Among the many needs brought to light through this pandemic, access to accurate, updated data has never been more important. In addition to problems with gathering data through testing and contact tracing, there's another, equally important challenge: processing and acting on this data. As The New York Times reports, COVID-19 data is getting trapped in a bottleneck caused by inefficient reporting, non-standardized processes, and archaic technologies still in use, like the fax machine. As the executive director of the Harris County Public Health department said, "The data is moving slower than the disease."

Of course, these challenges are not unique to the COVID-19 pandemic, or even public health data. For too long, the U.S. health care system has defaulted to an old-school, reactive approach to medicine and wellness, largely due to the lack of access to the data and technology needed to generate predictive insights. Risk factors, population health trends, potential comorbidities, and even cost mitigation opportunities have gone largely unnoticed because the majority of our data is difficult to use and lagging by months. Until now, predictive insights have been rudimentary at best, due to challenges like poor interoperability, disparate data sources, and a lack of true analysis and intelligence.