SAFE.AI: Developing and Testing an AI-based Hybrid Chatbot for Financial Empowerment in Rural Cancer Care

Summary

This is a randomized, two-arm, parallel-group pilot trial investigating a new chatbot tool designed to support cancer patients and caregivers, particularly those in rural communities. Approximately 60 participants will be randomized 1:1 to interact with either a hybrid chatbot or an AI-enabled chatbot. Participants will use their assigned chatbot to obtain clear and helpful information related to insurance, travel costs, and other financial aspects of cancer care.

Conditions

• Cancer
• Financial Toxicity

Interventions

OTHER

Rule-Based Chatbot

The rule-based (scripted) SAFE.ai chatbot is a guided conversational tool built to provide structured, accurate, and consistent information to rural cancer patients and caregivers experiencing cancer-related financial toxicity. This chatbot is grounded in the Self-Advocacy for Financial Empowerment (SAFE) resource toolkit, which was co-developed with a community advisory board (CAB) composed of rural patients, caregivers, nurses, and financial navigation experts across HCI's five-state catchment area. All scripted responses reflect priorities identified during qualitative needs assessment sessions, ensuring that content is culturally aligned with rural patient experiences and real-world financial challenges. The chatbot follows a rule-based decision tree. Users progress through the conversation by selecting a response from a set of fixed options displayed on-screen. This ensures that all content is clinically vetted, safe, consistent, and aligned with evidence-based practices.

OTHER

Hybrid Chatbot

The hybrid SAFE.ai chatbot builds on the existing rule-based system by integrating a large language model (LLM) layer to support more flexible, open-ended, and conversational interactions. While the rule-based chatbot provides structured conversations through predefined content, the hybrid approach allows users to ask complex or personalized questions about financial toxicity. To ensure safety and accuracy, the hybrid chatbot is not allowed to generate responses from the open internet. By combining the consistency of rule-based logic with the adaptability of an LLM, the hybrid chatbot will enable users to ask follow-up questions, describe nuanced financial situations, request clarification in their own words, and receive more tailored guidance while still ensuring adherence to SAFE content.

Sponsors & Collaborators

• Huntsman Cancer Institute

  collaborator OTHER

• University of Utah

  lead OTHER

Principal Investigators

• Djin Tay, PhD, RN · Huntsman Cancer Institute/ University of Utah

Study Design

Allocation

RANDOMIZED

Purpose

SUPPORTIVE_CARE

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2026-05-31

Primary Completion

2027-12-31

Completion

2027-12-31

Countries

• United States

Study Locations