Track 1: Artificial Intelligence: A Paradigm Shift in Nursing
Artificial Intelligence has been transformative for many public and private industries, and we are currently observing an AI-led revolution in healthcare. Nursing must play a key role in AI translation to practice. It is important that Nursing changes its mindset about AI, from treating it as a trend to considering it the paradigm shift it has become. This session will provide insights into aspects of Nursing that will be changed because of AI’s use in practice.
Track 2: Nursing Knowledge Big Data Requires Radical Educational Transformation – Let’s Build It
We are all gathered here at this conference to develop awareness, momentum, tools and strategies to ensure we have sharable, comparable nursing data in order to demonstrate nursings’ contributions to health and medical care outcome. But we have a fundamental problem that will hold us back from achieving this mission. Many direct care nurses, advanced practice nurses, faculty and educators lack the basic information and information technology competencies and capabilities to be full participants in the digital health evolution. During this session, participants and discussion leaders will work together to surface the issues and develop action steps to close the gap.
Track 3: Question everything! Conversations on radical transformations to address workforce issues
World War II created a crisis in nursing supply similar to what we are experiencing today. The profession responded with the Associate Degree RN. How will we respond to the current crisis? Bring your craziest ideas to these sessions as we debate new approaches to nursing education and nurse staffing.
Track 4: OMOP? Oh My! Hands-on Data Science using the Observational Health Data Sciences and Informatics (OHDSI) Platform
This is a workshop format session. Increasingly, healthcare data scientists and research networks are using the Observational Health Data Sciences and Informatics (OHDSI) ecosystem to accelerate research productivity and improve results. In this workshop, we will examine the OMOP data model, its rich concept ontologies and learn about the OHDSI analysis platform. Participants will then be guided in a hands-on exercise to gain a better understanding of the power of the platform by using these tools to define, characterize and analyze cohorts using simulated data. Participants can bring their own laptops to work through hands on exercises using the OHDSI tools or they can follow along with the instructors or work with their fellow attendees.