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Determining what matters: data resources for examining maternal health equity
Leremy A Colf1, Karina M Shreffler1
1Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States.
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.
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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