Health Research Scientist Beacon Health Options Rocky Hill, Connecticut
As governmental and private organizations have increasingly recognized racism as a public health crisis, addressing health disparity has never been more important. Recent research has demonstrated that the very data-driven processes that are commonly used in health care to mitigate bias in human decision making, may actually magnify and perpetuate existing disparity based on race and ethnicity. Explore the successful efforts of one state to develop an algorithm that mitigates bias in selecting vulnerable populations for participation in a housing program for Medicaid recipients who are homeless.
Learning Objectives:
Educate attendees regarding the risks and associated harms of introducing bias into algorithms used in behavioral health programming.
Demonstrate how to evaluate or test for the existence of bias in data driven decision making and healthcare algorithms
Describe the do's and don'ts of developing bias free data driven decision making and algorithm development or how to correct for bias in existing processes.