• Advances and Challenges in Women’s and Reproductive Health Informatics: A Global Perspective
  • Fatemeh Kiani,1,* Reyhane Norouzi Aval,2
    2. Department of Health Information Technology, Faculty of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.


  • Introduction: Women’s and reproductive health continues to face global challenges, including maternal mortality, infertility, and chronic conditions in midlife and postmenopause. Informatics innovations such as mobile health (mHealth), electronic health records (EHRs), and artificial intelligence (AI) are increasingly applied to improve outcomes across the reproductive life course. This review aims to synthesize recent advances in women’s and reproductive health informatics, identify key challenges such as data privacy and equity, and highlight opportunities for future research and clinical translation.
  • Methods: A narrative review of peer-reviewed literature (2018–2025) was conducted, focusing on applications of digital health, PGHD (person-generated health data), and AI in fertility, pregnancy, postpartum care, and postmenopausal health. Major databases (PubMed, Scopus, Web of Science) were searched using combinations of “women’s health informatics,” “reproductive health,” “mHealth,” “AI,” and “digital equity.”
  • Results: The review showed that artificial intelligence–enhanced fertility tracking applications have improved ovulation prediction and reproductive planning, though concerns regarding data privacy persist. Mobile health platforms demonstrated significant impact on antenatal care, increasing attendance rates and contributing to reductions in preterm birth and hypertensive disorders of pregnancy. In the postpartum period, digital interventions for maternal mental health monitoring and infant immunization tracking improved early identification of risks and service uptake. Among postmenopausal women, informatics models that integrate reproductive history with wearable and clinical data enhanced the prediction of osteoporosis and cardiovascular outcomes. Despite these advances, the field continues to face challenges including limited interoperability between systems, algorithmic bias due to underrepresentation of women in training datasets, and persistent digital divides in low resource settings.
  • Conclusion: Women’s and reproductive health informatics has demonstrated significant benefits in improving maternal, neonatal, and long term outcomes. Future progress requires precision reproductive health approaches, equity centered design, and stronger policy frameworks to ensure digital tools are accessible, secure, and inclusive.
  • Keywords: women’s health informatics; reproductive health; pregnancy; mHealth; artificial intelligence