Facing an unprecedented global crisis, our client needed a novel and data-driven approach to predict which counties would be most impacted by the COVID-19 pandemic in order to appropriately deploy their personnel and equipment to the most at-risk locations. Valkyrie created a custom data-driven system to help our emergency transport client predict which counties would be most impacted by the COVID-19 pandemic, in order to appropriately deploy their personnel and equipment to the most at-risk locations.
We developed over 600 models predicting hourly and daily demand for medical transports by integrating both publicly available and internal client data into our models that forecasted COVID-19 cases, deaths, and transports. We routed the results of our models and related data visualizations into an internal dashboard for decision makers in charge of deploying medical assets.
Our scientists were able to improve the accessibility, visibility, and contextualization of approximately 30 of the client’s operational and medical KPIs, by unifying medical, operational, and financial data from numerous databases and by building data visualization tools to display the metrics and insights.
Our data-driven system allowed the client to identify and visualize which counties would be most severely affected by the spread of COVID-19 in order for them to deploy their first responders. We improved on the accuracy of the client’s existing ambulance demand forecasting models by 15%, which translates to a significant improvement in ambulance deployment efficiency and on-time performance. Our scientists were able to equip our client with actionable insights from their data that informed critical decisions concerning the health of millions of people and their own front line health personnel.