Improving Hormone Therapy Use in Patients with Premature or Early Menopause

About This Grant

PROJECT SUMMARY Up to 3.1% of women in the United States experience premature menopause (menopause before age 40) and another 6.2% experience early menopause (menopause between age 40-45) due to a spectrum of surgical and non-surgical conditions. Premature/early menopause results in estrogen deprivation which has significant health consequences and adversely affects quality of life. Compared to natural menopause, women who undergo premature/early menopause have an increased risk for cardiovascular disease, osteoporosis, and neurological/psychological conditions, leading to a higher mortality risk. Systemic hormone therapy (HT) is highly effective in mitigating the short- and long-term consequences of estrogen deprivation and is recommended by guidelines from national and international professional organizations. However, research on HT use in women with premature/early menopause is sparse and the limited data available suggest severe underuse. Because women at younger ages are less prepared of menopausal transition and may face greater challenges in work, life, and health care, there is a critical need for research on premature/early menopause. The overarching goal of this project is to improve the long-term health of women with premature/early menopause by understanding factors influencing their HT use and developing a preliminary tool for identifying women at high risk for underuse. We will focus on women without malignancy or hereditary predisposition for cancer – a homogeneous population to better isolate influencing factors. Within this population, we propose the following specific aims: 1) to characterize the overall trajectory and heterogeneity in HT use and identify patient and physician factors associated with HT initiation and continuation; 2) to ascertain patients' and physicians' perceived barriers and facilitators to HT use; and 3) to develop a dynamic risk prediction model for HT underuse and explore the feasibility of a patient prioritization tool for HT counseling. We will achieve these aims by analyzing a unique dataset that integrates insurance claims data with electronic health record data and applying novel analytical approaches to characterize patients’ longitudinal trajectory of HT use (both the overall pattern and heterogeneity among patients), examine physician peer influence in HT practice, and develop artificial intelligence/machine learning-based risk prediction models. This will be supplemented by primary data collection using a mixed methods approach – combining qualitative interviews and focus groups with quantitative surveys of patients and physicians – to uncover individual, structural, and system-level factors influencing HT initiation and continuation and inform proactive interventions for improving HT use. By understanding care patterns related to HT use in women with premature/early menopause, its influencing factors, and characteristics of patients at particularly high risk for HT underuse, this project addresses an important but understudied clinical question. The findings can facilitate targeted interventions and better equip us with the knowledge and tools to improve care for this large population of women.