LTC ACO Selects ClosedLoop’s Data Science Platform to Deepen Accuracy of Predicted Risk


KENNETT SQUARE, PALTC ACO announced it selected ClosedLoop, the leading healthcare data science platform, to provide predictive analytics that will lead to improved health outcomes for its nearly 20,000 beneficiaries nationwide. Using ClosedLoop’s platform, LTC ACO will be able to better predict and prevent costly events by alerting ACO practitioners to events that require their intervention.

“Working with ClosedLoop will help us provide clinicians with even deeper data-driven insights into potential health risks that each member of our patient population faces, allowing us to proactively address health issues before they arise,” said Jason Feuerman, president and CEO of LTC ACO. “Our organization has a long history of making accurate and reliable predictions regarding the cost and quality of care of Medicare beneficiaries. Our relationship with ClosedLoop ensures we continue delivering meaningful and actionable insights to our participants.”

During this multi-year relationship, LTC ACO will use ClosedLoop’s platform and healthcare content library to easily produce highly customized artificial intelligence and machine learning models that incorporate patient data and public social determinants of health data. ClosedLoop will enable LTC ACO to more accurately predict risk for a variety of outcomes, including avoidable hospitalizations, and will provide robust explainability into the contributing factors. Machine learning models will help clinicians continually refine interventions by identifying where they are effective and why. This incremental knowledge makes it easier to target interventions efficiently to improve health outcomes and reduce costs.

“We’re grateful to forge a lasting relationship with one of the country’s top ACOs,” said Andrew Eye, CEO and Co-Founder, ClosedLoop. “From the beginning, it was clear that ClosedLoop and LTC ACO were aligned in their commitment to population health management. The U.S. wastes $1 trillion on healthcare annually due to factors like poor care coordination, overuse of low-value care, and lack of preventative care adoption. Systematically incorporating data science into the decision-making process and shifting to alternative payment models can mitigate this. LTC ACO’s dedication to both of these key initiatives is one of the many reasons why we’re excited to work with them.”

As the healthcare industry rapidly shifts towards value-based systems, there is an acute focus on individuals, prevention, and managing chronic disease. To understand which actions to take and systematically learn from data, healthcare organizations have to go beyond traditional rules-based analytics. ClosedLoop’s predictive modeling tools help organizations like LTC ACO determine which interventions are most effective in order to optimize results and improve health outcomes.

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