IBM Watson Improves Transitions of Care for High-Risk Patients
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IBM Watson Improves Transitions of Care for High-Risk Patients

It is hard to believe we are less than a month away from #HIMSS18, where the world connects for health. This years conference will take place at the Sands Expo and Convention Center in Las Vegas, March 5-9.

At this year’s event, I will be co-presenting a session with Jennifer Kotwicki, Director of Operations, BayCare Health System. The session titled Improving Transitions of Care for High-Risk Patients, will showcase how BayCare Health System is innovating with natural language processing to manage its Hospital Readmissions Risk and address MS-DRG bundled payments. BayCare will share its journey through a successful proof-of-technology to reduce COPD readmission risk, and its plans to deploy a similar approach to address additional patient conditions. The session takes place Thursday, March 8th at 10:30 AM in Theater B, at the IBM Booth #6243.

80% of health data is virtually invisible in current health information systems and absent from data analysis, because it is stored as blobs of text in an EMR or in a diagnostic report, and cannot be easily mined to drive meaningful insights and learning. During our session, you will hear how IBM Watson unlocked this valuable clinical data to aid in evidence-based decision-making at the point of care.

The need for timely case management interventions and effective care transitions from hospital to home for moderate to high-risk patients is a key goal for health systems today. A task that is often made more difficult, due to the fact the data needed to inform a timely predictive diagnoses and care plans for patients with chronic diseases (for example Chronic Obstructive Pulmonary Disease (COPD), is often hidden in physician notes, family history narratives, or discharge summaries.

Text-based notes in the patient record or embedded in reports contain a rich amount of untapped information, that when mined, can surface previously unseen comorbidities, demographics, and other social determinants of health along with psychological, behavioral and economic insights. Harnessing the power of Watson’s Natural Language Processing (NLP) capability, provides us the ability to surface symptoms, diseases and disorders, compound procedures, medications, demographic and social factors previously unavailable from structured data in a Cerner EHR.

The number of use cases that NLP is able to address is mind boggling, and extends to such things as enhanced patient stratification, improved clinical documentation, and the ability to predict outcomes and financial risk to name a few.

Perficient’s healthcare leadership team will be at HIMSS and we would be happy to share our real-world experience with Watson, AI and Natural Language Processing. Stop by and see us at booth #2671.

Looking forward to seeing you in Las Vegas!

Chief Strategist, Health Sciences, Perficient

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