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Improving IVF Utilization with Patient-Centric Artificial Intelligence-Machine Learning (AI/ML): A Retrospective
Mylene W M Yao1, Elizabeth T Nguyen1, Matthew G Retzloff2
1Department of R&D, Univfy Inc., 117 Main Street, #139, Los Altos, CA 94022, USA.
Machine learning prognostic reports significantly increased in vitro fertilization (IVF) utilization among new fertility patients. These data-driven tools enhance patient-provider counseling and treatment decisions for better IVF success rates.
Area of Science:
- Reproductive Medicine
- Artificial Intelligence in Healthcare
- Health Services Research
Background:
- In vitro fertilization (IVF) remains underutilized globally, despite its potential to help millions conceive.
- Effective patient-provider counseling and data-driven treatment decisions are crucial for optimizing IVF outcomes.
- Existing prognostic tools may lack global applicability or local adaptability.
Purpose of the Study:
- To investigate the association between the use of machine learning, center-specific (MLCS) prognostic reports (Univfy®) and IVF utilization rates.
- To assess how MLCS reports impact provider-patient counseling and subsequent treatment decisions.
- To determine if MLCS report usage influences the conversion rates to intra-uterine insemination (IUI) and/or IVF.
Main Methods:
- Retrospective cohort study of 24,238 new patient visits across seven fertility centers (2016-2022).
- Analysis of Univfy® report usage and its correlation with first IUI and/or IVF conversion within 180 days, 360 days, and "Ever" of the new patient visit.
- Statistical analysis using odds ratios (OR) to determine the association between report usage and IVF conversion.
Main Results:
- Univfy® report usage was significantly associated with higher direct and total IVF conversion rates across all timeframes (180-day, 360-day, Ever).
- Odds ratios for total IVF conversion ranged from 2.78 to 3.81 (p < 0.05), indicating a substantial increase with report usage.
- Older age was identified as a minor independent predictor of IVF conversion among patients using the Univfy® report, after accounting for center-specific factors.
Conclusions:
- Patient-centric, MLCS-based prognostic reports are linked to increased IVF utilization among new fertility patients.
- These reports can facilitate more informed treatment decisions and improve counseling.
- Further research is recommended to explore factors influencing treatment decisions and optimize patient-centric workflows using MLCS reports.
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