Dive into the Digital Divide, both as an effect and a cause. Let’s look expansively at how our digital divide was created, characterize the patient experience across employment/income, primary language, age, geographies, etc and the consequences on direct patient care, and then zoom out to explore the compounding consequences of that digital divide on scaling technologies, such as in the representation of these populations in training data for algorithmic tools. This both sets the stage for systems to think about how to customize their potential digital health expansion plan to their respective patient populations, as well as offer tangible precautions around how this feeds into the biases towards poorer performance in algorithms that may be leveraged against the same populations.