AI-driven support to improve patient engagement during IVF
Assessing the Impact of an Artificial Intelligence-Machine Learning Model on Patient Engagement in Medically Assisted Reproduction
This project will test whether an AI tool that provides personalized live-birth probabilities and tailored messages helps people aged 18–45 undergoing IVF/ICSI or donor cycles stay engaged with treatment and follow clinic recommendations.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 774 (estimated) |
| Ages | 18 Years to 45 Years |
| Sex | All |
| Sponsor | Instituto Valenciano de Infertilidade de Lisboa Research network |
| Locations | 1 site (Lisbon) |
| Trial ID | NCT07087171 on ClinicalTrials.gov |
What this trial studies
This observational study at IVI‑RMA Lisboa will deliver AI/ML reports that provide individualized probabilities of live birth and tailored communication to patients undergoing medically assisted reproduction. Researchers will track engagement metrics such as treatment initiation, appointment attendance, medication adherence, dropout rate, conversion rate, and patient-reported stress and satisfaction. Eligible participants are infertile patients aged 18–45 who plan IVF/ICSI, intrauterine insemination, or oocyte donation and are willing to receive counseling about their personalized prognosis. The study will compare engagement outcomes before and after introduction of the AI reports, using historical or concurrent controls as available.
Who should consider this trial
Good fit: Ideal candidates are infertile individuals aged 18–45 planning IVF/ICSI, intrauterine insemination, or oocyte donation who are willing to receive counseling about their personalized live-birth probability.
Not a fit: Patients older than 45, those not eligible for IVF/ICSI, menopausal or peri‑menopausal individuals, those undergoing fertility preservation, people who decline counseling about live‑birth probabilities, and same‑sex couples receiving partner oocytes are unlikely to benefit from this intervention.
Why it matters
Potential benefit: If successful, this approach could give patients clearer personalized chances of success plus tailored reminders and education that help more people start and complete treatment, reduce dropouts, and lower stress.
How similar studies have performed: Previous AI models have improved prediction of IVF outcomes and aided counseling in some reports, but applying AI specifically to increase patient engagement and conversion rates is relatively novel with limited published evidence.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * 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) Exclusion Criteria: * 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
Where this trial is running
Lisbon
- IVI-RMA Lisboa — Lisbon, Portugal (Recruiting)
Study contacts
- Study coordinator: Ana R Neves, MD, PhD
- Email: ana.neves@ivirma.com
- Phone: +351 800 180 614
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.