Interprofessional Big Data

 

Interprofessional Big Data: An Informatics Learning Laboratory Translating Key Concepts to the Real-World

 

April 4-5, 2018

Location: Doubletree by Hilton Minneapolis-University, Minneapolis, MN

Register Now

Interprofessional Big Data

 

Interprofessional Big Data: An Informatics Learning Laboratory Translating Key Concepts to the Real-World

 

April 4-5, 2018

Location: Doubletree by Hilton Minneapolis-University, Minneapolis, MN

Register Now


This hands-on informatics/big data workshop will provide a laboratory to address the key issues facing attendees. The workshop will teach key concepts, highlight exemplars, provide group consultations and customize the work session to address the questions brought forward by attendees. 


Program Objectives

This two-day workshop engages individuals and teams to explore key concepts in big data science, focusing on building capacity while understanding and supporting local solutions within a national context. 

This workshop focused on transformation, not traditional statistical analysis, will provide strategies for supporting transformative thinking using the latest informatics concepts. 

The workshop experience, driven by local experiences and the needs of attendees,will provide dedicated time within the interprofessional practice/education agenda to work with teams or individuals on designing and applying sustainable  interprofessional big data strategies local to  national. 

This workshop will dedicate specific attention  to understanding how interprofessional big data can be used to understand patterns, trends and evidence that will guide patient care, care management, risk management patient satisfaction, decision support, and implications for the education/practice Nexus. 

This workshop will describe the National Center’s IPE Core Data Set, a first-of-its-kind for interprofessional practice and education in the nation. 

Issues and Challenges attendees might consider bringing forward for discussion include:

  • Classifying data into dashboards
  • Classifying data into diagnosis (medical, nursing)
  • Optimizing best practices (clinical pathways)
  • Comparative effectiveness (drugs, technology, practice)
  • Prediction & risk profiling (diabetes, stroke, MI, pressure ulcers, falls)
  • Reducing readmissions
  • Integrating personalized medicine/health and social determinants of health
  • Leveraging social media, GPS, wearable technology for health

Who should attend

Increasingly, the delivery of health care is relying on big data to understand trends to optimize care and improve health outcomes. Anyone with an interest in interprofessional health informatics would benefit from this introductory level-course. Understanding that different members of the team bring different perspectives and strengths, we encourage you to broadly consider engaging your interprofessional team supporting your data goals. 

This course may be of particular interest to:

  • Health care and education collaborators exploring how to leverage big data to support solutions for interprofessional practice, education and scholarship
  • Health care administrators and clinical professionals desiring to understand basic principles of big data science and how it can guide decisions around care and care management.
  • Health IT professionals seeking information about current trends in interprofessional big data science and how they can be applied to local environments.
  • Individuals with an interest in learning more about interprofessional big data science and its role in advancing interprofessional practice and education.

Acknowledgements

The National Center for Interprofessional Practice and Education is supported by a Health Resources and Services Administration Cooperative Agreement Award No. UE5HP25067. The National Center is also funded in part by the Josiah Macy Jr. Foundation, the Robert Wood Johnson Foundation, the Gordon and Betty Moore Foundation, The John A. Hartford Foundation and the University of Minnesota.

A special thank you to the University of Minnesota School of Nursing for its leadership in nursing and interprofessional informatics research to improve health and health care through local, national and international engagement.