Tag Archives: Predictive analytics

Is a provider-led health plan a good fit? Evaluate 6 areas to find out

To drive down costs and improve care through value-based models, one must have a deep understanding of the population they serve. Health care providers have this knowledge. Their familiarity with the demographics, economics and general needs of their communities means some are well-positioned to launch their own provider-sponsored health plans (PSHP) and have a sense […]
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3 categories of non-clinical factors lead to readmissions

Failure to follow up with a physician or follow a medication regimen can cause a recently released patient to end up right back in the hospital. But there are other, non-clinical factors that also lead to readmissions. The causes can be grouped into three main categories: Patients’ medical literacy According to the National Network of Libraries […]
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In healthcare, real time isn’t always soon enough

Analytics platforms that provide insights immediately after data is collected can help physicians and care managers make the most of their time with patients. Real-time data integration allows care teams to engage patients closer to the point of care and make decisions on next steps. But in some cases even data accessible in real time […]
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Data-driven collaboration and teamwork

“The team! The team! The team!” Even as a dyed-in-the-wool Ohio State fan, I can still appreciate these six words spoken by Bo Schembechler, the famed coach of the University of Michigan (which we Buckeye fans like to refer to as “That team up north.”) His great speech is inspiring, even if you’re not a […]
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New technologies are breaking down data silos

The highest quality data does no one any good if the information is locked up in silos, unable to be shared. Now the tools of health care are changing in a way that will allow data to be accessed and analyzed. Electronic Medical Records (EMRs) and Health Information Exchanges (HIE) represent two of the top […]
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Getting behind the science: Program integrity, predictive analytics and best practices

Whether you pluck the petals from a daisy or gaze into a crystal ball, the traditional means of predicting and influencing future events has always carried a high degree of risk. Fortunately, when it comes to analyzing claims data, there are proven methodologies —predictive analytics — that states can use to help assess the validity […]
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Peer into patients’ and populations’ futures with predictive analytics

Predicting the future. It’s the stuff of fantasy and metaphysics—seeing clearly what will happen and making bold decisions based on that future vision. But prediction is also part of our day-to-day lives. We rely on weather reports to predict temperature, precipitation and other environmental conditions. We count on credit card companies to predict how we […]
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Trusting predictive analytics

Most likely, the last time you purchased something online you were offered “recommendations” or saw what “others also liked.” The technology behind these common prompts uses predictive analytics. Your online merchant is leveraging data about your shopping and online searching behavior to predict their desired outcome — that you might buy something else! As we […]
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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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