Generative AI development in healthcare
Clinical and administrative teams work through large volumes of text: notes, referrals, prior authorizations, patient messages, and policies. Generative AI can help staff get through that text faster, provided it runs under the rules that govern patient data.
Where generative AI fits
- Summarizing a long record for a clinician or care coordinator, with the source passage shown next to each point.
- Drafting replies to patient messages for staff to review and send.
- Answering staff questions about internal policies and procedures from your own documents.
- Extracting structured fields from referrals, faxes, and forms.
What shapes the build
Where the model runs
Patient data may need to stay inside your environment. That decides between a hosted model and one deployed in your own cloud account or data center.
What gets logged
Prompts and outputs can contain patient details, so logging, retention, and access need the same care as the records themselves.
Human review
Anything that touches a care decision needs a person accountable for the final call and a way to see what the model relied on.
What we ask first
- Which data will the system see, and does it include identifiable patient information?
- Who reviews the output before it reaches a patient or enters a record?
- Which of your compliance requirements apply, such as HIPAA in the United States, and who signs off?
- What does a wrong answer cost, and how would we notice one?
Services that apply
This page describes the field. We have not published a case study in healthcare yet. The case studies page lists the work we have.