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

NCT07087171 | Recruiting

• 1 other identifier: 2412-LIS-233-AN
• Study Type: observational
• Target: 774
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Infertility (IVF Patients); Artificial Intelligence (AI)

Keywords

IVF; Artificial intelligence; counselling; Conversion rate

Outcome Measures

Primary Outcomes (1)

• 9-month conversion rate

  9-month conversion, with conversion being defined as the first usage of Medically Assisted Reproduction (MAR) following a new patient visit

  From enrollment until 9 months after

Secondary Outcomes (2)

• 3-month MAR conversion

  From enrollment until 3 months after

• 6-month MAR conversion

  From enrollment until 6 month after

Study Arms (2)

Conventional counselling group

A retrospective cohort of patients who underwent their new patient visit with one of the doctors participating in the study between December 2024 and June 2025 will be analyzed.

AI-based counselling group

A prospective cohort of patients undergoing their NPV with one of the doctors participating in the study will receive an artificial intelligence-machine learning report with their accurate personalized probabilities of having a live birth rate together with a medical explanation by their physician

Other: Artificial intelligence-Machine learning report with accurate personalized probabilities of having a live birth rate

Interventions

Artificial intelligence-Machine learning report with accurate personalized probabilities of having a live birth rate OTHER

Patients included in the prospective arm will receive the Univfy® PreIVF Report with their accurate personalized probabilities of having a live birth rate (Univfy®) together with a medical explanation by their physician

AI-based counselling group

Eligibility Criteria

• Age: 18 Years - 45 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

The study period will run from December 1, 2024, to December 31, 2025. During the first phase, from December 1, 2024, to May 31, 2025, a retrospective cohort of patients attending their first appointment at IVI Lisboa with a research team member will have received conventional counseling regarding IVF treatment prognosis. In the second phase, from June 1, 2025, to November 30, 2025, a prospective cohort of patients attending their first appointment with the same team will receive AI-based counseling using the Univfy® PreIVF Report.®.

You may qualify if:

• Infertile patients aged 18-45 years
• Patients willing to undergo Medically Assisted Reproduction (heterosexual couples, same-sex female couples and single females undergoing artificial insemination, IVF/ICSI or oocyte donation treatments)

You may not qualify if:

• Age \>45 years
• Patients who are not candidates for IVF/ICSI
• Patients who are menopausal or peri-menopausal
• Patients undergoing Fertility Preservation
• Same-sex couples who will undergo reception of oocytes from partner.
• Patients who decline to be counselled about their probability of having a live birth from IVF/ICSI treatment

Sponsors & Collaborators

• Instituto Valenciano de Infertilidade de Lisboa: lead
• Univfy Inc.: collaborator

Study Sites (1)

IVI-RMA Lisboa

Lisbon, Portugal

RECRUITING

MeSH Terms

Conditions

Infertility

Condition Hierarchy (Ancestors)

Genital Diseases; Urogenital Diseases

Central Study Contacts

Ana R Neves, MD, PhD

CONTACT

+351 800 180 614; ana.neves@ivirma.com

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: OTHER
• Sponsor Type: NETWORK
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 18, 2025
• First Posted: July 25, 2025
• Study Start: June 11, 2025
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): August 1, 2026
• Last Updated: February 23, 2026

Record last verified: 2025-07

Locations

PT (1)