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Addressing Gaps in Reproductive Health Data That Affect Practice, Policy, and Research.

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    Gaps in reproductive health data hinder care and research. Strengthening data infrastructure through standardization and linkage is crucial for evidence-based reproductive healthcare across the lifespan.

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    Area of Science:

    • Reproductive Health
    • Health Data Science
    • Public Health

    Background:

    • Reproductive health data are essential for understanding lifelong health.
    • Current data gaps limit clinical care, public health surveillance, and research.
    • Inconsistent data collection and accessibility pose significant challenges.

    Purpose of the Study:

    • Examine barriers to comprehensive reproductive health data collection.
    • Review the impact of data gaps on various reproductive health aspects.
    • Propose an agenda to improve reproductive health data infrastructure.

    Main Methods:

    • Analysis of structural and political constraints on data collection.
    • Review of privacy, consent, and documentation challenges.
    • Assessment of disruptions to publicly available datasets.

    Main Results:

    • Identified barriers include structural, political, privacy, and documentation issues.
    • Data gaps impact assessment of menstrual health, contraception, pregnancy, and postpartum outcomes.
    • Disparities in morbidity and mortality are exacerbated by poor data.

    Conclusions:

    • Standardized measurement and improved data linkage are vital.
    • Coordinated leadership is needed to strengthen reproductive health data infrastructure.
    • Enhanced data systems will support evidence-based practice and policy across the reproductive lifespan.