The hype around AI is finally translating into real-world value, and we are seeing broader adoption of real-world data in Dermatology. This episode of tHEORetically Speaking features Dr. Stefan Weiss, Managing Director of Dermatology and Dr. Joseph Zabinski, Managing Director of AI and Personalized Medicine at OM1, who discuss the path to personalized medicine and AI-powered clinical decision support in dermatology.
This episode of tHEORetically Speaking features host Meg Richards, Executive Director of Solutions at Panalgo, who speaks with Erik Maul, Senior Director of Data Partnerships at Panalgo about data linkage.
The promise of improving patient care and outcomes through RWD has been understood for some time, but overcoming the fragmentation and inaccessibility of disparate data sources across disease states has proven to be a hard challenge across the industry. We’re not learning fast enough— this is where clinical expert-led AI can help.
By using AI to standardize unprecedented volumes of data, uncover clinical details that have previously been hidden in free text notes, and represent full patient journeys in near real-time, researchers can ask and answer complex questions for targeted populations like never before.
As the volume of the real word evidence data increases, the mechanisms to collect and translate the data into meaningful insights for pharmaceutical organisations becomes increasingly complex. Advances in technologies such as artificial technology have delivered global excitement, but mastering how to leverage AI for meaningful patient outcomes remains uncracked.
Join us as we discuss how the healthcare landscape is changing in technology and clinical trial innovation, including diversity improvement, leveraging real-world evidence, comparative arms, and decentralized clinical trials.
Looking to empower your organizations with high quality patient data? Human abstraction has long been considered the gold standard for extracting high quality information from EHR data. With the rise of NLP, large language models, and machine learning, the question becomes: how should we evaluate these new technologies against the traditional abstraction methods?
Join a panel of OM1’s clinical experts in cardiometabolic disease, immunology, and mental health as they explore how Artificial Intelligence (AI) can find phenotypic patterns and unlock insights hidden in real-world data.
The news that a prominent insurer had decided to cover a digital therapeutic for opioid disorder spurred national headlines recently. In this case, the therapeutic had a breakthrough designation from the FDA. That payer decision underscored the potential as well as the challenges that have arisen around developing and marketing digital therapeutics, which have become a fast-growing segment within digital healthcare. DTx delivers clinical interventions directly to patients via software to treat, manage or prevent disease - ranging from behavioral health conditions to diabetes. We'll take a close look at this burgeoning field and see where we're headed in the years to come.
Hear four experts from ICON and Kap Code provide insights on how to collect, use, analyze, and interpret social media data in different contexts. These experts share knowledge from over fifteen years of successfully developing and adapting algorithms to treat this kind of data.
Correctly identifying a patient with a rare disease can be like looking for a needle in a haystack: by definition, each rare disease has fewer than 200,000 patients out of more than 300M people in the US.
This blog reports practical uses of RWD sourced from the largest, cloud-based electronic health record (EHR) platform in the United States, offered by Veradigm® as part of its Health Insights database.