University of Pennsylvania
Philadephia, Pennsylvania, 19104, United States
Not Yet Recruiting
NCT Number: NCT07553559
Evaluating an Artificial Intelligence-Based Diagnostic Support Tool for Older Adults in Primary Care
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.
Not Yet Recruiting
Trial opening soon.
Get NotifiedKey information
Conditions
Age range
65 year and older
Sex eligibility
All sexes
Study type
Interventional
Phase
Not applicable
Primary location
Who can participate
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Clinicians
- Work in the University of Pennsylvania Health System
- Work in a primary care setting (i.e., Internal Medicine, Geriatric Medicine, Family Medicine, and Penn Primary Care)
- Actively treat adult patients who are 65 years old or older
Patients
- 65 years of age or older
- Have an upcoming encounter with a participating primary care clinician
- Indicate a new or worsening health concern that they wish to discuss at the upcoming encounter
Caregivers
- 18 years old or older
- Accompanying the participating patient during the encounter with the AI CDSS
- Identified by the patient as a caregiver
Exclusion criteria
An individual who meets any of the following criteria will be excluded from participation in this study:
- Under the age of 18 years old
- Unable to provide informed consent in the opinion of the investigator
- Has a "Research Do Not Contact" status in the electronic health record
Treatment and study plan
Artificial intelligence-based clinical decision support tool for diagnostic support
OtherINTERLACE 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.
Primary outcomes
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Feasibility of embedding the AI CDSS into a primary care visit
Time frame: From enrollment to the end of the study interview, up to two weeks
Participants will complete a Feasibility of Intervention Measure (FIM) via feedback survey following the primary care visit. Responses are measured on a 5-point Likert scale.
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Feasibility of embedding the AI CDSS into a primary care visit
Time frame: From enrollment until the end of the study interview, up to two weeks
Feasibility will also be assessed through brief survey questions asking whether participants experienced any barriers to using INTERLACE, whether it was useful during the visit, and how long it was used (all measured on a 7-point Likert scale), as well as open-ended questions in a semi-structured interview.
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Acceptability of embedding the AI CDSS into a primary care visit
Time frame: From enrollment until the end of the study interview, up to two weeks
Participants will complete the Acceptability of Intervention Measure (AIM) via feedback survey after the primary care visit. Responses to the AIM are measured on a 5-point Likert scale.
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Acceptability of embedding the AI CDSS into a primary care visit
Time frame: From enrollment until the end of the study interview, up to two weeks
Participants will also complete a modified version of the Technology Acceptance model (TAM). Responses to the TAM are measured on a 7-point Likert scale.
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Acceptability of embedding the AI CDSS into a primary care visit
Time frame: From enrollment until the end of the study interview, up to two weeks
Participants will complete a Net Promoter Score assessing the likelihood that they would recommend the AI CDSS to others at the end of the survey. This will be measured on a 10-point scale.
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Acceptability of embedding the AI CDSS into a primary care visit
Time frame: From enrollment until the end of the study interview, up to two weeks
Acceptability will also be assessed through brief survey questions assessing whether INTERLACE caused distress (measured on a 7 point Likert scale), as well as open-ended questions in a semi-structured interview.
Study contacts
Contact information is provided by the study sponsor or research team.
Alyssa M Sliwa, BA
CONTACT
Nicholas Bishop, BA
CONTACT
Sponsors and collaborators
Lead sponsor
University of Pennsylvania
Other
Collaborators
- National Academy of Medicine (NAM)
- Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging
Registry information
Official study title
Advancing Diagnostic Excellence For Older Adults Through Collective Intelligence And Imitation Learning
Acronym: INTERLACE
Important dates
- Study start
- 2026
- Primary completion
- 2026
- Study completion
- 2026
- First posted
- Apr 28, 2026
- Registry last updated
- Jul 10, 2026
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.