AI-Driven Model Impact on Patient Engagement in Medically Assisted Reproduction

Recruiting now

Conditions studied: Infertility (IVF Patients), Artificial Intelligence (AI)

In brief

Infertility is a globally significant medical condition, profoundly impacting individuals and couples both emotionally and physically. The multifaceted nature of in vitro fertilization (IVF) treatment demands active patient participation, with engagement playing a pivotal role in treatment success and satisfaction. However, suboptimal engagement can lead to challenges such as not initiating treatment, missed appointments, medication errors, dropping out and heightened stress levels, all of which may adversely affect clinical outcomes. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have revolutionized healthcare, offering innovative solutions for personalized patient care. In IVF, AI-ML models hold the potential to enhance patient engagement by delivering tailored communication, reminders, and educational support, but also improved prognostication by providing personalized and accurate predictions of treatment outcomes. These capabilities enable patients to make more informed decisions and enhance their adherence to treatment protocols.This protocol outlines a prospective evaluation of an AI-ML model, specifically the Univfy PreIVF report, developed to improve patient engagement in IVF care. Recently, a retrospective, multicenter study reported improved IVF utilization rates among patients counselled using the Univfy PreIVF Report. The current study will prospectively assess the model's effectiveness in addressing individual patient needs and creating a supportive treatment environment. Specifically, this study will measure adherence to providers' recommendation of treatment protocols. By analyzing the impact of these interventions, this research aims to provide robust evidence for the integration of AI-ML technologies in reproductive medicine, paving the way for broader implementation and improved patient outcomes.

Key facts

Study ID
NCT07087171
Run by
Instituto Valenciano de Infertilidade de Lisboa
People needed
774
Starts
2025-06-11
Expected to finish
2026-08-01
Last updated by the study team
2026-02-23

Who can join

Age: 18 and older, up to 45. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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