Evidence map›Paper›PMID 34041304›Full record

ArticleOpen forum infectious diseases2021

Diagnostic Accuracy of Health Care Administrative Diagnosis Codes to Identify Nontuberculous Mycobacteria Disease: A Systematic Review.

Carlos Mejia-Chew, Lauren Yaeger, Kevin Montes, Thomas C Bailey, Margaret A Olsen

Open access · goldAbstract read
In one paragraph

Article in Open forum infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

10 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Epidemiology of Pulmonary and Extrapulmonary Nontuberculous Mycobacteria Infections at 4 US Emerging Infections Program Sites: A 6-Month Pilot.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023
    Article
  9. Review
  10. 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

5 authors at 1 institution in 1 country.

Carlos Mejia-ChewDivision of Infectious Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Lauren YaegerBernard Becker Medical Library, Washington University in St. Louis, St. Louis, Missouri, USA.
Kevin MontesDepartment of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Thomas C BaileyDivision of Infectious Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Margaret A OlsenDivision of Infectious Diseases, Department of Medicine, Washington University School of Medicine in St. Louis, St. Louis, Missouri, USA.
Washington University in St. Louis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealth care administrative database research frequently uses standard medical codes to identify diagnoses or procedures. The aim of this review was to establish the diagnostic accuracy of codes used in administrative data research to identify nontuberculous mycobacterial (NTM) disease, including lung disease (NTMLD).

methodsWe searched Ovid Medline, Embase, Scopus, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov from inception to April 2019. We included studies assessing the diagnostic accuracy of

resultsWe identified 5549 unique citations. Of the 96 full-text articles reviewed, 7 eligible studies of moderate quality (3730 participants) were included in our review. The diagnostic accuracy of ICD-9-CM diagnosis codes to identify NTM disease varied widely across studies, with positive predictive values ranging from 38.2% to 100% and sensitivity ranging from 21% to 93%. For NTMLD, 4 studies reported diagnostic accuracy, with positive predictive values ranging from 57% to 64.6% and sensitivity ranging from 21% to 26.9%.

conclusionsDiagnostic accuracy measures of codes used in health care administrative data to identify patients with NTM varied across studies. Overall the positive predictive value of ICD-9-CM diagnosis codes alone is good, but the sensitivity is low; this method is likely to underestimate case numbers, reflecting the current limitations of coding systems to capture NTM diagnoses.

Indexed as

accuracyadministrative data researchICD codesnontuberculous mycobacteriaNTMNTMLD

Identifiers

PMID34041304
PMCPMC8134528
OpenAlexW3165375457

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.