Studies show that fewer than 5% of cancer patients are enrolled in any type of research study or clinical trial according to a research paper titled “Creating and Evaluating Chatbots as Eligibility Assistants for Clinical Trials: An Active Deep Learning Approach towards User-centered Classification” https://lnkd.in/d8_mScTG

To address the issue of low participation rate, researchers, Chuan and Morgan (University of Miami) show that chatbot can help patients determine their eligibility via interactive, two-way communication.

”The chatbot is supported by a user-centered classifier that uses an active deep learning approach to separate complex eligibility criteria into questions that can be easily answered by users and information that requires verification by their doctors.”

Based on available clinical trial eligibility criteria collected from the National Cancer Institute's website, the results indicate that the participants who used the chatbot achieved better understanding about eligibility than those who used only the website.

”Furthermore, interfaces with chatbots were rated significantly better in terms of perceived usability, interactivity, and dialogue."

At #TrialValue, we're in the lab building a new solution to enable participants/ patients and clinical research partners, improve engagement efforts around financial decision making when designing and planning clinical research and RWE programs. #Tripp will be ready to assist you soon.
#TrialValuePatientFinancialsNavigator, #Solving4ZeroPatient_Burden