Cancer
Conditions
Brief summary
This project conducts exploratory work on a HIPAA-compliant, large language model (LLM)-based tool that integrates structured and unstructured oncology electronic health record (EHR) data to automate the development of tailored SCPs, paired with a patient-facing chatbot to answer questions about the SCP. Unlike generic AI documentation tools, this system establishes benchmarks for SCP development and embeds user-centered design (UCD) directly into prompt engineering and model governance workflows.
Interventions
A secure LLM pipeline with structured and unstructured EHR data to automatically generate Survivorship Care Plans (SCPs) and develop a patient-facing chatbot to support comprehension. The SCP chatbot will leverage GARDE-Chat, an NCI-funded open-source chatbot platform
Sponsors
Study design
Eligibility
Inclusion criteria
* Adult cancer survivors * Age +18 years, * Speak and understand English * Affiliated with the Huntsman Cancer Institute.
Exclusion criteria
* Under age 18 * Not affiliated with Huntsman Cancer Institute * Unable to speak or understand English
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility: Recruitment Retention | up to 7 days | Feasibility of the interactive AI-SCP and chatbot. This outcome measure will report the proportion of subjects who were retained from recruitment. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Acceptability/Usability: System Usability Scale | up to 7 days | Acceptability and usability of the interactive AI-SCP and chatbot. This outcome measure will report the mean System Usability Scale (SUS) score. SUS scores range from 0-100, with higher scores indicating better usability and lower scores indicating worse usability. |
Countries
United States
Contacts
Huntsman Cancer Institute/ University of Utah