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: Heidi Beke-Harrigan, MLS, Health Sciences Librarian, Member Services Coordinator, OhioNET
There has been an explosion of conversation around the topic of big data. The potential for mining large sets of data in endless, customized combinations could revolutionize healthcare, patient outcomes and evidence-based medicine. At the same time, as with systematic reviews, effective data projects benefit from a collaborative environment and a team approach. One individual is not likely to possess the skills to formulate the right questions, write queries, extract the data, provide analysis and manage data storage/retrieval. Data without context is lifeless. Misused it can be exploited, misinterpreted and manipulated. Deriving meaning from data depends on someone’s ability to mine what’s there and make real connections to people’s lives. That’s where librarians excel. Our work has always been about cultivating connections, enabling access to raw information so that new ideas can ferment, providing access to those ideas and end products, and storing the results. Formats have come and gone, but it’s all data and librarians can play a key role in making data useful. Where individuals with specific expertise may focus on a very narrow aspect of data work (trees), librarians tend to see patterns, connections and possibilities (forest). Librarians like to create spaces where nuanced details and creativity can coexist and mingle in a place of infinite possibility.
What skills can librarians specifically bring to the table? Researchers have identified the need to recode data elements and challenges maintaining consistency of data over time as two barriers to big data work. Librarians with cataloging and metadata experience can work with teams to help bring about harmonizing of terminologies and standardize metadata descriptions. They are also able to ask important questions about storage and retrieval. Where will the coding that extracted the data live? Do the resulting data sets need to be stored? How can reproducibility or access points to the data be supported? What story does the data tell and who else might want to discover it?
Imagine further, a world where librarians are part of a new framework of front-line clinical teams and integral to using big data to improve patient outcomes. If we assist with research topic formulation, provide input regarding user experience design, help develop consult management tools, and support the creation of effective query forms and output displays, can we free up clinicians and partner with other colleagues to more fully explore the role of data in Practice Based Evidence (PBE)?
Librarians’ expertise in providing programming, informal learning opportunities and formal classroom instruction can serve us well to assist in citizen data scientist training and to prepare our students with critical skills for work in a data rich landscape. Part of that skill-set should also include an awareness for and appreciation for data literacy, data sharing, and transparency. As Dr. Brennan pointed out, there are certainly opportunities for data scientists and programmers in this information-rich world, but to give that data meaning, requires that we all bring the unique strengths and core values of our diverse professions to the table. In that realm, librarians have much to share.