Medical-AI trial: a chatbot to bring hereditary-cancer genetic testing to an underserved population — reducing health inequity (NCT05562778)
An interventional study comparing a chatbot that uses AI and natural language processing against usual care, to see whether it can raise the rate of recommending genetic testing among patients at elevated risk of a familial cancer syndrome, in an all-Medicaid gynecology clinic. It also evaluates drivers of inequity in access to testing. The primary outcome is the proportion recommended for genetic testing. 150 patients; recruiting.
Trial overview (primary data)
- StatusRecruiting
- ConditionsGynecologic Cancer, Hereditary Cancer Syndrome
- InterventionsOTHER: Chatbot
- SponsorWeill Medical College of Cornell University
- Target enrollment150 participants
- Period2023-01-15 〜 2027-12-01
Key points
- An interventional study comparing an AI/natural-language chatbot with usual care to raise genetic-testing recommendation rates among patients at elevated risk of familial cancer syndrome.
- The setting is an all-Medicaid gynecology clinic, an underserved population.
- It also evaluates drivers of inequity in access to and use of genetic testing.
- The primary outcome is the proportion of patients recommended for genetic testing. 150 patients; recruiting.
- It uses AI for access rather than accuracy; an evaluation of recommendation rates and access, not an establishment of counselor replacement or clinical-outcome improvement.
Some breast and ovarian cancers stem from hereditary (familial) cancer syndromes caused by changes in genes such as BRCA. Identifying this risk through genetic testing can guide prevention and early detection for the patient and precautions for the family. But genetic counseling and testing are limited by a shortage of specialists and do not reach underserved groups (such as low-income or public-assistance patients) well. This study tests whether an AI chatbot can close that gap.
Per the registry summary, it compares a chatbot using AI and natural language processing against usual care, to determine whether it can raise the rate of recommending genetic testing among patients at elevated risk of a familial cancer syndrome in an all-Medicaid gynecology clinic. It also evaluates drivers of inequity in access to and use of genetic testing.
The primary outcome is the proportion of patients recommended for genetic testing. The size is 150, and it is recruiting.
The key here is using AI not for accuracy but as a tool to scale access. If a chatbot can standardize and handle at volume the time-consuming intake of genetic risk that specialists cannot keep up with, it might extend testing opportunities to groups previously missed.
Putting health equity front and center is important for judging the social value of AI. That said, this study evaluates recommendation rates and access factors; it does not establish replacement of genetic counselors or improvement in clinical outcomes.
Why it matters
Using AI for access rather than accuracy, with health equity front and center, this design could extend testing to groups previously missed if a chatbot can standardize and scale the intake specialists cannot keep up with (this study evaluates recommendation rates and access, not clinical-outcome improvement).
FAQ
Why does inequity in access to genetic testing matter?
Does the chatbot replace a genetic counselor?
Sources (primary)
Source: ClinicalTrials.gov (U.S. NIH/NLM, public domain). This site does not provide medical advice. Verify the latest and exact details with the official source. This site is not endorsed or certified by the NIH/NLM.
- ClinicalTrials.gov (study record, original)
- NCT ID: NCT05562778