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Phone surveys are crucial for collecting health data but are expensive, time-consuming, and difficult to scale. To overcome these limitations, we propose a survey collection approach powered by conversational Large Language Models (LLMs).

Clinical decision support (CDS) tools are critical for improving care delivery and guideline adherence but are associated with clinician burnout when inadequately designed and implemented. User-centered design (UCD) and implementation science (IS) methods are evidence-based approaches to optimizing CDS tools, but are infrequently used in part due to limited guidance on how to apply them within resource-constrained health systems.This paper focuses on pragmatic application of an integrated UCD-IS approach, demonstrating [...]

Accelerate adoption of clinical research technology that obtains electronic health record (EHR) data through HL7 Fast Healthcare Interoperability Resources (FHIR).

Acute chest pain is a common presentation in the emergency department, characterized by sudden onset with high morbidity and mortality. Traditional diagnostic methods, such as computed tomography (CT) and CT angiography (CTA), are often time-consuming and fail to meet the urgent need for rapid triage in emergency settings.

Covariate-adaptive randomization algorithms (CARAs) can reduce covariate imbalance in randomized controlled trials (RCTs), but a lack of integration into Research Electronic Data Capture (REDCap) has limited their use. We developed a software pipeline to seamlessly integrate CARAs into REDCap as part of the all2GETHER study, a 2-armed RCT concerning HIV prevention.

The growing use of machine learning (ML) in healthcare raises concerns about how data biases affect real-world model performance. While existing frameworks evaluate algorithmic fairness, they often overlook the impact of bias on generalizability and clinical utility, which are critical for safe deployment. Building on prior methods, this study extends bias analysis to include clinical utility, addressing a key gap between fairness evaluation and decision-making.

To assess whether HL7 Fast Healthcare Interoperability Resources (FHIR) can underpin a fully standards-based, end-to-end digital research architecture, demonstrate it in a live study, and quantify its benefits for interoperability and development efficiency.

Patient navigation is designed to identify and address patients' needs throughout their cancer treatment. In the context of a clinical trial designed to deliver a standardized patient navigation protocol, a registry was needed to allow users from across multiple health systems to input patient data, track navigation outreach, and coordinate cancer care in real time. To design a registry to allow patient navigators (PNs) at 6 medical centers across 4 [...]

Federated network studies allow data to remain locally while the research is conducted through the sharing of analytical code and aggregated results across different health care settings and countries. A large number of databases have been mapped to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), boosting the use of analytical pipelines for standardized observational research within this open science framework. Transparency, reproducibility, and robustness of results have [...]

This study aimed to leverage a large language model (LLM) to improve the efficiency and thoroughness of medical record documentation. This study focused on aiding clinical staff in creating structured summaries with the help of an LLM and assessing the quality of these artificial intelligence (AI)-proposed records in comparison to those produced by doctors.This strategy involved assembling a team of specialists, including data engineers, physicians, and medical information experts, to [...]