SoN LAI 4 Day Intensive May 2022

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SOCR News & Events: Leadership, Analytics and Innovation (LAI) Master’s Program 4-Day Intensive (May 17, 2022)

LAI 4DayIntensive 2022.jpg

Logistics

Overview

  • Leadership, Analytics and Innovation (LAI) Program aims to prepare scholars for the Next Global Crisis.
  • In the 1880’s James Berrill Angell, the 3rd UM President, declared UM as an institution providing uncommon education for the common folk. Shortly thereafter, the School of Nursling was established.
  • At SoN, the UM Leaders & Best Initiative translates into Raising Effective Healthcare leaders and Best trained nursing and health professionals.
  • The 4-day intensive will offer unique opportunities for community building, networking, and innovating thinking, e.g., through Nurse Executive Fellow Academy discussions, Implementation Science and Analytics Workshops, Policy Paper sprints, Team-Building exercises, and Hackatons.
  • Emphasis on Diversity, Equity and Inclusions - DEI is important for a number of reasons: (1) Social-justice & fairness, exclusivity factors; (2) Economic factors – risk reduction; (3) Evolutionary factors – long-term stability and sustainability.

Challenges

Data, Methods & Implementation Challenges Effective Nursing, Biomedical, and Health Sciences Approaches
Lack of access to existing, effective, modern, active-learning resources Embrace Open and FAIR Data Science
Credit, acknowledgement, and recognition Give credit, entice independent enhancements
Storage, computing, networking limitations Challenging, but Google, MS, AMZ, NVIDIA, RStudio provide free Ed support
Collaboration Engage with fellow academics (e.g., MBDH, professional Societies), offer open-enrollment in short courses, MOOCs, other electives, Collaborate with partners on R&D projects
Cross-institutional partnerships (limited time, funding, HR),
Transdisciplinary interactions (non-trivial), Collaborate with partners on R&D projects
Application domain repurposing (requires team-science support)
Decision science and implementation of ML/AI into clinical practice Use a team science approach, embedding nurses, clinicians, statisticians and engineers

Core Principles

  • Team Science approach to tackling difficult healthcare challenges (science, implementation, translation, costs, outcomes, equity)
  • FAIR (Findable, Accessible, Interoperable, and Reusable) resources
  • Supporting the common-good, equitable, fair, transparent, trustworthy, rigorous, transdisciplinary, and sustainable Leadership, Analytics & Innovation in Nursing & Healthcare

Demonstrations

Contact

Questions, comments, collaborations, and suggestions are always welcome.





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