When we entered the MD, PhD program at Vanderbilt University in 2009, we had no idea our lives would take a dramatic turn, but here we are, running an Artificial Intelligence company to improve patient care.

So how did we go from wanting to practice medicine to building machine learning models? It all started in our medical rotations where it very quickly became clear to us that there was a huge gap in the way technology was being utilized to streamline the clinician workflow and integrate patient data. EHRs were clunky and required clinicians to spend hours per day on their computer charting instead of focusing on patients. This was creating major provider burnout and time constraints on an already overly taxed healthcare system. We also saw that administrators and clinicians did not have visibility into the performance of their practice. The key metrics that could help optimize practice efficiency and patient care were limited as much of the valuable information was locked away in the free text charts. Not to mention, medicine is dense with information. The future of medicine needs the mountain of information to be processed and presented to the clinician's of tomorrow in a way that's timely and thoughtful.

We knew there had to be a better way, so we started PredictionHealth. Our AI-assisted documentation service solves the burden of clinical documentation while also capturing data to help us build models that can make predictions by collecting and organizing medical information. Our Practice Intel dashboards help optimize your practice performance by leveraging structured and unstructured data points to provide actionable guidance. We envision a smarter healthcare system that creates outstanding, efficient patient care and we believe the best way to create this vision is to seamlessly integrate Artificial Intelligence into routine clinical care.

-Pedro and Ravi