Presentation (CTI)

OBJECTIVES: Menopause is often inadequately managed, particularly among Black and Asian women. Limited awareness, cultural stigma and delayed diagnoses result in poor treatment and care. The progression from perimenopause to menopause, including prescribed treatments, remains underexplored. We would like to examine the prevalence of menopause-related clinical events, diagnoses and treatment patterns in real-world primary care settings.
METHODS: Primary care data from 11 sites were analysed to identify patients (n=3,738) with clinical events/diagnoses associated with the keyword "menopause" in clinical codes. Clinical codes were categorised into perimenopausal/menopausal, and linked to medication datasets using unique identifiers associated with the specific clinical event.
RESULTS: 1,980 patients were identified with codes classified as menopause (median age 64, range 26-104). 93% had no medications recorded/prescribed for menopause-related clinical events. Most common treatments among the 133 patients receiving prescriptions were Estradiol 10 microgram pessaries (n=31), Estriol 0.01% vaginal cream with applicator (n=11), and Estradiol 50mcg/24hours/Norethisterone 170mcg/24hours transdermal patches (n=10).336 patients were identified with perimenopausal codes (median age 52.5, range 34-84), of whom 80% had no recorded/prescribed medications. Among the 65 treated patients, the most common were Progesterone micronised 100mg capsules (n=16), Estradiol 0.06% transdermal gel (750 microgram per actuation) (n=13), and Generic Evorel Sequi transdermal patches (n=12).At the largest site, prescription rates were 22% (77/349) for menopause and 42% (58/139) for perimenopause patients.
CONCLUSIONS: The findings reveal that most patients lacked prescribed/ recorded medications in primary care, aligning with previous publications of limited awareness and support for menopausal patients and suggesting a potential care gap. Medication data, inconsistently coded and predominantly sourced from three sites, underscored variability in coding and prescribing practices. Future research will utilise more comprehensive datasets to examine how demographic factors (ethnicity, co-morbidities) influence patient care.