Diagnostic Support
Conditions
Brief 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.
Interventions
OTHERArtificial 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
University of Pennsylvania
Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging
National Academy of Medicine (NAM)
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
65 Years to No maximum
Healthy volunteers
No
Inclusion criteria
Clinicians 1. Work in the University of Pennsylvania Health System 2. Work in a primary care setting (i.e., Internal Medicine, Geriatric Medicine, Family Medicine, and Penn Primary Care) 3. Actively treat adult patients who are 65 years old or older Patients 1. 65 years of age or older 2. Have an upcoming encounter with a participating primary care clinician 3. Indicate a new or worsening health concern that they wish to discuss at the upcoming encounter Caregivers 1. 18 years old or older 2. Accompanying the participating patient during the encounter with the AI CDSS 3. 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: 1. Under the age of 18 years old 2. Unable to provide informed consent in the opinion of the investigator 3. Has a "Research Do Not Contact" status in the electronic health record
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Feasibility of embedding the AI CDSS into a primary care visit | 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. |
| Acceptability of embedding the AI CDSS into a primary care visit | 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. |
Countries
United States
Contacts
CONTACTAlyssa M Sliwa, BA
CONTACTNicholas Bishop, BA
PRINCIPAL_INVESTIGATORGary E Weissman, MD, MSPH
University of Pennsylvania
Outcome results
None listed