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ArticleMaternal and child health journal2017

Evaluation of the Completeness, Data Quality, and Timeliness of Fetal Mortality Surveillance in Wyoming, 2006-2013.

Alexia V Harrist, Ashley Busacker, Charlan D Kroelinger

Abstract readEvaluation Study
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In one paragraph

Article in Maternal and child health journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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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.

Alexia V HarristEpidemic Intelligence Service, Division of Scientific Education and Professional Development, Center for Surveillance, Epidemiology, and Laboratory Services, Centers for Disease Control and Prevention, Atlanta, GA, USA. alexia.harrist1@wyo.gov.ORCID http://orcid.org/0000-0002-3357-3513
Ashley BusackerWyoming Department of Health, Cheyenne, WY, USA.
Charlan D KroelingerMaternal and Child Health Epidemiology Program, Division of Reproductive Health, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, GA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose The number of fetal deaths in the United States each year exceeds that of infant deaths. High quality fetal death certificate data are necessary for states to effectively address preventable fetal deaths. We evaluated completeness of detection of fetal deaths among Wyoming residents that occur out-of-state, quality of cause-of-death data, and timeliness of Wyoming fetal death certificate registration during 2006-2013. Description The numbers of out-of-state fetal deaths among Wyoming residents recorded by Wyoming surveillance and reported by the National Vital Statistics System were compared. Quality of cause-of-death data was assessed by calculating percentage of fetal death certificates completed in Wyoming with ill-defined, unknown, or missing cause-of-death entries. Timeliness was determined using the time between the fetal death and filing of the fetal death certificate with the Wyoming Department of Health Vital Statistics Service. Assessment Wyoming surveillance detected none of the 76 out-of-state fetal deaths among Wyoming residents reported by the National Vital Statistics System. Among 263 fetal death certificates completed in Wyoming and collected by Wyoming surveillance, 108 (41%) contained ill-defined, unknown, or missing cause-of-death entries. Median duration between the fetal death and filing with the Wyoming Vital Statistics Service was 33 days. Conclusion Wyoming fetal mortality surveillance is limited by failure to register out-of-state fetal deaths among residents, poor quality of cause-of-death data, and lack of timeliness. Strategies to improve surveillance include automating interjurisdictional sharing of fetal death data, certifier education, and electronic fetal death registration.

Indexed as

Death CertificatesElectronic Health RecordsFetal DeathFetal MortalityVital StatisticsCause of DeathData AccuracyFemaleHumansPopulation SurveillancePregnancyUnited StatesWyomingElectronic death reportingFetal cause of deathFetal death certificatesFetal mortality

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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.