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Identifying inequities through research and data.
It’s time to re-examine current systems. Milliman applies our deep expertise and analytic capabilities to better understand hidden bias and systemic inequities in healthcare and insurance.
The first step in addressing disparities is understanding them. Milliman uses claims data to reveal key patterns and biases. Learn more about how we are working to overcome systemic inequities in healthcare.
An examination of racial disparities in preventive services for Medicare beneficiaries with type 2 diabetes.
Insurers need to adapt to rising demand for transparency and accountability on how their business practices contribute to potential systemic societal inequities.
We delve into three recent CMS health-equity-focused initiatives, which have significant implications for Medicare Advantage organizations.
While data science techniques offer immense potential for risk managers, (re)insurers need a multidisciplinary approach to tackle challenges and ensure successful implementation.
Now that CMS requires REACH ACOs to measure and address health equity, providers face a steep learning curve with data analysis.
How do responses differ by demographic characteristics?
A summary of available data sources that can assist state Medicaid agencies in evaluating health disparities and measuring progress toward health equity goals
This white paper discusses how to detect bias and build a fair machine-learning model.
This report evaluates the general enrollment Medicare Advantage plans available to individuals of different racial and ethnic groups in the United States.
We tested two prospective diagnosis-based MARA models intended for use on Medicare populations, and found no indication of racial bias.
We’re here to help you break through complex challenges and achieve next-level success.