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Region 5 Blog March 28th, 2024
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Apr

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Reflections on Big Data in Healthcare: Exploring Emerging Roles

Posted by on April 16th, 2018 Posted in: Data Science


In the NNLM Big Data in Healthcare: Exploring Emerging Roles course, we asked participants, as they progressed through the course to consider the following questions: Do you think health sciences librarians should get involved with big data in healthcare? Where should librarians get involved, if you think they should? If you think they should not, explain why. You may also combine a “should/should not” approach if you would like to argue both sides. NNLM will feature responses from different participants over the coming weeks.

Written by: Kathleen Carlson, Education Librarian, College of Medicine Phoenix, University of Arizona, Phoenix, AZ

It is essential for the future of medical librarians to get involved in Big Data. Much of our future work will be coming from big data research projects, especially librarians that work in hospitals and health care systems. Since librarians were early adopters of technology, we were able to move from print indexes to searching indexes on CD-ROMs that were eventually moved to the Web. Moving from the card catalogue to integrated automated library systems, librarians understand how important it is to move forward with Big Data. Many of the older, experienced librarians may not have the expertise or training in the fields of math, computational skills, statistics and domain expertise but we know that our profession should be part of our institutions Big Data team and at least have a seat at the table.

I know that being an Assistant Professor of Practice in the Department of Biomedical Informatics (BMI) at my academic institution, has allowed me to understand and speak the language of Big Data. Clinicians will come to me for resources and journal articles and I have learned a lot by attending monthly journal club meetings on different subjects of Biomedical Informatics and Big Data. BMI fellows, Chief Medical Information Officers (CMIO,) Chief Nursing Officers (CNO) of area hospitals, and BMI faculty attend the sessions. Here I have an opportunity to be seen and be heard and ask questions when they arise as a non-clinician. We have covered the following topics of Big Data and Informatics in the past three years:

  • Cybersecurity
  • Data Standards
  • Health Literacy
  • Electronic Health Record/Electronic Patient Record
  • Process Oriented Health Information Systems
  • Clinical Decision Support Systems
  • Graphic Display and Visualization
  • Health information Exchange
  • Cloud Computing Services
  • Substitutable Medical Applications and Reusable Technologies (SMART)
  • Fast Health Interoperability Resources (FHIR)

I also attend monthly Clinical Informatics Grand Rounds. The speakers vary from clinicians to researchers, MBA, Pharmacy and Public Health faculty.

So, for the past three years I have had a seat at the table and have given our library visibility within Biomedical Informatics and Big Data. I also believe that a medical librarian at any institution should find a champion or champions that will assist him/her in getting a seat at the table. And when that is accomplished, a hospital librarian should get permission to embed at least one vetted  link that is appropriate to a patient’s electronic record with MedlinePlus.gov,  National Institute on Aging, or another consumer health oriented resource. This would relieve the burden on clinicians in finding the best resource for patient care.

Big Data can be organized, appraised, secured, preserved with a librarian’s help and can assist researchers and clinicians in patient care and help find areas that may need improvement. Creating an online resource guide with Big Data tools and resources can be a first step into marketing the librarian and library. The NNLM PSR had recently recruited a data and technology services coordinator. She asked librarians if they collected any data for their institution. Unfortunately, we are considered a satellite campus of a large Research One University. I think there are areas at my institution where data is collected but could be used more effectively. I know within the Scholarly Project, a four-year mandatory thesis and poster at our institution, many of our students use Big Data from area hospitals or the state’s data archives to have foundational information in their presentations and theses. They are assisted by their clinical mentors.

I also like one of my fellow course student’s discussion post about teaching himself ‘R’ so he is able to teach classes to the data scientists on his campus. Finding resources for Big Data programming language and free software for statistical computing and graphics software like ‘R’ and can help the librarian be an informational resource for Big Data collection. This instruction example is one-way librarians will have to get out of your comfort zone and put themselves out there for Big Data. We have access to SPSS and STATA in our library commons. I took three classes on RedCap to help me understand Big Data and how to collect it safely and securely. REDCap is a secure web application for building and managing online surveys and databases and collecting data.

The librarian can be the go-to resource for students and researchers and help them search the archives of stored Big Data sets. I do not believe that our small campus has the capacity to store Big Data and it is not something that the larger academic institution is willing to duplicate. I do believe that as a librarian being visible and attending committee meetings, journal clubs, clinical informatic rounds and actually showing an interest in learning about Big Data gives a librarian the knowledge and vocabulary to understand and share with her constituents. The librarian can also familiarize himself/herself with websites that assist in Big Data knowledge similar to the Institute for Health Metrics and Evaluation which I learned about in the course discussions.

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Developed resources reported in this program are supported by the National Library of Medicine (NLM), National Institutes of Health (NIH) under cooperative agreement number UG4LM012343 with the University of Washington.

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