Determining what matters: data resources for examining maternal health equity

Maternal morbidity and mortality (MMM) rates in the U.S. are high and increasing, and are disproportionately experienced by understudied, underrepresented, and underreported (U3) populations, especially Black, Indigenous, and/or rural women. Decreasing MMM among U3 women would substantially improve...

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Main Authors: Leremy A. Colf, Karina M. Shreffler
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Public Health
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1499468/full
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author Leremy A. Colf
Karina M. Shreffler
author_facet Leremy A. Colf
Karina M. Shreffler
author_sort Leremy A. Colf
collection DOAJ
description Maternal morbidity and mortality (MMM) rates in the U.S. are high and increasing, and are disproportionately experienced by understudied, underrepresented, and underreported (U3) populations, especially Black, Indigenous, and/or rural women. Decreasing MMM among U3 women would substantially improve maternal health equity and health outcomes, yet current data limitations inhibit our ability to fully understand the reasons underlying the disparities or regional nuances. This article calls for leveraging diverse, publicly available data such as deidentified health system utilization data; geocoded locations of hospitals providing multiple levels of maternal care services; and social determinants and demographic data into a series of linked datasets to enable county-level investigations of maternal health equity, healthcare utilization, and health outcomes.
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spelling doaj-art-1e0be25f399d4c24bfb12e9f3edc14b42025-08-20T02:55:06ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-02-011310.3389/fpubh.2025.14994681499468Determining what matters: data resources for examining maternal health equityLeremy A. ColfKarina M. ShrefflerMaternal morbidity and mortality (MMM) rates in the U.S. are high and increasing, and are disproportionately experienced by understudied, underrepresented, and underreported (U3) populations, especially Black, Indigenous, and/or rural women. Decreasing MMM among U3 women would substantially improve maternal health equity and health outcomes, yet current data limitations inhibit our ability to fully understand the reasons underlying the disparities or regional nuances. This article calls for leveraging diverse, publicly available data such as deidentified health system utilization data; geocoded locations of hospitals providing multiple levels of maternal care services; and social determinants and demographic data into a series of linked datasets to enable county-level investigations of maternal health equity, healthcare utilization, and health outcomes.https://www.frontiersin.org/articles/10.3389/fpubh.2025.1499468/fullmaternal healthlinked datahealth equitybirth outcomeshealth policy
spellingShingle Leremy A. Colf
Karina M. Shreffler
Determining what matters: data resources for examining maternal health equity
Frontiers in Public Health
maternal health
linked data
health equity
birth outcomes
health policy
title Determining what matters: data resources for examining maternal health equity
title_full Determining what matters: data resources for examining maternal health equity
title_fullStr Determining what matters: data resources for examining maternal health equity
title_full_unstemmed Determining what matters: data resources for examining maternal health equity
title_short Determining what matters: data resources for examining maternal health equity
title_sort determining what matters data resources for examining maternal health equity
topic maternal health
linked data
health equity
birth outcomes
health policy
url https://www.frontiersin.org/articles/10.3389/fpubh.2025.1499468/full
work_keys_str_mv AT leremyacolf determiningwhatmattersdataresourcesforexaminingmaternalhealthequity
AT karinamshreffler determiningwhatmattersdataresourcesforexaminingmaternalhealthequity