Empowered Patient Podcast Applying Clinical Natural Language Processing to Precision Medicine and Population Health with Dr. Calum Yacoubian IQVIA
Dr. Calum Yacoubian, the Director of NLP Healthcare Strategy for IQVIA, is applying clinical natural language processing to take complex, unstructured healthcare data and turn it into structured and searchable information. In a value-based care environment, clinical NLP can augment manual work by nurses, clinical coders, and clinicians to identify relevant, often unstructured information at the right time for specific patients, and payers to undergo chart review for risk adjustment.
Calum explains, "Within healthcare, data and information are hugely fragmented. There was a HIMSS report in 2020 that said the average healthcare system in the U.S. has 15 disparate EMR systems it is pulling data from. Going back to your first question, the 360-degree view of a patient is about using as much data as available to understand patients and the populations they exist in. If it's difficult to access and make the most of the data. That's the first and probably one of the biggest barriers that we have in healthcare, this disparate data that exists in the ecosystem, and the multiple different formats that it exists in."
"In the healthcare setting, huge amounts of clinical information is in text form, either dictated and transcribed or typed directly by clinicians into the free text boxes. These have become the kind of dumping ground for much clinically relevant information in a clinical setting. When we think of that data, clinical NLP, which is specifically my focus, we are able to look into that data to understand the nuance of that information and to pull out information and data in a structured format in a way the provider or the nurse or the physician or one of the other allied health professionals intended when they were interviewing the patient and documenting it in the medical record."
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