| Literature DB >> 30815183 |
Wei-Chun Lin1, Isaac H Goldstein2, Michelle R Hribar1, Abigail Huang1,3, Michael F Chiang1,2.
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.Entities:
Mesh:
Year: 2018 PMID: 30815183 PMCID: PMC6371379
Source DB: PubMed Journal: AMIA Annu Symp Proc ISSN: 1559-4076