Evidence map›Paper›PMID 33936435›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2020

Learning Tasks of Pediatric Providers from Electronic Health Record Audit Logs.

Barrett Jones, Xinmeng Zhang, Bradley A Malin, You Chen

Abstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Inferring EHR Utilization Workflows through Audit Logs.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2022
    Article
  7. Predicting next-day discharge via electronic health record access logs.Journal of the American Medical Informatics Association : JAMIA · 2021
    Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Barrett JonesDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Xinmeng ZhangDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Bradley A MalinDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
You ChenDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Funding

Discovering Care Coordination Practice Patterns in the EMR: Interpretation and Impact on Patient OutcomesR01LM012854 · NLM · VANDERBILT UNIVERSITY MEDICAL CENTER · PI CHEN, YOU · 2019 to 2022
$1.5M
NLM NIH HHS R01 LM012854
6 · The paper itself

Abstract

The amount of time spent working in the Electronic Health Record (EHR) has become a burden for many providers. We propose computational methods to learn EHR tasks of Pediatrics residents and attending physicians in the treatment of healthy newborns by analyzing EHR audit log data. We perform statistical analyses of the association between EHR events and provider role, leverage word embedding, k-means, and ProM process mining software on audit log data to learn EHR tasks and visualize them. Residents more commonly perform note preparation and result viewing relative to attendings. Attendings perform more communication and chart review. Task workflows analysis resulted in 2 tasks for attendings and 3 tasks for residents. The attending tasks focus on chart review patient report and history, and inbox service. Primary themes for residents are admit/discharge with order creation, note review, and result review.

Indexed as

Electronic Health RecordsChildCommunicationHealth PersonnelHumansInfant, NewbornLearningPediatricsWorkflow

Identifiers

PMID33936435
PMCPMC8075537

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.