The Future of Clinical Trial Matching is Digital

Discussion Topics:

Matching patients to clinical trials, especially as close to the initial diagnosis as possible, may have a critical impact on patient outcomes. Yet, due to a largely manual, time-consuming, and error-prone process, many healthcare institutions experience significant inefficiencies in that area.

An increasing number of hospitals and health systems are setting their sights on new technology, such as Artificial Intelligence (AI) and Natural Language Processing (NLP), to streamline this process. They are starting to uncover additional hurdles that may need to be resolved before fully automating clinical trial matching.

While some of these hurdles relate to the accuracy and reliability of the underlying technology driving this automation, other challenges fall more on the behavioral side and relate to clinicians’ willingness to adopt AI systems.

This virtual event featured several experts with significant experience in the oncology clinical trials space. Key topics of the discussion included:

What are the main workflows that a clinical trial matching solution should and can automate?

What are the key benefits of applying technology to automate clinical trial matching?
- How can automation help healthcare organizations identify and enroll more patients from under-represented groups?
- How can a more efficient and effective clinical trial matching process lead to better patient outcomes and satisfaction?
- What can technology do to prevent staff burnout, empower Research departments, and improve healthcare organizations' reputations?