Leveraging Population Health Datasets to Advance Maternal Health Research.
Background: Maternal mortality is a public health crisis in the U.S., with no improvement in decades and worsening disparities during COVID-19. Social determinants of health (SDoH) shape risk for morbidity and mortality but maternal structural and SDoH are under-researched using population health da...
| Publicado en: | Maternal & Child Health Journal Vol. 27; no. 10; pp. 1683 - 1689 |
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| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Oct2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=172312466&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 172312466 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10927875 N9J jtl: Maternal & Child Health Journal issn: 10927875 maglogo: N pubinfo: dt: Oct2023 vid: 27 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 172312466 164175302 172312466 172312466 10.1007/s10995-023-03695-4 172312466 ppf: 1683 ppct: 6 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Leveraging Population Health Datasets to Advance Maternal Health Research. aug: au: Beck, Dana Hall, Stephanie Costa, Deena Kelly Admon, Lindsay affil: https://ror.org/00jmfr291 National Clinician Scholars Program, University of Michigan, Ann Arbor, MI, USA sug: subj: Maternal Health Services Research, Medical Population Surveillance Methods Databases, Health Evaluation Maternal Mortality Prevention and Control Social Determinants of Health Human Female Pregnancy Databases, Health Utilization Pregnancy Outcomes Data Collection Methods Sample Size Descriptive Statistics Confidence Intervals Questionnaires Funding Source Female ab: Background: Maternal mortality is a public health crisis in the U.S., with no improvement in decades and worsening disparities during COVID-19. Social determinants of health (SDoH) shape risk for morbidity and mortality but maternal structural and SDoH are under-researched using population health data. To expand knowledge of those at risk for or who have experienced maternal morbidity and inform clinical, policy, and legislative action, creative use of and leveraging existing population health datasets is logical and needed. Methods: We review a sample of population health datasets and highlight recommended changes to the datasets or data collection to better inform existing gaps in maternal health research. Results: Across each of the datasets we found insufficient representation of pregnant and postpartum individuals and provide recommendations to enhance these datasets to inform maternal health research. Conclusions: Pregnant and postpartum individuals should be oversampled in population health data to facilitate rapid policy and program evaluation. Postpartum individuals should no longer be hidden within population health datasets. Individuals with pregnancies resulting in outcomes other than livebirth (e.g., abortion, stillbirth, miscarriage) should be included, or asked about these experiences. Significance: We review population health datasets and provide recommendations that would enable maternal health researchers to unlock the full potential of these datasets by exploring the influence of structural factors and SDoH on maternal health among under-researched groups. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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