Clinic Workflow Simulations Using Secondary EHR Data

Overview

Journal AMIA Annu Symp Proc

Specialty Medical Informatics

Date 2017 Mar 9

PMID 28269861

Citations 12

Authors

Michelle R Hribar

David Biermann

Sarah Read-Brown

Leah Reznick

Lorinna Lombardi

Mansi Parikh

Winston Chamberlain

Thomas R Yackel

Michael F Chiang

Affiliations

Soon will be listed here.

Abstract

Clinicians today face increased patient loads, decreased reimbursements and potential negative productivity impacts of using electronic health records (EHR), but have little guidance on how to improve clinic efficiency. Discrete event simulation models are powerful tools for evaluating clinical workflow and improving efficiency, particularly when they are built from secondary EHR timing data. The purpose of this study is to demonstrate that these simulation models can be used for resource allocation decision making as well as for evaluating novel scheduling strategies in outpatient ophthalmology clinics. Key findings from this study are that: 1) secondary use of EHR timestamp data in simulation models represents clinic workflow, 2) simulations provide insight into the best allocation of resources in a clinic, 3) simulations provide critical information for schedule creation and decision making by clinic managers, and 4) simulation models built from EHR data are potentially generalizable.

Citing Articles

Inferring EHR Utilization Workflows through Audit Logs.

Zhang X, Zhao Y, Yan C, Derr T, Chen Y AMIA Annu Symp Proc. 2023; 2022:1247-1256.

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Measuring impact of a quality improvement initiative on glaucoma clinic flow using an automated real-time locating system.

Musser J, Cho J, Cohn A, Niziol L, Ballouz D, Burke D BMC Ophthalmol. 2022; 22(1):283.

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Electronic Health Record Use among Ophthalmology Residents while on Call.

Long C, Tai-Seale M, El-Kareh R, Lee J, Baxter S J Acad Ophthalmol (2017). 2020; 12(2):e143-e150.

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Workflow Differences Affect Data Accuracy in Oncologic EHRs: A First Step Toward Detangling the Diagnosis Data Babel.

Diaz-Garelli F, Strowd R, Lawson V, Mayorga M, Wells B, Lycan Jr T JCO Clin Cancer Inform. 2020; 4:529-538.

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Predicting Wait Times in Pediatric Ophthalmology Outpatient Clinic Using Machine Learning.

Lin W, Goldstein I, Hribar M, Sanders D, Chiang M AMIA Annu Symp Proc. 2020; 2019:1121-1128.

PMID: 32308909 PMC: 7153152.

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