Ana P Pereira, Andrea M Seet, Beatriz Domingues, Dora Janela, Akshat Pradhan, Anabela C Areias, Xin Tong, Virgílio Bento, Vijay Yanamadala, Steven P Cohen, Jennesa Atherton, Fernando Dias Correia, Luke Belz, Fabíola Costa
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引用次数: 0
Abstract
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: The matched cohort included 602 women (301 per group). Relative to CG, IG patients had substantially lower healthcare spending over 12 months, with mean gross per-person pelvic-related savings of $3,082.4 (95% CI $1,270.2 to $4,894.7, p<.001). Savings were primarily associated with fewer surgical procedures (per-person difference of $2,534.2; 95% CI $831.2 to $4,237.2, p=.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.
目的:比较参加雇主赞助的人工智能(AI)结构化盆腔护理项目的女性与在常规临床环境中接受盆底功能障碍(PFD)常规面对面护理的女性的医疗保健利用和支出。方法:从2022年7月至2025年5月,从第三方美国全国索赔数据库中提取精确和倾向评分匹配的队列,进行回顾性付款人视角的经济评估。符合条件的参与者是患有骨盆相关疾病的成年女性,至少有24个月的连续健康保险覆盖,并且在前一年至少有一次骨盆索赔。干预组(IG)由参加人工智能盆腔护理计划的妇女组成(包括由专门从事盆腔健康的物理治疗师异步监测的生物反馈介导的盆底肌肉训练)。比较组(CG)包括寻求PFD医学或物理治疗评估访问的妇女。使用基于潜伏的生长分析评估IG可获得的自我报告临床结果。结果:匹配队列包括602名女性(每组301名)。与CG相比,IG患者在12个月内的医疗保健支出明显较低,平均每人盆腔相关的总节省为3,082.4美元(95% CI 1,270.2美元至4,894.7美元,pp= 0.004),在医疗办公室就诊和成像利用率方面也存在差异。IG参与者在盆底症状负担、工作效率和心理健康方面表现出显著改善。局限性:基于声明的分析不能排除未测量的混淆、错误分类或选择偏差。为期一年的随访限制了对长期经济影响的评估。结论:与常规护理相比,人工智能盆腔护理项目的参与与较低的医疗保健利用率和支出显著相关,主要与较少的手术干预有关。这些发现强调了可获得的、符合指南的人工智能盆腔护理的潜力,以减少与PFD相关的医疗保健支出,并为付款人导向的医疗服务模式提供信息。
期刊介绍:
Journal of Medical Economics'' mission is to provide ethical, unbiased and rapid publication of quality content that is validated by rigorous peer review. The aim of Journal of Medical Economics is to serve the information needs of the pharmacoeconomics and healthcare research community, to help translate research advances into patient care and be a leader in transparency/disclosure by facilitating a collaborative and honest approach to publication.
Journal of Medical Economics publishes high-quality economic assessments of novel therapeutic and device interventions for an international audience