Cheryl E. Field, MSN, RN, CRRN: PointClickCare: Employee (Ongoing)
Today as a staff member in a skilled nursing facility your days are packed. No matter what your role is from direct care to administrator there is an a keen awareness that success requires attention to resident centric details which roll up into organizational outcomes measured in revenue, risk and reputation. Clinical leaders are directing care, and staff are focused on completion of tasks for their patients. We know early identification leads to lower cost and improved healthcare outcomes. Too often we don't have time to critically think about the data elements constantly being collected in an electronic health record. Until now. This session will show you how new technologies leverage massive amounts of everyday data, to build predictive measures which add value to the decisions made in senior care every day. These technologies save staff time and improve care outcomes by doing some analysis of the data that humans simply don't have time or computing capacity to perform. More importantly, these technologies are making their way into healthcare and those organizations which embrace technology are predicted to success not only in revenue, risk and reputation but in staff retention as well. Using Rehospitalization and Significant change as examples we will review the use of deep neural networks, and natural language processing methods were research and used to improve care outcomes among a pilot group of skilled nursing facilities. Come learn how advanced technology can bring value every day to the decisions made by care providers in your organization.
Learning Objectives:
Define machine learning and how it applies to your care setting.
Describe three similarities and differences in decision making between machine learning and human analysis and decision making.
State three lessons learned from integration of a predictive rehospitalization model into the clinical decision-making process, care outcomes and market position for skilled nursing facility organizations.