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Location
Zoom - Webinar, 12:00pm - 1:00pm CT
Date
January 25, 2023
With CMS’ launch of the ACO REACH program bringing attention to its focus on improving health equity, reducing health disparities has become an industry-wide priority. Many providers and payers use machine learning algorithms or rules-based systems for population health, clinical decision support, and other decisions that affect healthcare resource allocation. But if these tools aren’t evaluated for algorithmic bias, they can unintentionally make health disparities worse.
In this webinar, ClosedLoop will discuss the importance of evaluating algorithms for bias prior to deployment as well as metrics for assessing bias. We will also demo new features for algorithmic bias evaluation that enable data science teams using the ClosedLoop platform to assess algorithmic bias as part of process for training and validating machine learning models in healthcare.
January 25th, 12:00 - 1:00 PM Central
Speakers:
Carol McCall, FSA, MAAA, MPH
Chief Health Analytics Officer
ClosedLoop
Helen Rickey
VP of Product
ClosedLoop
Joseph Gartner, PhD
Director of Data Science
ClosedLoop
Todd Burkhard
VP of Data Analytics
Medical Home Network
In this webinar, ClosedLoop will discuss the importance of evaluating algorithms for bias prior to deployment as well as metrics for assessing bias. We will also demo new features for algorithmic bias evaluation that enable data science teams using the ClosedLoop platform to assess algorithmic bias as part of process for training and validating machine learning models in healthcare.
In this webinar, ClosedLoop will discuss the importance of evaluating algorithms for bias prior to deployment as well as metrics for assessing bias. We will also demo new features for algorithmic bias evaluation that enable data science teams using the ClosedLoop platform to assess algorithmic bias as part of process for training and validating machine learning models in healthcare.
