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Big Data, Healthcare, and the Evolution of the Health Science Librarian

Posted by on April 23rd, 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: Lisa Mastin, Medical Librarian, WellStar Atlanta Medical Center, Atlanta, GA

Data is part of life and the amount of data being created, captured, stored, and analyzed is expanding exponentially. In the healthcare sector, Big Data is rapidly changing the landscape. Health Science librarians should get involved with big data in healthcare, at least at a basic level, because if they do not, they risk losing the ability to engage with the user (i.e. researcher, clinician, patron), in a user-centered environment. I see health science librarians working in several areas of data science. At the very least, and possibly the most essential element, would be to acquire an understanding of the language used in data science.

Although I do not believe all librarians should become data scientists or even work with big data (several postings in this course expressed a similar opinion), I do believe that all health science librarians need to know the terminology. In an online discussion based on the National Institute of Nursing Research (NINR) module of Big Data, one reflection on Dr. Brennan’s video mentioned that she liked Dr. Brennan’s comment that “data science is a team sport,” and agreed that as librarians, we should be able to speak the language and “at least know who to turn to or ask.” This relates to the second area I feel that health science librarians should get involved with big data in healthcare – knowing who to go to with questions. In a reply to her reflection, another remarked, “librarians connect our users to articles, books, databases, and web resources;” so “what’s to stop us from connecting our users to experts on campus?” I agree that librarians can learn who the data science experts are at their institution and then pass that information along to their users. In doing this, the health science librarians are establishing contacts and forming relationships across their campus or institution, and creating connections is something else librarians are skilled at doing.

Training is also a skill that librarians excel at and is the next area where I see health science librarians becoming involved with big data. As Jeff Durham noted in a reflection on medical research, librarians, “have advanced skills in information and pedagogy,” so are well suited to train researchers. Other class members shared this idea, and I believe that most librarians feel confident when it comes to training/teaching. Health science librarians could, for example, train researchers on how to use data science-related technology tools or on how to find specific information in their electronic health records (EHR). If health science librarians gain access to the EHR at their institutions, this opens the door to other areas in which they could assist with big data. I see librarians creating metadata and/or controlled vocabularies for the natural language portion of patient notes entered into the EHR by clinicians. We discussed this in the module five online discussion session and several participants expressed interest in assisting in these areas, as well as working with an EHR in other capacities (i.e. adding links to the library website or related databases, adding information for physicians, etc.).

In addition to the areas I have mentioned, I feel that data visualization, population health, and data management would also be areas in which health science librarians could work with big data. Traditional librarian skills, such as information searching, research methods, database management, archival work, and digital preservation combined with some newer skill sets (data literacy, informatics, visual analytics), will allow health science librarians to compete for these roles. Where and how health science librarians decide to get involved with big data in healthcare will certainly vary by individual librarian, by what is most important is that they do become involved with it. I reviewed an article about an ongoing big data research project on cardiovascular care in China, and in this article, there was no mention of librarians assisting with the project. One of the course instructors made the wise comment that she wondered if there are people working on the project performing research data management functions. if there was someone performing these roles, they weren’t trained as librarians. I now think that there are probably many research projects where people are doing the data science work that we have discussed in this course, but librarians are not doing it. Health Science librarians can bring their unique skills to big data research projects if they possess the skills and researchers know librarians are capable and can provide big data support.

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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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