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 and Medical Home Network 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.

Watch the webinar on demand.