Evidence map›Paper›PMID 37043168›Full record

ArticleDrug safety2023

Validation of an ICD-9-Based Algorithm to Identify Stillbirth Episodes from Medicaid Claims Data.

Sabina O Nduaguba, Nicole E Smolinski, Thuy N Thai, Steven T Bird, Sonja A Rasmussen, Almut G Winterstein

Abstract read
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In one paragraph

Article in Drug safety, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

6 authors at 3 institutions in 2 countries.

Sabina O NduagubaDepartment of Pharmaceutical Systems and Policy, College of Pharmacy, West Virginia University, Morgantown, WV, USA.ORCID http://orcid.org/0000-0001-6383-2603
Nicole E SmolinskiDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, 1225 Center Drive, PO Box 100496, Gainesville, FL, 32611, USA.
Thuy N ThaiDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, 1225 Center Drive, PO Box 100496, Gainesville, FL, 32611, USA.
Steven T BirdDivision of Epidemiology, Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, MD, USA.
Sonja A RasmussenCenter for Drug Evaluation and Safety (CoDES), University of Florida, Gainesville, FL, USA.
Almut G WintersteinDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, 1225 Center Drive, PO Box 100496, Gainesville, FL, 32611, USA. almut@cop.ufl.edu.ORCID http://orcid.org/0000-0002-6518-5961
Center for Drug Evaluation and Research · USUniversity of Florida · USWest Virginia University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn administrative data, accurate timing of exposure relative to gestation is critical for determining the effect of potential teratogen exposure on pregnancy outcomes.

objectiveTo develop an algorithm for identifying stillbirth episodes in the ICD-9-CM era using national Medicaid claims data (1999-2014).

methodsUnique stillbirth episodes were identified from clusters of medical claims using a hierarchy that identified the encounter with the highest potential of including the actual stillbirth delivery and that delineated subsequent pregnancy episodes. Each episode was validated using clinical detail on retrieved medical records as the gold standard.

resultsAmong 220 retrieved records, 197 were usable for validation of 1417 stillbirth episodes identified by the algorithm. The positive predictive value (PPV) was 64.0% (57.3-70.7%) overall, 80.4% (73.8-87.1%) for inpatient episodes, 28.2% (14.1-42.3%) for outpatient-only episodes, and 20.0% (2.5-37.5%) for outpatient episodes with overlapping hospitalizations. The absolute difference between the dates of the algorithm-specified stillbirth delivery and the medical record-based event was 4.2 ± 24.3 days overall, 1.7 ± 7.7 days for inpatient episodes, 14.3 ± 51.4 days for outpatient-only episodes, and 1.0 ± 2.0 days for outpatient episodes that overlapped with a hospitalization. Excluding all outpatient episodes, as well as pregnancies involving multiple births, the PPV increased to 82.7% (76.8-89.8%).

conclusionsOur algorithm to identify stillbirths from administrative claims data had a moderately high PPV. Positive predictive value was substantially increased by restricting the setting to inpatient episodes and using only input diagnostic codes for singleton stillbirths.

Indexed as

International Classification of DiseasesStillbirthAlgorithmsDatabases, FactualFemaleHumansMedicaidPregnancyPregnancy Outcome

Identifiers

PMID37043168
OpenAlexW4365135027

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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.