Previously submitted to: JMIR Formative Research (no longer under consideration since Jul 24, 2023)
Date Submitted: Oct 13, 2022
Open Peer Review Period: Oct 13, 2022 - Dec 8, 2022
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Differentiating Physicians by Note-taking Practices in the EHR: A Case Study of a Open-source Tool to Cluster Providers into Phenotypes of Electronic Health Record Documentation Behavior
ABSTRACT
Background:
Background:
Documenting clinical notes in Electronic Health Record (EHR) systems is a crucial job for physicians, yet characterizing provider documentation behavior is still difficult because of the lack of applications to do so.
Objective:
Objective:
This study aims to analyze physician documentation behavior phenotypes at a multi-specialty clinic, as well as develop open-source software to make such profiling more easily available for other clinics to replicate.
Methods:
Methods:
For this observational retrospective study, we analyzed data on physician note-taking behavior from EPIC Signal and applied the k-means clustering algorithm to identify and analyze different phenotypes in the data set.
Results:
Results:
We developed an efficient tool and easy-to-follow protocol to profile provider documentation behavior, which identified four physician phenotype clusters within our data. Of these four, two were characterized by physicians with high note-taking efficiency, with one cluster having low documentation length and above-average efficiency, and the other having average documentation length and extremely high efficiency. Of the two remaining clusters, one was characterized by physicians with low note-taking efficiency, and the last consisted of low-volume providers.
Conclusions:
Conclusions:
Cluster analysis is a useful method to characterize different physician note-taking behaviors, which can be used to efficiently identify both physician champions and physicians in need of note-taking training.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.