Evidence map›Paper›PMID 38779571›Full record

ArticleJAMIA open2024

Call me Dr Ishmael: trends in electronic health record notes available at emergency department visits and admissions.

Brian W Patterson, Daniel J Hekman, Frank J Liao, Azita G Hamedani, Manish N Shah, Majid Afshar

Erratum issuedAbstract read
In one paragraph

Article in JAMIA open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Leveraging artificial intelligence to reduce diagnostic errors in emergency medicine: Challenges, opportunities, and future directions.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2025
    Review
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Brian W PattersonBerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, United States.ORCID https://orcid.org/0000-0002-4584-3808
Daniel J HekmanBerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, United States.ORCID https://orcid.org/0000-0002-7964-9501
Frank J LiaoBerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, United States.ORCID https://orcid.org/0000-0002-7577-7530
Azita G HamedaniBerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, United States.
Manish N ShahBerbeeWalsh Department of Emergency Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, United States.
Majid AfsharDepartment of Medicine, University of Wisconsin-Madison, Madison, WI 53705, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over the time since EHR establishment. Materials and Methods: We conducted a retrospective analysis of EHR data from a large healthcare system, examining the number of notes and a corresponding number of total words and total tokens across all notes available to physicians during patient encounters in the emergency department (ED). We assessed the change in these metrics over a 17-year period between 2006 and 2023. Results: The study cohort included 730 968 ED visits made by 293 559 unique patients and a total note count of 132 574 964. The median note count for all encounters in 2006 was 5 (IQR 1-16), accounting for 1735 (IQR 447-5521) words. By the last full year of the study period, 2022, the median number of notes had grown to 359 (IQR 84-943), representing 359 (IQR 84-943) words. Note and word counts were higher for admitted patients. Discussion: The volume of notes available for review by providers has increased by over 30-fold in the 17 years since the implementation of the EHR at a large health system. The task of reviewing these notes has become commensurately more difficult. These data point to the critical need for new strategies and tools for filtering, synthesizing, and summarizing information to achieve the promise of the medical record.

Indexed as

documentationemergency medicinenatural language processingsummarization

Identifiers

PMID38779571
PMCPMC11110617

What OpenQuestion holds

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LicenceCC BY
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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.