IBM Content and Predictive Analytics for Healthcare How it works Unstructured Data (Nurses notes, discharge notes, etc.) Structured Data (Billing data, EMR, etc.) Raw Information Search and Visually Explore (Mine) Monitor, Dashboard and Report Question and Answer* Custom Solutions Dynamic Multimode Interaction IBM Content and Predictive Analytics Content Analytics Natural Language Processing Medical Fact and Relationship Extraction (Annotation) Trend, Pattern, Anomaly, Deviation Analysis Predictive Analytics Predictive Scoring and Probability Analysis Analyzed and Visualized Information Health Integration Framework Data Warehouse and Model Master Data Management Advanced Case Management Business Analytics Partners (HLI) Specialized Research IBM Watson for Healthcare Confirm hypotheses or seek alternative ideas with confidence based responses from learned knowledge* Key Points to Make Explain the components to ICPA (see slide) Explain the flow of information from left-to-right Start with Raw Information, both structured and unstructured Explain how the ICPA transforms raw information into analyzed information though multiple analytics services Content Analytics Natural Language Processing Medical Fact and Relationship Extraction Trend, Pattern, Anomaly, Deviation Detection and Analysis Predictive Analytics Predictive Scoring and Probability Analysis In the future, we’ll add Watson services to enable deep question answering from trusted knowledge sources Analyzed information is surfaced to all knowledge workers (executives, clinicians and operational roles) Users are able Search and Explore (Mine), Monitor and Report and Question and Answer (future) Analyzed Information (Insights) can leverage master patient information systems and exchanges It can also be delivered through custom solutions .. or through other systems such as: Data Warehouses and Business Analytics systems Advanced Case Management systems All built on a proven Health Integration Framework 1 * Future optional capability 1 1 1