Health Plans

Leveraging AI to match treatments and care management to individual members

Total healthcare spending in the U.S. has reached $3.5 trillion with costs now representing 18 percent of the GDP and no slowdown in sight. Fortunately, these escalating costs are driving innovation—new data and technology are giving health plans the opportunity to improve outcomes for patients, collaborate with biopharma and providers, and lower the total cost of care.

Traditionally, health plans have relied on basic statistical methods and rules-based techniques to deliver solutions targeting the “average” patient or populations. But none of us are average so, this approach fails to move the needle when it comes to improving the quality of care or reducing costs.

Instead, health plans are now looking to the robust volume and variety of healthcare data to tailor their care management programs.

Artificial intelligence (AI) provides an opportunity to mine data for insights that can make a significant impact on the individual member level. Health plans have begun to recognize that leveraging AI offers the best opportunity to help improve health outcomes, eliminate spending on ineffective treatments and more effectively match treatments and care management to individual members.

GNS Healthcare’s causal AI platform, REFS™, unlocks the value of traditional and emerging data sources to help health plans rethink their business and the way they deliver care. The GNS causal AI platform, REFS™,provides health plans with a powerful AI capability that helps them address their business challenges in a number of ways.

Innovative Health System Models

One of the biggest challenges facing health plans is evaluating their network and benefits accurately to discover the underlying mechanisms, treatment patterns and care practices that drive performance. The GNS Health System model provides health plans with a method for obtaining key insights around network and benefit design that are crucial to establishing an effective value-based care model.

Intervention Optimization

The GNS causal machine learning platform applies the most advanced form of analytics to claims, EHR, genomic wearable and other data to precisely predict individual risks, revealing the optimal intervention time to provide the best care at the least cost.

The ability to simulate hundreds of thousands of “what if” scenarios helps health plans target individuals for intervention by intervention therapy matching. The process can be applied to multiple diseases and conditions and encompasses rapidly expanding available data sets, greatly improving the accuracy of results. Our pre-built models on metabolic syndrome and advanced illness have helped our clients optimize care plans at the individual patient level.

AI and causal machine learning also enables health plans to accurately view how patient non-compliance affects disease trajectories, compare drugs, and determine the results of delayed treatments.

Value-based Initiatives Support

Our extensive experience in the pharmaceutical space makes GNS unique in its ability to bridge the gap between pharma and health plans and provide novel insights into the effectiveness of therapies in the real world. Our expertise and groundbreaking technology provide unprecedented insights into ways to meet the growing demands of value-based care.

By better understanding what treatments will work for individual patients and WHY, you gain greater transparency into line placement for different therapeutics and can provide compelling causal-based evidence to allow you to confidently make intervention recommendations for individual members.