Smarter Is: Predictive, Preventive Healthcare
Clinical data warehouses turn information into smarter treatments
Johnny’s doctor is stumped. In this small-town hospital, she’s never seen these symptoms before, and the nearest specialist is 200 miles away. There’s no immediate danger, but how can she hone in on the problem, choose and conduct the right tests, and get a treatment plan—especially one the insurance payer will approve?
Getting a handle on healthcare costs is one of society’s greatest challenges. In 2007, USD2.2 trillion was spent on healthcare,1 and that figure is expected to grow steadily while quality of care continues to vary dramatically. Applying information technology to the problem has been a difficult task, even though some of the purely administrative benefits are easy to imagine. But what if we use healthcare data to improve decision making across the entire provider organization?
IBM partner Convergence CT, a clinical data warehouse provider, is one of the leaders in making this “what if ” a reality. Working together with IBM, they have combined IBM® InfoSphere® and IBM Cognos® technologies with healthcare expertise to create IBM InfoSphere Clinical Analytics, a pre-integrated clinical data warehouse. With preloaded data definitions for industry standards, predefined performance indicators, and prebuilt analytics, the warehouse gives providers a sophisticated tool that would take IT and medical specialists enormous amounts of time to create independently.
Seventy-five person-years of expertise and construction have gone into building a heuristic model of clinical analytics. The warehouse captures data from multiple sources, cleanses it, and stores it, performing more than 900 data validations to ensure that the data can be trusted.
IBM® InfoSphere® Clinical Analytics also addresses an important requirement of any healthcare IT project or solution: helping medical staff focus on healthcare duties instead of on data management. For example, predesigned dashboards and data cubes help staff track surgical outcomes and analyze benchmarks for practice management and clinical performance. Meanwhile, reports that automatically comply with—and document compliance to—privacy regulations help take the compliance burden off medical practitioners. Instead of forcing a nurse with patient responsibilities to maintain data quality and anonymity standards, the reports and applications take care of it.
The equations are simple. For the hospital, research facility, or medical practice:
server + data management software + clinical models = ready-to-use tools
And for the patient:
predictive + prescriptive = better health outcomes