Secondary Use of Electronic Health Record Data for Prediction of Outpatient Visit Length in Ophthalmology Clinics

Wei Chun Lin, Isaac H. Goldstein, Michelle Hribar, Abigail Huang, Michael Chiang

Research output: Contribution to journalArticle

Abstract

Electronic health record systems have dramatically transformed the process of medical care, but one challenge has been increased time requirements for physicians. In this study, we address this challenge by developing and validating analytic models for predicting patient encounter length based on secondary EHR data. Key findings from this study are: (1) Secondary use of EHR data may be captured to predict provider interaction time with patients; (2) Modeling results using secondary data may provide more accurate predictions of provider interaction time than an expert provide; (3) These findings suggest that secondary use of EHR data may be used to develop effective customized scheduling methods to improve clinical efficiency. In the future, this has the potential to contribute toward methods for improved clinical scheduling and efficiency.

Original languageEnglish (US)
Pages (from-to)1387-1394
Number of pages8
JournalAMIA ... Annual Symposium proceedings. AMIA Symposium
Volume2018
StatePublished - Jan 1 2018

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Electronic Health Records
Ophthalmology
Outpatients
Physicians

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Secondary Use of Electronic Health Record Data for Prediction of Outpatient Visit Length in Ophthalmology Clinics. / Lin, Wei Chun; Goldstein, Isaac H.; Hribar, Michelle; Huang, Abigail; Chiang, Michael.

In: AMIA ... Annual Symposium proceedings. AMIA Symposium, Vol. 2018, 01.01.2018, p. 1387-1394.

Research output: Contribution to journalArticle

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