustainable solutions.Eye (London, England) · 2026Review
- Enhancing clinical documentation with voice processing and large language models: a study on the LAOS system.NPJ digital medicine · 2025Article
- Factors influencing treatment and time spent with physicians in patients with uveitis compared to other ophthalmology subspecialties in the National Ambulatory Medical Care Survey.Eye (London, England) · 2024Article
- Large language models and their impact in ophthalmology.The Lancet. Digital health · 2023Review
- An operations research approach to automated patient scheduling for eye care using a multi-criteria decision support tool.Scientific reports · 2023Article
- Appointment Scheduling Problem in Complexity Systems of the Healthcare Services: A Comprehensive Review.Journal of healthcare engineering · 2022Review
- Measuring Electronic Health Record Use in the Pediatric ICU Using Audit-Logs and Screen Recordings.Applied clinical informatics · 2021Article
- Observational
- Modeling the impact of COVID-19 on Retina Clinic Performance.BMC ophthalmology · 2021Article
- Artificial intelligence-assisted reduction in patients' waiting time for outpatient process: a retrospective cohort study.BMC health services research · 2021Article
- Evaluation of Electronic Health Record Implementation in an Academic Oculoplastics Practice.Ophthalmic plastic and reconstructive surgeryArticle
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo improve clinic efficiency through development of an ophthalmology scheduling template developed using simulation models and electronic health record (EHR) data.
designWe 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.
participantsWe 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.
methodsWe 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 measuresMeasurements of clinical efficiency (mean clinic volume, patient wait time, examination time, and clinic length).
resultsMean 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.
conclusionsSimulation 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.
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