Rohan D’Souza is the Head of Product at KenSci. Rohan is accountable for driving the innovation and product strategy in bringing machine learning solutions to some of the largest and most prestigious health systems in the world, aligned to achieving the quadruple aim of healthcare. KenSci has pioneered a suite of machine learning models that are tuned to indicators that improve operational efficiencies, clinical quality, and financial profitability on a highly scalable, elastic cloud framework. Prior to joining KenSci, Rohan was instrumental in building an industry leading population health solution at eClinicalWorks from the ground up. With over 100M patient’s data flowing through the platform, he helped some of the largest and most successful ACO’s in the US to understand opportunities within their data and build intervention strategies to drive change. He is also a leading voice for the open health data initiative and was responsible for pushing the agenda on EMR systems adopting an open API framework for healthcare interoperability. Rohan graduated from the University at Buffalo with a double degree in Biological Sciences and Business Marketing, focused on the intersection of health policy with biostatistics. His research helped guide the University at Buffalo to become the first public University in the state of New York to go completely tobacco free.
Healthcare leaders today are faced with increasingly complex and unprecedented challenges. With COVID-19 taking the world by storm, the need for an intelligent system of insights that can proactively deliver actionable and real-time knowledge on patient populations is imminent to providing better care. Multiple Health systems across the country, such as Indiana University Health, are turning to technology and leveraging investments in Data & AI to adapt to the need for readiness, preparedness and response to the rapid surge in patient volumes.
KenSci recently launched a Realtime Command Center for COVID-19 Response to support our customers during these challenging times. This solution converts near-real-time (NRT) messages like HL7 (ADT, ORU, ORM etc.) into a single common data model using the FHIR specification and provides health systems a real-time view into bed management and capacity planning along with important insights like overall ventilator use, surge projections and discharge planning insights. The Realtime Command Center is deployed on top of the existing KenSci Platform and infrastructure, built on Azure Databricks. Join this session to hear about how prior investments in Data & AI have enabled Indiana University Health to rapidly extend its pre-existing infrastructure and self-service offerings to react to the need for COVID-19 focused dashboards and insights. During this session, you will learn: