Available Until 10/31/2028
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Big Data in Healthcare: Exploring Emerging Roles*

For more information or to schedule this course, contact: John Bramble, john.bramble@utah.edu or visit the course site and contact the coordinator in your region.

Site URL: https://nnlm.gov/classes/big-data-healthcare-exploring-emerging-roles

The Big Data in Healthcare:  Exploring Emerging Roles course will help health sciences librarians better understand the issues of big data in clinical outcomes and what roles health sciences librarians can take on in this service area. 
This is a Medical Library Association approved course that will earn students 9 contact hours. This is a semi-self-paced course (“semi" meaning there will be completion deadlines). 

Course content comes from information shared by the presenters at the March 7, 2016 "Using Data to Improve Clinical Patient Outcomes Forum", top reading picks from the NN/LM  MCR Data Curation/Management Journal Club  and NN/LM PSR Data Curation/Management Journal Club’s articles, recommended reading from Club members, and taking the course  Big Data Fundamentals from the Big Data University.

Student will have the opportunity to share what they learned with the instructor from each section of the course content. These submissions can be used to help support the student's views expressed in the final essay assignment.  


Students will articulate their views on why health sciences sector librarians should or should not become involved in supporting big data initiatives by sharing a 500-800 word essay to wrap the course up. Students are encouraged to be brave and bold in their views so as to elicit discussions about the roles librarians should play in this emerging field.

Students who sign up for this course agree to:

  • Commit to spend the full 9 contact hours learning about and articulating their views on the course topic (this includes the 1.5 contact hours from the Big Data University’s course). Students will be docked for missing or low quality work.  

  • Complete the course requirements by the deadline established in each course offering. Arrangements can be made to move  into a future cohort if conflicts arise.

  • Provide course feedback (strengths/weaknesses) on the MLA Online Course Evaluation form.

Grading
Pass / fail grading systems. This means when student submissions meets the assignment's expectations they pass receive full credit for the contact hours for that section.  For submissions that are unclear or incomplete, they will send it back to them to fix or complete until it passes. Students have the option to fail and accept fewer contact hours. They just need to let me know. 


Learning Objectives

Students who successfully complete the course will:

  • Have a better understanding of the role that big data plays in clinical patient outcomes.

  • Have a better understanding of the fundamentals of big data from a systems perspective.

  • Articulate their views/options on the role health sciences sector librarians is in supporting big data initiatives (student will be encouraged to allow their views to be published on one of the NN/LM's publications as part of a dialog with the wider health sciences librarian community engaging in this topic).


Agenda 

  • Participate in all required forum assignments

  • View recordings from the March 6, 2016 Using Data to Improve Clinical Patient Outcomes Forum

  • Read the assigned articles selected by the NNLM Data Journal Club (MCR/PNR)

  • Complete the Big Data Fundamentals course from the Big Data University. 
    Submit a 500 minimum to 800 maximum word essay sharing your view/opinion on this topic.

  • Allow the course instructors to share your views as part of an ongoing dialog with the wider health sciences librarian community who are engaging in this topic.

MLA CE Credits: 9