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Evaluating an Artificial Intelligence-Based Diagnostic Support Tool for Older Adults in Primary Care

NCT07553559 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 40

Last updated 2026-04-28

No results posted yet for this study

Summary

Older adults commonly experience diagnostic errors that may lead to direct harms and increased healthcare costs. Older adults are especially at risk because of higher rates of comorbidity burden, medical complexity, frailty, and cognitive impairment. An artificial intelligence (AI) clinical decision support system (CDSS) offer a promising approach to promote diagnostic excellence for older adults.

The purpose of this study is to assess the acceptability and feasibility of a new AI CDSS for older adults in primary care. The goal of this AI CDSS is to provide diagnostic support during primary care visits (i.e., help make timely and accurate diagnoses) and support communication amongst patients, doctors, and caregivers about the patient's health.

In this study, participants will use the AI CDSS in a primary care visit and review its suggestions for diagnoses and tests. Afterwards, they will complete a feedback survey and interview where they share their thoughts about and experience using the AI CDSS.

Conditions

  • Diagnostic Support

Interventions

OTHER

Artificial intelligence-based clinical decision support tool for diagnostic support

INTERLACE is an artificial intelligence-based clinical decision support tool. It uses a patient's medical history, vital signs, and current symptoms to make suggestions for diagnoses and tests. These suggestions can be considered and discussed amongst patients, caregivers, and clinicians during primary care visits to help find a good diagnosis for the patient's symptoms.

Sponsors & Collaborators

  • Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging

    collaborator UNKNOWN

  • National Academy of Medicine (NAM)

    collaborator UNKNOWN

  • University of Pennsylvania

    lead OTHER

Principal Investigators

  • Gary E Weissman, MD, MSPH · University of Pennsylvania

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
65 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2026-05-31
Primary Completion
2026-09-30
Completion
2026-09-30

Countries

  • United States

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Entities

Companies

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07553559 on ClinicalTrials.gov