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| Name | Class |
|---|---|
| Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging | UNKNOWN |
| National Academy of Medicine (NAM) | UNKNOWN |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Artificial intelligence-based clinical decision support tool for diagnostic support | Other | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | 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. | 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. | 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. | 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. | From enrollment until the end of the study interview, up to two weeks |
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Inclusion Criteria:
Clinicians
Patients
Caregivers
Exclusion Criteria:
An individual who meets any of the following criteria will be excluded from participation in this study:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Alyssa M Sliwa, BA | Contact | 215-746-3080 | alyssa.sliwa@pennmedicine.upenn.edu | |
| Nicholas Bishop, BA | Contact | nicholas.bishop@pennmedicine.upenn.edu |
| Name | Affiliation | Role |
|---|---|---|
| Gary E Weissman, MD, MSPH | University of Pennsylvania | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| University of Pennsylvania | Philadephia | Pennsylvania | 19104 | United States |
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| 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. | From enrollment until the end of the study interview, up to two weeks |