Stigma and discrimination within health care and public health institutions continue to deny people access to fair, culturally safe, and affirming care. Health and biomedical informatics can aid in understanding, detecting, and reducing stigma and discrimination in health care and public health. Panelists will draw from studies with multiple marginalized populations (e.g. African Americans, LGBTQ+, patients with stigmatized illnesses) and digital tools (e.g. Twitter, patient portals, electronic health records, electronic wearable devices, sensing technology). We will discuss how stigma and discrimination can negatively impact the adoption and use of digital health technologies, be enacted through the collection, use and analysis of health-related data, and be detected through emerging informatics methods (e.g. natural language processing and machine learning) and socio-technical strategies. Critically, we will discuss how health informatics can be part of addressing stigma and discrimination at individual, cultural, and institutional levels to promote fair, culturally safe and affirming care.