VALIDATE: Virtual Agent Linked Intelligent Disease Assessment Tool Engine
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About
The collection and analysis of family, medical, lifestyle, and environmental exposure history (a Comprehensive Health History or "CHH") can identify critical risk factors for many chronic and life-threatening conditions, including cancer. Despite its importance, CHH is infrequently documented and analyzed in primary-care medical practice due to numerous hurdles, and currently available tools have proven inadequate to address this critical problem. This study will evaluate the Virtual Agent Linked Intelligent Disease Assessment Tool Engine ("VALIDATE") system as an easy to administer, accurate, cost-effective, and clinically useful tool for collecting and analyzing structured CHH data.
Full description
Our study's objective is to evaluate the Virtual Agent Linked Intelligent Disease Assessment Tool Engine ("VALIDATE") system as a means to improve the affordability and ease, while maintaining the validity and feasibility, of collecting, assessing, and acting on Comprehensive Health History data.
Virtual Agents (VAs) are fully autonomous and embodied software agents that use both verbal (e.g. speech) and non-verbal modalities (e.g., gaze, gesturing) to simulate a clinician-patient encounter. These agents have already successfully shown advantages to patients for: entering family history data on their own, facilitating medication adherence, providing behavioral health information, serving as clinical interviewers, promoting breastfeeding, and educating about and motivating exercise and weight loss. The VALIDATE system has been developed to be a fully automated alternative to the currently extremely labor-intensive process of collecting and transcribing CHH data. VALIDATE will be evaluated for its capability to significantly diminish clinician time and cost to collect, review, analyze, and document accurate and complete certain CHH data directly from patients at home using their own personal desktop computers. VALIDATE will also be evaluated for its capability to identify valid clinical action, e.g. referral indications for familial cancer assessment based on American College of Medical Genetics and Genomics (ACMG)/National Society of Genetic Counselors (NSGC) and National Comprehensive Care Network (NCCN) Guidelines.
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Inclusion criteria
All adults above the age of 18
Exclusion criteria
Children under the age of 18
Trial design
Primary purpose
Allocation
Interventional model
Masking
0 participants in 2 patient groups
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Data sourced from clinicaltrials.gov
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