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.
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
65 years of age or older
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
Single group
Artificial intelligence-based clinical decision support tool for diagnostic support
Other interventionINTERLACE 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.
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.
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.
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.
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.
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University of Pennsylvania
Lead sponsor
Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging
Collaborator
National Academy of Medicine (NAM)
Collaborator
This trial is not recruiting at the moment. You can still explore other options:
