“If AI-related technologies can help match real people to the unique needs of trials, doctors, nurses, and others can spend more time connecting one-to-one with potential trial participants, reaffirming the human connections that can be drowned out by paperwork and data input.” -The Health Care Blog
COVID-19 has taken devastating effects on cancer treatments and clinical trials. With people too nervous to leave home, the number of cancer screenings dropped by almost 90% in the peak of the pandemic. Many cancer centers are changing gears to focus on programs that will generate revenues for expansion or break, preventing permanent community center closures.
Clinical trials are costly, and patient-trial matching requires clinical coordinators, physician investigators, and research support staff to spend tedious hours combing through disjointed patient records. With new technology, however, cancer centers can optimize screening methods to save research teams critical time and effort. Patient-trial matching technology not only helps to predict and protect future revenue streams but also provide oncologists with viable and cutting-edge trial options for patients.
Learn more in this article from The Health Care Blog, featuring Dr. Tandy Tipps and Brenda Noggy from the Inteliquet™ team, about taking a smart data-driven approach to clinical trials in the upcoming post-COVID reset.
Inteliquet on the Oncology Learning Network Podcast: Highlighting Inteliquet’s Determined Efforts Through the COVID-19 Landscape
PART 1: Not All Oncology Real-World Data is Created Equal
Health IT Answers: Extraordinary Patient Matching Could Turn Around Clinical Trials in 2021