Evaluating the Preferences and Tradeoffs of AI-based Electronic Consultations for Older Adults in Primary Care
Evaluating the Safety and Appropriateness of AI-based E-Consults for Older Adults in Primary Care
Electronic consultations, or e-consults, let a primary care doctor request medical advice from a specialist without requiring the patient to attend a separate visit. Artificial intelligence (AI) systems may be able to provide this type of advice, potentially making e-consults faster and less costly. However, whether AI-based e-consults are acceptable may depend on how patients and clinicians weigh factors such as who provides the advice, how quickly it is received, its cost, and its quality.
The purpose of this study is to examine how older adult patients and primary care clinicians weigh these factors when comparing e-consults produced by a human specialist with those produced by an AI system. In the study, participants will complete a one-time survey in which they compare sets of two hypothetical e-consults. Each e-consult will include a different combination of features, such as whether the advice comes from a human or AI, the expected wait time, the cost, and the quality of the advice. This study will estimate how much patients and clinicians value each feature in an e-consult. The findings will inform the potential future AI e-consults, so they better reflect patient and clinician preferences.
Aperçu de l'étude
Statut
Les conditions
Intervention / Traitement
Type d'étude
Inscription (Estimé)
Phase
- N'est pas applicable
Contacts et emplacements
Coordonnées de l'étude
- Nom: Nicholas Bishop
- Numéro de téléphone: 215-573-0779
- E-mail: nicholas.bishop@pennmedicine.upenn.edu
Lieux d'étude
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Pennsylvania
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Philadelphia, Pennsylvania, États-Unis, 19104
- Recrutement
- University of Pennsylvania
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Contact:
- Nicholas Bishop
- Numéro de téléphone: 215-573-0779
- E-mail: nicholas.bishop@pennmedicine.upenn.edu
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Critères de participation
Critère d'éligibilité
Âges éligibles pour étudier
- Adulte plus âgé
Accepte les volontaires sains
La description
PATIENTS:
Inclusion Criteria:
- Adult, 65 years of age or older
- Had at least two office visits at Penn Medicine in the past 12 months
- Has an upcoming appointment in a Penn Medicine primary care setting, including family medicine, internal medicine, and geriatric medicine
Exclusion Criteria:
- Documented Alzheimer's, dementia, or related condition
CLINICIANS:
Inclusion Criteria:
- Adult, 18 years of age or older
- Works at Penn Medicine as one of the following: physician, nurse practitioner, or physician's assistant
- Works in a primary care Penn Medicine setting including: family medicine, internal medicine, geriatrics medicine
Exclusion Criteria:
- Actively in medical school, internship, or residency
Plan d'étude
Comment l'étude est-elle conçue ?
Détails de conception
- Objectif principal: Recherche sur les services de santé
- Répartition: N / A
- Modèle interventionnel: Affectation à un seul groupe
- Masquage: Aucun (étiquette ouverte)
Armes et Interventions
Groupe de participants / Bras |
Intervention / Traitement |
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Expérimental: Electronic Consultation Systems
Participants will review 2 different e-consult systems, which will differ in terms of quality, cost, wait time, and source of the e-consult.
Participants will then indicate a preference for 1 e-consult system in each set.
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Participants will review these e-consults systems via a one-time survey lasting about 15 minutes.
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Que mesure l'étude ?
Principaux critères de jugement
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
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Preferences and Tradeoffs of Attributes of Electronic Consults
Délai: From enrollment to the end of the survey, approximately 15 minutes
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Participants will review 12 sets comparing 2 hypothetical e-consults.
Each e-consult is defined by five attributes: the source (i.e., AI vs. human), wait time, cost, and quality of the e-consult, as well as, whether follow-up questions can be asked.
For each set, the outcome is the participant's selection of one e-consult over the other.
We will analyze the results of the discrete choice experiment using mixed-effects logistic regression adjusted for each attribute value with crossed random effects (intercepts) for participant and task.
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From enrollment to the end of the survey, approximately 15 minutes
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Mesures de résultats secondaires
Mesure des résultats |
Description de la mesure |
Délai |
|---|---|---|
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Health Numeracy Measured by the Short Numeracy Understanding in Medicine Instrument
Délai: From enrollment to the end of the survey, approximately 15 minutes
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Health numeracy will be measured using the 8-item Short Numeracy Understanding in Medicine instrument (S-NUMi).
Each correct response contributes one point to the total score.
Total scores range from 0 to 8, with higher scores indicating greater health numeracy.
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From enrollment to the end of the survey, approximately 15 minutes
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Collaborateurs et enquêteurs
Parrainer
Dates d'enregistrement des études
Dates principales de l'étude
Début de l'étude (Réel)
Achèvement primaire (Estimé)
Achèvement de l'étude (Estimé)
Dates d'inscription aux études
Première soumission
Première soumission répondant aux critères de contrôle qualité
Première publication (Réel)
Mises à jour des dossiers d'étude
Dernière mise à jour publiée (Réel)
Dernière mise à jour soumise répondant aux critères de contrôle qualité
Dernière vérification
Plus d'information
Termes liés à cette étude
Autres numéros d'identification d'étude
- 26-5862
Informations sur les médicaments et les dispositifs, documents d'étude
Étudie un produit pharmaceutique réglementé par la FDA américaine
Étudie un produit d'appareil réglementé par la FDA américaine
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