Breaking barriers in women’s pelvic health: claims-based economic analysis and healthcare utilization of an AI care program compared to usual care

AIM: To compare healthcare utilization and spending among women enrolled in an employer-sponsored, artificial intelligence (AI) structured pelvic care program with those receiving usual in-person care for pelvic floor dysfunction (PFD) in routine clinical settings. METHODS: This retrospective payor-perspective economic evaluation used exact and propensity score-matched cohorts derived from a third-party U.S. nationwide claims database from July 2022 to May 2025. Eligible participants were adult females with a pelvic-related condition, at least 24 months of continuous health-insurance coverage, and a minimum of one pelvic claim in the prior year. Intervention group (IG) comprised women who participated in the AI pelvic care program (consisting of biofeedback-mediated pelvic floor muscle training asynchronously monitored by a physical therapist specialized in pelvic health). Comparator group (CG) included women who sought a medical or physical therapy evaluation visit for PFD. Self-reported clinical outcomes available for the IG were assessed using latent-basis growth analysis. RESULTS: =.004), with differences also noted in medical office visits and imaging utilization. IG participants demonstrated significant improvements in pelvic floor symptom burden, work productivity, and mental health. LIMITATIONS: Claims-based analyses cannot exclude unmeasured confounding, misclassification, or selection bias. The one-year follow-up limits assessment of long-term economic impact. CONCLUSIONS: Participation in this AI pelvic care program was associated with markedly lower healthcare utilization and spending compared with usual care, largely linked to fewer surgical interventions. These findings highlight the potential of accessible, guideline-concordant AI pelvic care to lessen healthcare spending associated with PFD and inform payor-oriented care delivery models.