This paper is in the following e-collection/theme issue:

User Training and Skills (51) Electronic Health Records (1053)

Published on in Vol 5, No 4 (2018): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9889, first published .
An Optimization Program to Help Practices Assess Data Quality and Workflow With Their Electronic Medical Records: Observational Study

An Optimization Program to Help Practices Assess Data Quality and Workflow With Their Electronic Medical Records: Observational Study

An Optimization Program to Help Practices Assess Data Quality and Workflow With Their Electronic Medical Records: Observational Study

Authors of this article:

Mavis Jones1 Author Orcid Image ;   Reza Talebi1 Author Orcid Image ;   Jennifer Littlejohn1 Author Orcid Image ;   Olivera Bosnic1 Author Orcid Image ;   Jason Aprile1 Author Orcid Image
Article Authors Cited by (6) Tweetations (3) Metrics

Journals

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  2. Mangin D, Lawson J, Adamczyk K, Guenter D. Embedding “Smart” Disease Coding Within Routine Electronic Medical Record Workflow: Prospective Single-Arm Trial. JMIR Medical Informatics 2020;8(7):e16764 View
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  4. Tell A, Westenhöfer J, Harth V, Mache S. Stressors, Resources, and Strain Associated with Digitization Processes of Medical Staff Working in Neurosurgical and Vascular Surgical Hospital Wards: A Multimethod Study. Healthcare 2023;11(14):1988 View

Books/Policy Documents

  1. Fung D, Poremski D. Starting At the Beginning. View