View source for SoN LAI 4 Day Intensive May 2022

== [[SOCR_News | SOCR News & Events]]:  Leadership, Analytics and Innovation (LAI) Master’s Program 4-Day Intensive (May 17, 2022) ==
[[Image:LAI_4DayIntensive_2022.jpg|220px|thumbnail|right|]] 

== Logistics ==

* '''Event Date/Time''': May 17, 2022, 1:00-1:30 PM ([https://time.is/ET US Eastern Time])
* '''Location''': [https://online.nursing.umich.edu/student-experience/online-learning/ LAI Program 4-Day Intensive], [https://maps.studentlife.umich.edu/building/school-of-nursing-building SNB Building, University of Michigan].
* '''Format''':	Residential/In-person
* '''RSVP''' (required): [https://online.nursing.umich.edu/student-experience/online-learning/#modal:request-info RSVP]

* [https://wiki.socr.umich.edu/images/2/2b/Dinov_LAI_4_Day_Intensive_May_2022_Outline.pdf Ivo Dinov's Presentation ''LAI in Data-Driven, Evidence-based, and Technology-Enhanced Health Science''].

== Overview==
* [https://nursing.umich.edu/academics/specialties/leadership-analytics-and-innovation Leadership, Analytics and Innovation (LAI) Program] aims to prepare scholars for the ''Next Global Crisis''.
* In the 1880’s James Berrill Angell, the 3<sup>rd</sup> 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 [https://leadersandbest.umich.edu/ 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==

{| class="wikitable"
| align="center" style="background:#f0f0f0;"|'''Data, Methods & Implementation  Challenges'''
| align="center" style="background:#f0f0f0;"|'''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==
* Resource navigators ([https://socr.umich.edu/html/Navigators.html graphical], [https://dspa2.predictive.space/ key phrase search])
* [https://wiki.socr.umich.edu/index.php/SOCR_Books Electronic books] - [https://dspa2.predictive.space/ Data Science and Predictive Analytics (DSPA) active-learning resources], [http://www.socr.umich.edu/people/dinov/SMHS_Courses.html Scientific Methods for Health Sciences], [https://wiki.socr.umich.edu/index.php/Probability_and_statistics_EBook Probability and Statistics EBook]
* [https://umich.instructure.com/courses/38100/files/folder/Case_Studies Case-studies and driving motivational challenges], [https://wiki.socr.umich.edu/index.php/SOCR_Data open data resources]
* [https://socr.umich.edu/HTML5/ Webapps] - [https://socr.umich.edu/HTML5/MotionChart/ Motion Charts], [http://myumi.ch/O49zG Pressure Injury Prediction Model], [https://socr.umich.edu/HTML5/SOCR_TensorBoard_UKBB UK Biobank], [https://socr.umich.edu/HTML5/SOCRAT/ SOCR Analytical Toolbox]
* Collaborative Open-Science ([https://socr.umich.edu/html/SOCR_Research.html Ongoing Research Project], [https://socr.umich.edu/html/SOCR_Consulting.html Consulting], [https://www.socr.umich.edu/people/dinov/publications.html Pubs]).

==Contact==
[https://socr.umich.edu/people/dinov/ Questions, comments, collaborations, and suggestions are always welcome].



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