Evidence map›Paper›PMID 29087984›Full record

ArticleMedical care2018

Improved Identification of Venous Thromboembolism From Electronic Medical Records Using a Novel Information Extraction Software Platform.

Raymund B Dantes, Shuai Zheng, James J Lu, Michele G Beckman, Asha Krishnaswamy, Lisa C Richardson, Sheri Chernetsky-Tejedor, Fusheng Wang

Abstract read
In one paragraph

Article in Medical care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. A systematic approach to venous thromboembolism prevention: a focus on UK experience.Research and practice in thrombosis and haemostasis · 2023
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Review
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

8 authors.

Raymund B DantesDepartments of Medicine, Division of Hospital Medicine.
Shuai ZhengBiomedical Informatics, Emory University School of Medicine.
James J LuDepartment of Mathematics and Computer Science, Emory University.
Michele G BeckmanDivision of Blood Disorders, National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention.
Asha KrishnaswamyDivision of Heart Disease and Stroke Prevention, National Center for Chronic Disease Prevention and Health Promotion.
Lisa C RichardsonDivision of Cancer Prevention and Control, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta GA.
Sheri Chernetsky-TejedorDepartments of Medicine, Division of Hospital Medicine.
Fusheng WangBiomedical Informatics, Emory University School of Medicine.

Funding

Intramural CDC HHS CC999999
6 · The paper itself

Abstract

introductionThe United States federally mandated reporting of venous thromboembolism (VTE), defined by Agency for Healthcare Research & Quality Patient Safety Indicator 12 (AHRQ PSI-12), is based on administrative data, the accuracy of which has not been consistently demonstrated. We used IDEAL-X, a novel information extraction software system, to identify VTE from electronic medical records and evaluated its accuracy.

methodsMedical records for 13,248 patients admitted to an orthopedic specialty hospital from 2009 to 2014 were reviewed. Patient encounters were defined as a hospital admission where both surgery (of the spine, hip, or knee) and a radiology diagnostic study that could detect VTE was performed. Radiology reports were both manually reviewed by a physician and analyzed by IDEAL-X.

resultsAmong 2083 radiology reports, IDEAL-X correctly identified 176/181 VTE events, achieving a sensitivity of 97.2% [95% confidence interval (CI), 93.7%-99.1%] and specificity of 99.3% (95% CI, 98.9%-99.7%) when compared with manual review. Among 422 surgical encounters with diagnostic radiographic studies for VTE, IDEAL-X correctly identified 41 of 42 VTE events, achieving a sensitivity of 97.6% (95% CI, 87.4%-99.6%) and specificity of 99.8% (95% CI, 98.7%-100.0%). The performance surpassed that of AHRQ PSI-12, which had a sensitivity of 92.9% (95% CI, 80.5%-98.4%) and specificity of 92.9% (95% CI, 89.8%-95.3%), though only the difference in specificity was statistically significant (P<0.01).

conclusionIDEAL-X, a novel information extraction software system, identified VTE from radiology reports with high accuracy, with specificity surpassing AHRQ PSI-12. IDEAL-X could potentially improve detection and surveillance of many medical conditions from free text of electronic medical records.

Indexed as

AgedAged, 80 and overAge FactorsElectronic Health RecordsFemaleHospitals, SpecialHumansInformation Storage and RetrievalLength of StayMaleMiddle AgedOrthopedic ProceduresSensitivity and SpecificitySex FactorsUnited StatesVenous Thromboembolism

Identifiers

PMID29087984
PMCPMC5927846

What OpenQuestion holds

Textmetadata
LicenceTDM
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.