Clinical Research Directory

Evaluating the Preferences and Tradeoffs of AI-based Electronic Consultations 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.

Deployment and Evaluation of Artificial Intelligence Software for Electrocardiogram Analysis and Management in Primary Care

The DAISEA-ECG project aims to improve the diagnosis of heart diseases in primary care through the DeepECG platform, which combines ECG-AI and ECHONeXT algorithms. This study uses a stepped wedge design, where each Family Medicine Group acts as its own control. The FMGs will gradually transition from the control period (without AI recommendations) to the intervention period (with AI recommendations activated) in a randomized sequence. The primary objective is to compare the sensitivity of family physicians in detecting cardiac pathologies, with and without the assistance of the DeepECG platform. Sensitivity is defined as the proportion of patients correctly referred to cardiology or for transthoracic echocardiography (TTE) among those who indeed required cardiovascular evaluation, as confirmed by an independent adjudication committee.

Ostrobothnia Digital Clinic Experiment

This randomized controlled trial (RCT) examines the impacts of a publicly provided digital clinic that offers digital primary care services to consumers. This intervention grants access to a public digital clinic that provides chat-based primary care consultations via a mobile phone application and website, including care needs assessment, diagnoses, follow-up care recommendations, and prescriptions. The digital clinic supplements traditional public primary care services, including in-person visits and phone consultations. The trial takes place in Ostrobothnia, Finland, a healthcare district serving a population of 178,000 residents. The investigators will randomize access to the digital clinic at the household level, providing access to 50% of the households. By doing so, the investigators aim to evaluate whether digital services can substitute for, complement, or increase the utilization of traditional primary care, particularly in-person visits or calls to traditional clinics. At the end of the nine-month trial, access to the digital clinic will be expanded to the entire population.