Researchers develop risk adjustment model for elderly

Researchers have developed a so-called risk adjustment model to predict how often elderly people seek treatment in a healthcare centre or hospital.The results suggest that the new model is more accurate than traditional regression models commonly used for this task, and can reliably predict how the situation changes over the years. The research results were published in the scientific publication series of Proceedings of Machine Learning Research.Risk-adjustment models make use of data from previous years and are used to allocate healthcare funds in a fair and effective way. These models are already used in countries like Germany, the Netherlands, and the US. However, this is the first proof-of-concept that deep neural networks have the potential to significantly improve the accuracy of such models.According to Pekka Marttinen, Assistant Professor at Aalto University and FCAI, "Without a risk adjustment model, healthcare providers whose patients are ill more often than average people .