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GCN : February 2015
24 GCN FEBRUARY 2015 • GCN.COM BY BRIAN ROBINSON The use of big data to rapidly analyze costs, understand public behaviors and anticipate security threats continues to attract the interest of government agen- cies that see the technology as a way to gain measurable insights into their most demanding problems. Nowhere are researchers more active in exploring the uses of big data than in government health care organizations, where data scientists are working toward creating reliable tools for predicting a pa- tient’s risk of disease or a virus’s path of infection. To some extent health care programs are an obvious target for big data invest- ment. Agencies already have large data- bases with years of information on diseas- es and patient health, and they have an urgent need to provide better and more productive information for researchers, doctors and nurses. The Veterans Health Administration (VHA), for example, has created several big data analytics tools to help it improve health services to its 6.5 million primary care patients. The VHA’s care assessments needs (CAN) score is a predictive analytic tool that indicates how a given veteran com- pares with other individuals in terms of likelihood of hospitalization or death. The scores are analyzed by VHA’s patient care assessment system (PCAS), which uses these scores and other data to help medical teams coordinate patient care. The technology has changed the whole approach at the VHA from being purely reactive to one in which patients at the highest risk of being hospitalized can be identified in advance and provided services that can help keep them out of emergency rooms and other critical care facilities, according to Stephan Fihn, di- rector of the VHA’s Office of Analytics and Business Intelligence. While still considered fairly rudimen- tary tools, the CAN score and PCAS dem- onstrate that big data predictive analytics can work for large populations. The agency now needs to “markedly ramp that effort up,” Fihn said, and to that end the VHA is working on dozens of predictive models that can be deployed over the next decade. The models will show patients that “this what we know about you, here’s what we think you need,” he said, and be able to do that in a rapid, medically relevant manner. Government agencies are making strides testing uses of big data to predict risks of disease or the path of a killer virus, but hurdles remain, including linking legacy datasets and setting up common vocabularies. Big DIAGNOSING 0215gcn_024-027.indd 24 2/2/15 9:52 AM