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Dragonfly June 17th, 2019
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Data, Data Everywhere and Not a Drop to Drink

Posted by on April 20th, 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: Jeff Durham, Medical Librarian, Desert Regional Medical Center, Palm Springs, CA

We swim in a sea of information; more often than not we are drowning in it. When a person is presented with a smorgasbord of data, how do we determine what we should eat? This is the current situation with regards to big data and healthcare. What data should be utilized and how. It is in this data-centric meal that the data-savvy health science librarian should be most at home: as critic, guide, and chef.

As health science librarians, we have a responsibility to not only provide the communities that we serve with access to up-to-date and accurate information, but also must be available to enable and facilitate the informational needs of researchers in our communities. With the tremendous amount of big data that is generated on a daily basis, health science librarians have a duty to become involved and assist all of their patrons, both lay and professional, to access, extract, and manage the data (both big and small) that they need.

There are barriers to making a librarian into a data-savvy librarian who can tackle big data problems with ease. One barrier is that many graduate schools in library and information science have not been as keen to teach data science in a general education format, preferring to see it more as a sub-specialty. This occurs ironically enough in iSchools as well. While there is a growing trend to change this educational oversight, it is not the dominant paradigm yet. Another barrier is that of opportunity. All too often, the librarian simply does not have the time or their employer does not provide the means (e.g. time off, reimbursement) for the librarian to refresh their skill set. Until library managers and directors see the value of continuing education of the librarians on their staff on how to use data science and work with big data, the health sciences librarian will continue to fall behind.

There are also opportunities to be found. In hospitals and health science libraries, with residents and medical students, there are lots of in-roads for librarians to make. Given the exponential growth in big data that biomedical devices and the prevalence of smart devices which are constantly generating both passive and active data there is a lot of big data to utilize. The data that is being produced has the potential to be used in research projects for students, residents, nurses, and doctors on staff. There is a significant gap between the abilities of these medical professionals and that of data science. The role of the data-savvy librarian is to be a bridge between these gaps. The data-savvy librarian is able to assist their patrons in identify the datasets that they need as well as demonstrating how to wrangle, clean and visualize their data. By doing this, the librarian provides an essential role in the medical field. It is through the management of big data and assisting the researcher with working with the data and discerning patterns and trends that the librarian enables the student, nurse, or clinician to make evidence-based decisions on the data. By doing so, the librarian assists not only the informational needs of the researchers, but also has a very real impact on patient care.

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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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