Customers are highly satisﬁed with ClosedLoop, who is used by both payer and provider organizations to improve risk scores, decrease readmissions, close care gaps, and reduce claims denials.
ClosedLoop’s platform ━ purpose-built and dedicated to healthcare ━ combines an intuitive end-to-end machine learning platform with a comprehensive library of healthcare-specific models and features. The platform is designed so that healthcare organizations (HCOs) can leverage the power of AI to address their biggest challenges.
Predict the comprehensive chronic and preventive care needs of individual patients with unparalleled precision.
Predict and prioritize high-risk members and use Contributing Factors insights to personalize outreach and interventions.
Strengthen commercial success, gain precision insights into key cohorts, and power digital therapeutics and value-based contracts.
Artificial intelligence (AI) and machine learning (ML) are increasingly used in healthcare to combat unsustainable spending and produce better outcomes with limited resources, but healthcare organizations (HCOs) must take steps to ensure they are actively mitigating and avoiding algorithmic bias.
Implementing a comprehensive strategy to advance health equity is a moral and financial imperative for healthcare organizations (HCOs). Persistent health disparities create preventable suffering and excess costs, are fueled by social determinants of health (SDoH), and consistently disadvantage people of color. Recent studies of racial equity estimate that $135 billion could be saved annually if racial disparities in health were eliminated, including $93 billion in excess costs of care.
COVID-19 simultaneously exacerbated existing health disparities and introduced entirely new ones. The pandemic disproportionately impacted people of color, and due to a combination of persistent health disparities and social determinants of health (SDoH), they are at higher risk for infection, severe illness, and death.
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