Using Advanced Data Analytics and ML to Improve Patient Care and Reduce Costs

Hospital-acquired conditions (HAC) represent a major strain on hospitals. Infections, surgical errors, and falls in medical facilities lead to further medical treatment that payers (insurers, public health programs) will often refuse to cover. While HACs are inevitable at even the best-run facilities, minimizing can go a long way in improving a hospital’s financial position and patient care. Some providers have made significant progress in identifying sources of HACs by leveraging advanced data analytics and ML. In this second episode of our three-part series on data and analytics use cases for the Healthcare industry, Emma Irwin will present demonstrate how Dataiku’s Data Science Studio can be leveraged to quickly and easily design, train and deploy accurate models to identify sources of HAC and implement strategies to minimize their occurrence.