Tag Archives: risk stratification

Sentara Medical Group puts improved predictive modeling into action

In a recent post, we discussed usability factors in predictive analytics. Today’s final post in the predictive analytics series will discuss an example of a provider that has used prediction to inform its population health management program. Predicting hospitalizations helps Sentara practice proactive care. Sentara Medical Group has 380 primary and specialty care physicians in […]
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Today’s predictive analytics should provide timely, actionable intelligence

In a previous post on predictive analytics, we discussed the variables that determined predictive accuracy. Today’s topic is usability of predictive results. Old news is only good for wrapping fish. The point of prediction in health care is to head off bad outcomes before they happen. So for predictive usability, data must be timely. In […]
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The power of prediction: Predictive analytics need to provide timely and actionable intelligence

In my last post, I wrote about the variables that determined the accuracy of predictive models. Accuracy, however, is only half of the equation. The data also must be usable; that’s today’s topic. Timeliness is a critical aspect of usability in predictive analytics. For a provider to deploy predictive modeling in their organization, their own […]
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Data analytics optimize providers’ management of value-based contracts

Providers who manage value-based contracts are looking for ways to improve clinical outcomes and reduce costs. And they’re doing this by acquiring care management strategies and an ability to build better predictive risk models for high-risk populations. With a just small sliver of the U.S. population accounting for a bulk of health care costs, provider […]
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Analyzing “good” data provides a true snapshot of patients’ risk

Analyzing your data can reveal important insights about your patient population, including identifying those who are at highest risk for hospitalization. In my last post, we discussed the importance of having “good” data. This means data that has been gleaned from as many sources as possible, and has been normalized and validated so that it […]
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Data and analytics support one IPA’s risk-based business

In our last blog, we talked about how AppleCare Medical Group, an independent practice association in California, is helping manage patient risk by making sure its physicians are happy. Engaging physicians and keeping them on board as you move to risk-based reimbursement is a must, said AppleCare’s Surendra Jain, MD. Physicians will participate, he said, […]
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