Issue link: https://beckershealthcare.uberflip.com/i/289185
78 Executive Briefing: Data Analytics Data and risk/value-based contracts Having data and analytics to know where your organization stands amidst the larger universe is key, but it is sometimes just as im- portant to have a good grasp on risk at the individual patient level. That's especially true when managing risk/value-based contracts within ACOs and similar organizations. Risk-bearing providers are acquiring more advanced care man- agement strategies and an ability to build better predictive risk models for high-risk populations. Baylor Quality Alliance uses a predictive modeling system to better predict readmissions and segment populations to improve overall care management. "In the United States, $1.35 trillion is the cost of care for 5 percent of the population, and they need special attention and resources applied to them," said Dr. Couch. "You don't know how to do that until you know who they are. That's where good predictive models come in." For example, Dr. Couch stated, an organization may be aggres- sively treating a cohort of diabetics. Without predictive modeling data, physicians may not know that half of them are depressed, which may lead to worse outcomes. Knowing this, he added, al- lows physicians and case managers to get those patients the mental health services they need. By doing so, those patients may be less likely to be readmitted. "That is generally not dealt with in any other way other than the analytic systems that can help identify those patients and their specific medical conditions," Dr. Couch said. Using analytics, care coordinators can reach out to patients to ensure they're seeing their physicians, taking medications, com- municating with all of their care providers and understanding the different instructions they may get from multiple providers. Predic- tive modeling analytics allows organizations such as Baylor and San Francisco-based Brown and Toland medical group to recon- cile discrepancies and enhance care. While clinical analytics can help organizations identify clinical population and patient risk, organizations also need to know the details around their financial risk. This need calls for sophisticated predictive models that account for the health of an organization's patient population. Episode grouper technology — the same tech- nology payers use to aggregate and assess data — is useful in this area. Using claims data to analyze past expenses combined with a disease knowledge base, groupers can apply advanced risk analytics to show organizations the cost of caring for a group of patients in the coming year. Such information is invaluable for budget and staff planning. Build better care systems on better data It all starts with data — real world data that can be applied to im- prove patient outcomes and remove unnecessary costs. For health- care, real world data requires, at minimum, the integration of clini- cal and claims data to reflect what actually happens in healthcare environments. And by applying advanced analytics to such broad, inclusive data sets, providers will have a sharper lens with which they can analyze the inner workings of their systems. They can see what's working, what's not working, what it costs and whether it could be more efficient. Data allows them to better understand their populations, then tailor the care they provide to suit patient needs. Applying advanced analytics to comprehensive data will reveal to providers things they don't know and help them more fully un- derstand the risks and uncertainty associated with providing care. Analytics will help providers better calculate difficult decisions and prompt them to ask questions that they never thought to ask. Successful organizations will embrace the unknowns their data uncovers and ask what they can learn. Providers want to know what they don't know, and they are us- ing analytics to gain that knowledge — knowledge they need to improve, manage and succeed in today's dynamic, value-based healthcare market, as well as prepare for tomorrow's challenges. n 1 Data from Humedica statistically de-identified common data repository "Episode grouper technology — the same technology payers use to aggregate and assess data — is useful in this area. using claims data to analyze past expenses combined with a disease knowledge base, groupers can apply advanced risk analytics to show organizations the cost of caring for a group of patients in the coming year." 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