Six in 10 Adults in the US have a chronic disease. Four in 10 US adults have 2 or more chronic diseases1.

The Partnership to Fight Chronic Disease estimates that by 2030, 83 million people in the U.S. will have three or more chronic health conditions, up from 31 million in 20152.

Chronic conditions are the leading cause of death & disability and a leading driver of US annual healthcare cost. US healthcare costs for chronic diseases such as heart disease, cancer, diabetes, and Alzheimer’s disease totaled $1.1 trillion in 2016. If the lost economic productivity is accounted, the total economic impact was $3.7 trillion. This is equivalent to nearly 20 percent of the US gross domestic product2.

As per CMS estimates, healthcare spending is expected to continue to grow at an average of 5.5 percent through 2025, with chronic disease treatment comprising a major portion of it. Chronic diseases eat up significant healthcare dollars for payers and other health organizations, leaving them with challenges of covering care for patients with these expensive, long-term conditions.

Analytics to drive care value

By 2020, it is estimated that the amount of individual health information will double every 73 days3. Data gathered from structured and traditional sources, IoT devices, and large sets of unstructured big data information can help create new-generation tools that can bring us better insights, dependable recommendations, and real-time feedback.

As care delivery continues to evolve from reactive disease treatment to proactive preventive care, more healthcare organizations are looking at advanced technologies like artificial intelligence and machine learning to assist in drawing actionable items from their big data resources.

Analytics is playing an increasingly important role in risk stratification. For instance, it helps predict which individuals might develop chronic conditions such as diabetes or heart failure. Integrating such actionable insights into payer and provider prevention initiatives, clinician workflow, and patient engagement activities can help raise awareness of risk for both clinicians and patients. It can lead to the recommendations for evidence-based preventative measures to reduce risk.

Healthcare organizations can follow these steps to utilize analytics in chronic care management within their own workflows:

  • Identify the sources of data in healthcare, both internal and external.
  • Apply analytics model to specific healthcare challenges in chronic management, such as managing pre-diabetes and diabetes at the population level.
  • Use observations and actionable insights from analytics to achieve desired care outcomes

Having advance knowledge pertaining to chances of contracting a disease paves the path for effective prevention and improves patient care. Preventing chronic diseases or at least managing symptoms when prevention is not possible can reduce costs.

The ITC Infotech Advantage

ITC Infotech’s Healthcare Insights platform allows payers and providers to leverage big data, analytics, artificial intelligence and machine learning to gain actionable insights for healthcare enterprises.

Improving healthcare is not a singular effort. You need assistance from specialists who can plan a roadmap for you and make the transformation seamless. With our healthcare technology experts, you can make the shift from legacy systems to on-cloud cutting-edge technologies.

Moving toward a connected value care delivery healthcare ecosystem is the need of the hour and we can facilitate the change for you.

Author:

Jeewan Mohta Lead Consultant

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