Tag Archives: care management data

10 tips for working with MCOs to advance Medicaid program integrity

Have you turned to managed care organizations (MCOs) to reduce Medicaid costs and improve patient care? If so, you probably know how difficult it is to know for sure whether your MCOs are doing all they can to reduce fraud, waste and abuse. In May 2015, CMS proposed a new rule that MCOs strengthen their […]
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Better predictive modeling requires bigger, more varied, higher quality data sets

In a previous blog about predictive analytics, we discussed how comprehensive health care data is necessary for a high degree of prediction. In this post, we’ll discuss the variables that increase predictive accuracy. The larger the better. As the sample size of a predictive model grows, the model’s uncertainty level and degree of bias decreases. […]
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The power of prediction: Sentara Medical Group puts predictive analytics into action

In my most recent post, I wrote about usability factors in predictive analytics. In today’s post—the final post in the predictive analytics series—I’ll share an example of a provider that put all the predictive pieces together to transform its population health management program. Sentara Medical Group uses predictive models to identify high-risk patients, particularly those […]
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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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The power of prediction: Predictive accuracy depends on data set size, sources and quality

In my last blog post, I wrote about how predictive analytics needed comprehensive health care data to have a high degree of prediction. In today’s post, I’ll dig deeper into the variables the increase predictive accuracy.