Category: Johns Hopkins

Flagging Fragmented Care – Risk Stratification Analytics Part 9

We all know health care is fragmented, especially for those with higher medical needs. When you are trying to control costs and improve the health of your patients, you need the right information to understand who needs your services the most. It’s not enough to just focus on patients with a certain condition or rely…
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Preventing Hospitalizations – Risk Stratification Analytics Part 8

What are some of the more difficult parts of your population health efforts? Perhaps it is team members spending more time on aggregating data rather than working on improvements. Or maybe it is not about time but quality as you are not able to get the right kind of data, like being able to proactively…
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The Johns Hopkins ACG® System

How KPI Ninja, using the Johns Hopkins ACG System, provides integrated, advanced, comprehensive analytics to Health Information Exchanges (HIEs) and health care providers. The HIE Landscape HIEs make important connections between health plans, hospitals, private practices, providers and public health. They integrate large amounts of vital patient data and make key pieces available for sharing…
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Identifying Frailty – Risk Stratification Analytics Part 7

Frailty, while sometimes referred to as the normal aging process, is not always seen in geriatric patients. Rather, frailty as part of risk stratification is defined as a set of health characteristics that are associated with poor health outcomes, no matter the age. While there is no standard definition or formal diagnosis of frailty, identification…
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Making Laboratory Data Useful for Population Health Efforts – Risk Stratification Analytics Part 6

Providers are familiar with using laboratory test results to assist in the diagnosing and monitoring of a patient’s health condition. Performing this work for an entire population is challenging, as providers and care teams simply do not have time to jump from system to system to review test results, reconcile it with other health data…
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