Evidence map›Paper›PMID 33112910›Full record

ArticlePloS one2020

Improving US maternal mortality reporting by analyzing literal text on death certificates, United States, 2016-2017.

Marian F MacDorman, Marie Thoma, Eugene Declercq

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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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

7 citing papers in PubMed.

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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

3 authors.

Marian F MacDormanMaryland Population Research Center, University of Maryland, College Park, Maryland, United States of America.ORCID 0000-0003-4266-3163
Marie ThomaDepartment of Family Science, University of Maryland School of Public Health, College Park, Maryland, United States of America.
Eugene DeclercqDepartment of Community Health Sciences, Boston University School of Public Health, Boston, Massachusetts, United States of America.

Funding

Methodological Issues in Maternal Mortality ResearchR21HD095236 · NICHD · UNIV OF MARYLAND, COLLEGE PARK · PI MACDORMAN, MARIAN · 2018 to 2019
$440k
NICHD NIH HHS R21 HD095236
6 · The paper itself

Abstract

Changes in data collection and processing of US maternal mortality data across states over time have led to inconsistencies in maternal death reporting. Our purpose was to identify possible misclassification of maternal deaths and to apply alternative coding methods to improve specificity of maternal causes. We analyzed 2016-2017 US vital statistics mortality data with cause-of-death literals (actual words written on the death certificate) added. We developed an alternative coding strategy to code the "primary cause of death" defined as the most likely cause that led to death. We recoded deaths with or without literal pregnancy mentions to maternal and non-maternal causes, respectively. Originally coded and recoded data were compared for overall maternal deaths and for a subset of deaths originally coded to ill-defined causes. Among 1691 originally coded maternal deaths, 597 (35.3%) remained a maternal death upon recoding and 1094 (64.7%) were recoded to non-maternal causes. The most common maternal causes were eclampsia and preeclampsia, obstetric embolism, postpartum cardiomyopathy, and obstetric hemorrhage. The most common non-maternal causes were diseases of the circulatory system and cancer, similar to the leading causes of death among all reproductive-age women (excluding injuries). Among 735 records originally coded to ill-defined causes, 94% were recoded to more specific, informative causes from literal text. Eighteen deaths originally coded as non-maternal mentioned pregnancy in the literals and were recoded as maternal deaths. Literal text provides more detailed information on cause of death which is often lost during coding. We found evidence of both underreporting and overreporting of maternal deaths, with possible overreporting predominant. Accurate data is essential for measuring the effectiveness of maternal mortality reduction programs.

Indexed as

Death CertificatesMaternal MortalityResearch ReportAdultCause of DeathFemaleHumansMiddle AgedPregnancyUnited StatesYoung Adult

Identifiers

PMID33112910
PMCPMC7592741

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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.