Evidence map›Paper›PMID 32884825›Full record

ArticleAcute medicine & surgery

Validation of chief complaints, medical history, medications, and physician diagnoses structured with an integrated emergency department information system in Japan: the Next Stage ER system.

Tadahiro Goto, Konan Hara, Katsuhiko Hashimoto, Shoko Soeno, Toru Shirakawa, Tomohiro Sonoo, Kensuke Nakamura

Open access · goldAbstract read
In one paragraph

Article in Acute medicine & surgery. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
5.8field-weighted citation impact, top 4% of its field
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

13 citing papers in PubMed, 21 citations in OpenAlex.

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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

7 authors at 5 institutions in 1 country.

Tadahiro GotoDepartment of Clinical Epidemiology and Health Economics School of Public Health The University of Tokyo Tokyo Japan.ORCID https://orcid.org/0000-0002-5880-2968
Konan HaraDepartment of Public Health Graduate School of Medicine The University of Tokyo Tokyo Japan.
Katsuhiko HashimotoDepartment of Emergency Medicine Southern Tohoku General Hospital Koriyama Japan.
Shoko SoenoDepartment of Emergency Medicine Southern Tohoku General Hospital Koriyama Japan.
Toru ShirakawaDepartment of Social Medicine Osaka University Graduate School of Medicine Osaka Japan.
Tomohiro SonooDepartment of Emergency Medicine Hitachi General Hospital Hitachi Japan.ORCID https://orcid.org/0000-0002-9182-7059
Kensuke NakamuraDepartment of Emergency Medicine Hitachi General Hospital Hitachi Japan.
Hitachi General Hospital · JPSouthern Tohoku General Hospital · JPThe University of Osaka · JPThe University of Tokyo · JPUniversity of Tokyo Health Sciences · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimEmergency department information systems (EDIS) facilitate free-text data use for clinical research; however, no study has validated whether the Next Stage ER system (NSER), an EDIS used in Japan, accurately translates electronic medical records (EMRs) into structured data.

methodsThis is a retrospective cohort study using data from the emergency department (ED) of a tertiary care hospital from 2018 to 2019. We used EMRs of 500 random samples from 27,000 ED visits during the study period. Through the NSER system, chief complaints were translated into 231 chief complaint categories based on the Japan Triage and Acuity Scale. Medical history and physician's diagnoses were encoded using the International Classification of Diseases, 10th Revision; medications were encoded as Anatomical Therapeutic Chemical Classification System codes. Two reviewers independently reviewed 20 items (e.g., presence of fever) for each study component (e.g., chief complaints). We calculated association measures of the structured data by the NSER system, using the chart review results as the gold standard.

resultsSensitivities were very high (>90%) in 17 chief complaints. Positive predictive values were high for 14 chief complaints (≥80%). Negative predictive values were ≥96% for all chief complaints. For medical history and medications, most of the association measures were very high (>90%). For physicians' ED diagnoses, sensitivities were very high (>93%) in 16 diagnoses; specificities and negative predictive values were very high (>97%).

conclusionsChief complaints, medical history, medications, and physician's ED diagnoses in EMRs were well-translated into existing categories or coding by the NSER system.

Indexed as

Chief complaintelectronic health recordemergency departmentnatural language processing

Identifiers

PMID32884825
PMCPMC7453131
OpenAlexW3082448508

What OpenQuestion holds

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Registered trials

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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.