Diagnostic SupportINTERLACENCT07553559
Evaluating an Artificial Intelligence-Based Diagnostic Support Tool for Older Adults in Primary Care
A study testing Artificial intelligence-based clinical decision support tool for diagnostic support in people with Diagnostic Support, run by University of Pennsylvania at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 65 years and older
- Conditions the study is for
- Diagnostic Support
- What is being tested?
- Artificial intelligence-based clinical decision support tool for diagnostic support
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 40 participants
- Where
- 1 siteUnited States
- Study dates
- Oct 2026to Jan 2027
- Phase
- Interventional
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 65 years and older
- All sexes
- No healthy volunteers
- Older adult
Who may be able to join
- 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
Show all 12Show fewer
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Nicholas Bishop, BA contact
United States1 site
University of Pennsylvania
Philadephia, Pennsylvania, 19104
Clinical Research Coordinator, 215-746-3080, alyssa.sliwa@pennmedicine.upenn.edu
About this study
Official title: Advancing Diagnostic Excellence For Older Adults Through Collective Intelligence And Imitation Learning
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
- Being tested
- Artificial intelligence-based clinical decision support tool for diagnostic support
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence-based clinical decision support tool for diagnostic supportOther
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.
| Study group | Role | What they receive |
|---|---|---|
| Use of INTERLACE tool in primary care visit | Experimental | All participants will be asked to use INTERLACE in their primary care visit. The tool will be presented on an handheld electronic device and may be used by patients, caregivers, and primary clinicians at each visit. First, the patient will input their current symptoms into INTERLACE. Then, using these symptoms, latest vital signs, and the patient's medical history, INTERLACE will make suggestions for diagnoses and tests. Patients, caregivers, and clinicians can view and discuss these suggestions together to arrive at a potential diagnosis. Receives: Other: Artificial intelligence-based clinical decision support tool for diagnostic support |
What is being measured
The primary outcome is the main question the study is designed to answer.
Feasibility of embedding the AI CDSS into a primary care visit
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.
Measured: From enrollment to the end of the study interview, up to two weeks
Feasibility of embedding the AI CDSS into a primary care visit
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.
Measured: From enrollment until the end of the study interview, up to two weeks
Acceptability of embedding the AI CDSS into a primary care visit
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.
Measured: From enrollment until the end of the study interview, up to two weeks
Acceptability of embedding the AI CDSS into a primary care visit
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.
Measured: From enrollment until the end of the study interview, up to two weeks
Acceptability of embedding the AI CDSS into a primary care visit
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.
Measured: From enrollment until the end of the study interview, up to two weeks
Acceptability of embedding the AI CDSS into a primary care visit
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.
Measured: From enrollment until the end of the study interview, up to two weeks
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Apr 2026
- Study startOct 2026 (estimated)
- Primary completionJan 2027 (estimated)
- Study completionJan 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diagnostic SupportStudies of the same condition, open and under way.
- More trials run by University of PennsylvaniaThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Diagnosis
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 40 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Pennsylvania
- Sponsor type
- University, hospital or other
- Collaborators
- Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging, National Academy of Medicine (NAM)
- Responsible party
- Principal investigator, Gary Weissman, University of Pennsylvania
- Investigators
- Gary E Weissman, MD, MSPH, Principal investigator, University of Pennsylvania
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07553559
- Sponsor's protocol ID
- 852952
- Acronym
- INTERLACE
- Status last verified
- Jul 2026
- First submitted
- 9 Apr 2026
- Last updated
- 23 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No