Chronic Disease

The human and economic costs associated with chronic disease continue to soar, creating a burden for patients and the healthcare system overall. According to the CDC, six in ten adults in the U.S. have a chronic disease, and four in ten adults have two or more chronic diseases. Heart disease, cancer, and diabetes are not only the leading cause of death and disability in the U.S., they make up 90% of the nation’s $3.3 trillion annual healthcare costs.

Focusing on life-changing resources to either prevent chronic diseases or slow their progression will optimize quality of life and reduce the demand on the healthcare system. Predictive analytics can identify patients at higher risk of developing chronic diseases or in the early stages of their progression. By using this valuable insight, care teams can intervene with personalized programs and services that can help patients avoid long-term health problems that are difficult and costly to treat.

Did you know...


of the nations $3.3 trillion in annual healthcare expenditures are spent on chronic health conditions

$237 billion

is how much diabetes costs the U.S. health care system and employers every year

4 in 10

Adults have two chronic diseases

See How ClosedLoop Can Predict Which Patients Will Develop Chronic Conditions

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Hospital Acquired Conditions & Infections

Annually, approximately 2 million patients suffer with HAIs in the U.S., and nearly 90,000 are estimated to die. The overall direct cost hospitals incur due to HAIs is estimated to be as high as $45 billion annually.

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There were approximately 3.3 million adult 30-day all-cause hospital readmissions in the U.S. in 2011, and they were associated with about $41.3 billion in hospital costs.

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Total Risk

The top 5% of all patients account for 50% of the total U.S. healthcare expenditures. Identify which patients have the highest overall risk in the next 6 months or year.

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Appointment No-Shows

Costing more than $150B a year, missed appointments and late-cancels are a major problem for providers. Reduce scheduling difficulties by identifying patients likely to no-show.

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