Evidence map›Paper›PMID 36420643›Full record

ArticlePharmacoepidemiology and drug safety2023

Validation of claims-based algorithms to identify non-live birth outcomes.

Yanmin Zhu, Brian T Bateman, Sonia Hernandez-Diaz, Kathryn J Gray, Loreen Straub, Rebecca M Reimers, Beryl Manning-Geist, Elizabeth Yoselevsky, Lockwood G Taylor, Rita Ouellet-Hellstrom and 4 more

Abstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Review
  8. Pregnancy episodes in All of Us: harnessing multi-source data for pregnancy-related research.Journal of the American Medical Informatics Association : JAMIA · 2024
    Article
  9. Review
  10. Article
  11. Article
  12. 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

14 authors.

Yanmin ZhuDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-6697-6450
Brian T BatemanDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Sonia Hernandez-DiazDepartment of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA.ORCID 0000-0003-1458-7642
Kathryn J GrayDepartment of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Loreen StraubDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0003-2623-2726
Rebecca M ReimersDepartment of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Beryl Manning-GeistDepartment of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Elizabeth YoselevskyDepartment of Obstetrics and Gynecology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Lockwood G TaylorCenter for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, USA.
Rita Ouellet-HellstromCenter for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, USA.
Yong MaCenter for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, USA.
Yandong QiangCenter for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, USA.
Wei HuaCenter for Drug Evaluation and Research, United States Food and Drug Administration, Silver Spring, Maryland, USA.
Krista F HuybrechtsDivision of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.ORCID 0000-0001-5805-8430

Funding

TRAINING GRANT IN GENETICST32GM007748 · NIGMS · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI Anne O'Donnell-Luria, Louise Wilkins-Haug · 1985 to 2026
$12.0M
NIGMS NIH HHS T32 GM007748
6 · The paper itself

Abstract

purposePerinatal epidemiology studies using healthcare utilization databases are often restricted to live births, largely due to the lack of established algorithms to identify non-live births. The study objective was to develop and validate claims-based algorithms for the ascertainment of non-live births.

methodsUsing the Mass General Brigham Research Patient Data Registry 2000-2014, we assembled a cohort of women enrolled in Medicaid with a non-live birth. Based on ≥1 inpatient or ≥2 outpatient diagnosis/procedure codes, we identified and randomly sampled 100 potential stillbirth, spontaneous abortion, and termination cases each. For the secondary definitions, we excluded cases with codes for other pregnancy outcomes within ±5 days of the outcome of interest and relaxed the definitions for spontaneous abortion and termination by allowing cases with one outpatient diagnosis only. Cases were adjudicated based on medical chart review. We estimated the positive predictive value (PPV) for each outcome.

resultsThe PPV was 71.0% (95% CI, 61.1-79.6) for stillbirth; 79.0% (69.7-86.5) for spontaneous abortion, and 93.0% (86.1-97.1) for termination. When excluding cases with adjacent codes for other pregnancy outcomes and further relaxing the definition, the PPV increased to 80.6% (69.5-88.9) for stillbirth, 86.6% (80.5-91.3) for spontaneous abortion and 94.9% (91.1-97.4) for termination. The PPV for the composite outcome using the relaxed definition was 94.4% (92.3-96.1).

conclusionsOur findings suggest non-live birth outcomes can be identified in a valid manner in epidemiological studies based on healthcare utilization databases.

Indexed as

Abortion, SpontaneousAlgorithmsDatabases, FactualFemaleHumansPregnancyPregnancy OutcomeStillbirthclaims-based algorithmpositive predictive valuespontaneous abortionstillbirthterminationvalidation study

Identifiers

PMID36420643
PMCPMC10906136

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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.