Kaiser Permanente researchers push the envelope with AI and NLP

Although healthcare is squarely in the era of big data and data analytics, it remains difficult in clinical research to accurately identify patients with complex conditions like valvular heart disease through medical records. And if researchers cannot identify these patients, they cannot study them, track practice patterns or conduct population management. Part of the problem is that the current methods used to identify highly specific conditions like valvular heart disease use diagnosis or procedure codes. These were created primarily for billing purposes and often are not very useful for clinical care because they can be quite nonspecific and not include detailed data about the condition. "For example, a patient with moderate or severe aortic stenosis, which is a narrowing of one of the primary heart valves, is entirely different than a patient with mild valve disease," said Dr. Matthew Solomon, a cardiologist at the Permanente Medical Group and a physician researcher at the Kaiser Permanente Division of Research in Oakland, California.