Microaggressions are pervasive in daily life, including in undergraduate and graduate medical education and across health care settings. The authors created a response framework (i.e., a series of algorithms) to help bystanders (i.e., health care team members) become upstanders when witnessing discrimination by the patient or patient's family toward colleagues at the bedside during patient care, Texas Children's Hospital, August 2020 to December 2021. Similar to a medical "code blue," microaggressions in the context of patient care are foreseeable yet unpredictable, emotionally jarring, and often high-stakes. Modeled after algorithms for medical resuscitations, the authors used existing literature to create a series of algorithms, called Discrimination 911, to teach individuals how to intervene as an upstander when witnessing instances of discrimination. The algorithms "diagnose" the discriminatory act, provide a process to respond with scripted language, and subsequently support a colleague who was targeted. The algorithms are accompanied by training on communication skills and diversity, equity, and inclusion principles via a 3-hour workshop that includes didactics and iterative role play. The algorithms were designed in the summer of 2020 and refined through pilot workshops throughout 2021. As of August 2022, 5 workshops have been conducted with 91 participants who also completed the post-workshop survey. Eighty (88%) participants reported witnessing discrimination from a patient or patient's family toward a health care professional, and 89 (98%) participants stated that they would use this training to make changes in their practice. The next phase of the project will involve continued dissemination of the workshop and algorithms as well as developing a plan to obtain follow-up data in an incremental fashion to assess for behavior change. To reach this goal, the authors have considered changing the format of the training and are planning to train additional facilitators.