Category Archives: by Jeremy Orr, MD, MPH

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.

The power of prediction: Predictive analytics help providers accurately identify high-risk patients

Readers of my blog posts have probably noticed an ongoing theme: Organizations taking the journey from volume to value need to apply advanced analytics to data to be able to manage risk and make the most out of value-based care. Over my next few blog posts, I’ll stick with that theme, with my focus on […]
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Using advanced analytics to improve quality and cost for COPD patients

Patients with chronic obstructive pulmonary disease, or COPD, represent a huge chunk of the nation’s health care costs. In 2010, COPD-related costs totaled $49.9 billion, including $29.5 billion in direct health care expenditures, $8 billion in indirect morbidity costs and $12.4 billion in indirect mortality costs. It is a major cause of hospitalizations in the […]
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Better knowledge of your patients can lead to higher quality care

Congestive heart failure is a major source of health care costs in the United States. About 5.1 million people in the United States have the disease, costing the nation an estimated $32 billion each year. But providers can and should make a difference in the care of CHF to reduce not only costs but harm […]
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Predict the future: Are your hypertension patients at risk of complications?

Hypertension affects millions of Americans, increasing their risk for other health problems such as heart disease and stroke. The leading cause of visits to the doctor, hypertension costs $156 billion annually in health care services, medications and missed days of work.

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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Predict the future: stratify patients by risk to more effectively coordinate care

As organizations take on more risk, both clinical and financial, they are looking for ways to improve the quality of the care they provide and reduce costs. Population health management (PHM) with a strong emphasis on advanced analytics is one strategy for getting there.

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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