LAS VEGAS – IBM has launched a new technology designed to extract relevant clinical information from unstructured data. Based on the same natural language processing technology used in IBM's Watson, its new Content and Predictive Analytics for Healthcare is aimed at preventing patient readmissions.
Austin, Texas-based Seton Healthcare Family is the first client to adopt and use the technology. Officials say it will enable clinicians to glean relevant knowledge from troves of patient data – helping "analyze the past, understand the present and predict future outcomes."
By combining IBM's Watson technology with industry solutions offerings, Seton plans to focus the new content and predictive analytics solution on the root causes of hospital readmissions, and ways it can decrease preventable multiple hospital visits.
[See also: IBM's Watson is far from elementary.]
One in five patients suffer from preventable readmissions, according to the New England Journal of Medicine – representing $17.4 billion of the current $102.6 billion Medicare budget. Beginning in 2012, however, hospitals will be penalized for high readmission rates with reductions in Medicare discharge payments.
Charles J. Barnett, president and CEO of Seton Healthcare Family, says the Watson-based technology will allow his organization to "leverage our unstructured information in new ways not possible before.”
He adds that with the technology, "we can access an integrated view of relevant clinical and operational information to drive more informed decision making. For example, by predicting readmission candidates, we can reduce costly and preventable readmissions, decrease mortality rates and ultimately improve the quality of life for our patients.”
More than 80 percent of healthcare data today is unstructured – in the form of physician notes, registration forms, discharge summaries, documents, etc. Moreover, that data is doubling every five years.
And since it's arduous for healthcare enterprises to include business analysis, it's often left out – with millions of patient notes and records sitting unavailable in separate clinical data silos.
[See also: IBM, Nuance to apply 'Watson' analytics to healthcare.]
Officials say IBM Content and Predictive Analytics for Healthcare enables doctors and healthcare professionals to go far beyond traditional search and analysis of unstructured data. They can advance diagnosis and treatment by accurately extracting medical facts and understanding relationships buried in large volumes of clinical and operational data. The IBM solution transforms raw information into healthcare insight quickly by revealing trends, patterns, deviations and predicting the probability of outcomes, allowing organizations to derive insight in minutes versus weeks or months, or not at all.
As a result, healthcare professionals can find more effective ways to care for high-risk patients, provide safer patient care, and develop new models for reimbursement for quality care.
The new technology is compatible with IBM’s Health Integration Framework, which helps healthcare organizations realize more value from existing information system investments, such as data warehouse, business intelligence, master data management and advanced case management.
