Please provide your email address to receive an email when new articles are posted on . Use of decentralized elements in cancer clinical trials did not have long-term negative effects on data quality.

As the push to integrate artificial intelligence and increase interoperability evolves, Clinical Architecture sees a dire need for tools that can assess the quality of healthcare data. Poor quality ...

JACKSONVILLE, Fla.--(BUSINESS WIRE)--Availity®, the nation’s leading real-time information network, announces its strategic collaboration with Connective Health, a company focused on empowering ...

Clinical data management is entering a new phase as AI automates EDC build, shortens timelines, and enables data teams to focus on quality.

In the last decade, the volume of clinical trial data has surged, presenting unprecedented challenges for sponsors and contract research organizations (CROs). The task of collecting, cleaning, ...

Clinical research has always been the backbone of medical progress, providing the data and insights needed to develop new treatments, improve patient outcomes, and advance public health. Yet, the ...

By adopting the standard usability practices in The Sequioa Project's USCDI v3 guidance, organizations can improve clinical data quality and enhance patient care, which are essential for innovation.

Quality data is critical to informing public health actions. That’s why every day, state and local health departments analyze and use health system data to protect and promote community health. They ...

A new peer-reviewed study published in the March edition of PLOS Digital Health offers one of the first real-world evaluations of how physicians assess AI-generated clinical content in everyday ...

Physicians, struggling under the pressure of heavy patient loads amidst a national clinical workforce shortage, continue to rank working with EHR systems as the second most challenging part of the job ...

In this video interview, Marc Buyse, ScD, founder and CEO of IDDI, examines the most common threats to trial data reliability, including opaque methodologies, synthetic controls, and the limits of ...