Healthcare is grappling with both chronic and deteriorating resource scarcity. At the same time the demand for services is increasing as the population ages. In emergency departments this manifests as recurring crowding which leads to an estimated annual death toll of 50,000 to 100,000 people in OECD countries. New tools are needed to address this crisis. Our research team has developed a forecasting system called Tulva, which can predict the number of patients arriving in the emergency department 24 hours into the future using artificial intelligence. We have published four articles which describe the performance and need for the software. Additionally, we have developed an early prototype of the software and integrated it in hospital databases to perform real-time predictions. This kind of forecasting is common in sectors like retail and industry but applications in healthcare have not emerged. Accurate forecasts would enable operational management to ensure that limited resources are used when they are needed the most which would improve both cost-effectiveness and patient safety. Our method can be applied in hospitals, healthcare centers, and private clinics alike. We are seeking funding to prepare for the commercialization of Tulva with the goal of creating a significant international business. The project aims to explore commercialization opportunities in both the public and private markets, both in Finland and abroad. We will further develop the software's proof of concept and conduct an extensive market analysis to identify key value chains and the most promising market segments.
Funding source
Business Finland: Research to Business funding