ArticleData in brief2026
Building data capacity for maternal health equity: Introduction of a novel dataset.
Article in Data in brief, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This article describes a new, publicly available data resource linking numerous existing datasets and analyses at the county/FIPS code level. Linked datasets include publicly available data on county demographic makeup (e.g., race, population, etc.), social vulnerability factors, and pregnancy-related hospital utilization. It also includes a new dataset, measuring travel time from each county to the nearest hospital for each of four levels of maternal care services. A wide variety of datasets, including population-level health data, are published by the United States Government for public use. While these data sets are immensely valuable for research and can be used to improve healthcare delivery and outcomes, it can be challenging to find, access, and link the data. Maternal health, population health, and demography researchers as well as healthcare providers and health policy experts, can use this dataset to better understand the causes of maternal morbidity and mortality and to improve health outcomes. By linking these varied data sources, this new data resource allows examination of individual contributing factors as well as the interplay between and relative strengths of multiple correlated factors. Additionally, this dataset allows researchers to add any additional data, simply by using FIPS codes for linking.
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Registered trials
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.