# Improving service delivery models of medically assisted reproduction: A patient journey mapping study of sexual minority women couples’ experience of medicalized family formation

> **NIH NIH R01** · HARVARD PILGRIM HEALTH CARE, INC. · 2024 · $99,998

## Abstract

PROJECT SUMMARY/ABSTRACT
 The parent R01 grant has quantified numerous obstetrical and perinatal health disparities among sex-
ual minority women (SMW; e.g., those with same-sex attractions, same-sex behavior, and/or lesbian/gay/bi-
sexual identity) and their offspring compared to their heterosexual counterparts using data from unique, pro-
spective, intergenerational cohorts—the Nurses' Health Studies and Growing Up Today Study. Documented
disparities include adverse perinatal mental health—a known contributor to adverse obstetrical and perinatal
outcomes. Yet, due to small sample sizes and other methodological limitations, little is known about the mech-
anisms that drive SMW's perinatal mental health inequities and how this may influence subsequent health in-
equities. When forming biological and/or genetic families, many SMW in same-sex couples require specialized
fertility services due to a lack of sperm within their relationship. However, negative and discriminating experi-
ences, lack of provider knowledge, and barriers to accessing care are common experiences among SMW fertil-
ity patients. Additionally, undergoing fertility care can be emotionally and financially distressing, and SMW are
more likely to have a history of mental illness—a risk factor for perinatal mental illness. Given these considera-
tions, it is prudent to understand SMW's preconception mental health and if the role of structural antecedents
to the perinatal period (e.g., fertility care experiences) may uniquely influence SMW's adverse perinatal mental
health. Consequently, this research will help identify whether promoting positive patient experiences and men-
tal health during fertility care may serve as a critical intervention point for this population. To address these
gaps, the proposed aims of this community-placed, mixed methods study are to 1) elucidate the patient experi-
ence of fertility care among SMW and their partners in same-sex couples and 2) develop best practices for in-
clusive family formation data collection in the Nurses' Health Studies and Growing Up Today Study. We will
achieve these aims by conducting online semi-structured interviews, quantitative assessments of mental health
and patient experiences, and family formation timelines—an established graphical elicitation method that pro-
motes the report of temporal narratives through the co-creation of research data. This project will produce the
first investigation of the patient experience of fertility care among SMW across the U.S. It will also be among
the first best practices developed for accurately collecting inclusive family formation data in large population-
based surveys. This work will have a positive impact on the field of SMW's perinatal health by identifying po-
tential mechanisms of adverse preconception mental health and, subsequently, adverse perinatal and obstetri-
cal outcomes. Additionally, this work will reconceptualize how fertility research is conducted to accurately char-
...

## Key facts

- **NIH application ID:** 11020435
- **Project number:** 3R01MD015256-05S1
- **Recipient organization:** HARVARD PILGRIM HEALTH CARE, INC.
- **Principal Investigator:** Brittany Michelle Charlton
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $99,998
- **Award type:** 3
- **Project period:** 2021-05-16 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11020435

## Citation

> US National Institutes of Health, RePORTER application 11020435, Improving service delivery models of medically assisted reproduction: A patient journey mapping study of sexual minority women couples’ experience of medicalized family formation (3R01MD015256-05S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/11020435. Licensed CC0.

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