The More Things Change . . .

Back in January, I shared our plans for aligning the National Library of Medicine’s (NLM’s) organizational structure with the goals and vision in the 2017-2027 Strategic Plan. Now, in the heat of summer, it’s time to tell you about our progress.

We’ve come a long way, while remaining true to our mission and commitment to be a source of trusted health information.

First things first.

We’re guided by a strategic plan that affirms our pledge to support data-driven science, engage with stakeholders, and build a workforce for the future while preserving our essential role as a National Library that collects, organizes, and disseminates biomedical and life sciences information to the public through offerings such as PubMed, the database of Genotypes and Phenotypes (dbGaP), and MedlinePlus.

We examined all aspects of our organization, which encompasses 1,700 people, five key divisions, operational processes and practices related to our technical and physical infrastructure elements, and myriad offerings. Our efforts revealed—and reinforced—the immense talent that exists across NLM. They also identified opportunities for improving efficiency and effectiveness.

Perhaps the biggest transition in 20 years has been the sunset of the Specialized Information Services (SIS) division, with staff and programs being integrated across the Library. We will continue to work out logistics associated with this transition and will provide notice of changes on the SIS home page. In the meantime, I’d like to acknowledge the recently retired SIS leaders, Florence Chang, Acting Associate Director, and Janice Kelly, Acting Deputy Associate Director, for guiding an outstanding, dedicated team through a complex transition. I hope you will join me in thanking them for their service to NLM and wishing them well as they embark on new journeys.

We consolidated our outreach, training, and engagement activities and created an Office of Engagement and Training (OET) within the Division of Library Operations. Headed by Amanda J. Wilson, this office brings together many of the outreach and training staff and services from across the library, along with the National Network of Libraries of Medicine. We’ll be better able to coordinate outreach activities when and where they are needed most, launch national efforts, and institute modern planning and evaluation processes to ensure that our efforts are effective.

We evaluated the quality and sustainability of many NLM public offerings. Some key resources, such as TOXNET and ClinicalTrials.gov, moved to more modern, robust technical platforms to ensure security and sustainability. Some offerings were sunsetted, with the information integrated into more sustainable resources. As we continue to examine NLM’s offerings, we’ll post updates in the NLM Technical Bulletin.

We worked with workforce development experts to better understand the talents and goals of the more than 50 staff members who joined new teams or have new jobs. The creative design staff from our Audiovisual Program Development Branch (APDB) merged with the Office of Communications and Public Liaison, establishing a more powerful team that will use a wider array of video, images, and technology to tell the NLM story. The technical staff from APDB joined the Office of Computer and Communications Systems, affording greater coordination of our information technology, computer, and audiovisual production activities.

Some NLM staff have taken on new roles. For instance, in Library Operations, Stacey Arnesen, who led the Disaster Information Management Research Center, is now Deputy Director for the Public Services Division and Jeanne Goshorn, who led the Biomedical Information Services Branch, is now Deputy Director for the Bibliographic Services Division. Victor Cid joined the Lister Hill National Center for Biomedical Communications’ Cognitive Science Branch and Dan Gerendasy, Chief of International Programs, kept his same role and joined OET.

To prepare staff for a future of data science, we developed the Data Science @NLM Training Program. As part of this program, each staff member completed a self-assessment and received an individual development plan that included activities such as self-study or participation in an in-depth training course.

Everyone’s present or future work will be touched by data science—from our indexers who need to interpret literature using new analytics, to our investigators who employ machine learning to power up natural language processing, to our purchasing clerks who invoice for cloud services. We’ve developed new work groups, sometimes by adding one or two new people to a branch or merging two smaller groups into one.

For better collaboration, some staff teams have moved from the National Institutes of Health (NIH) main campus to larger facilities off campus, allowing work groups that should work together to be together. And some of our meeting rooms have been equipped with better technology to enhance telework and promote staff productivity.

We’re preparing to hire new investigators for our intramural program and ensuring our research labs are equipped for data science. We’ve already renovated part of the Lister Hill Center to bring the ClinicalTrials.gov team together in one place and will be strengthening our physical infrastructure and our technological platforms. We’re planning a four-year renovation of the main Library building. The renovation will create more flexible work spaces for more than 150 people on the first floor and mezzanine, a new integrated reading room for our patrons, and a state-of-the-art training facility, as well as contribute to our ongoing efforts to increase our collection space.

How did all of this happen so quickly?

The outstanding staff at NLM is full of people willing to make plans and try new things despite some uncertainties. I’m grateful to Library staff and NIH leadership for their support as we journey into the future together.

As always, I’ll continue to keep you posted about key developments and milestones that take place along the way!

Democratizing Information Access

When I became director of the National Library of Medicine (NLM), I took an oath of office in which I promised to uphold the U.S. Constitution. As we celebrate Independence Day, I’m reflecting once again on what that oath means to me and how I live out my commitment to it through my work.

This time, I want to reflect on the role of NLM in democratizing information access. As the world’s largest biomedical library, NLM supports health care and biomedical discovery by helping to ensure direct access to biomedical information and research for the scientific community and the public.

NLM delivers scientific knowledge to the nation and to the world. Through MEDLINE and PubMed, we provide a platform for scientists and scholars to share their findings freely and a database that can be used by anyone to explore and discover biomedical and health information. It’s a sound investment of federal dollars; a boon to research; and a reliable resource for patients, families, and caregivers.

The Library has established critical elements essential for journals included in our collection. These include editorial practices that contribute to the objectivity, credibility, and quality of the content. These critical elements let the public know that the information NLM presents is trustable.

NLM is committed to making the biomedical and scientific literature accessible to all. The Library does not decide what gets published; journals and their editorial boards do that. But as a library, NLM is committed to archiving the published literature over time to reflect the state of knowledge now and the ways knowledge grows. For example, sometimes claims published in the biomedical literature are superseded by new discoveries. A lack of reproducibility calls other findings into question. Medical perspectives might change or broaden to encompass the patient’s perspective where the professional’s or clinician’s had been privileged previously. Other published findings might turn out to be flat wrong, due to, among other things, invalid assumptions, improper methodology, or unsupported claims that were not caught during peer review.

It’s often said, though, that the literature is self-correcting. Science takes the long view, and our job at NLM is to let it, documenting where the science stands today and pointing to where it might go in the future, but otherwise remaining neutral about what’s published—as long as the journal’s content shows strong scientific merit; the process for selecting that content is transparent and sound (e.g., external peer review, ethical practices, stated conflicts of interest, prompt corrections or errata); and the journal offers opportunities for comment and dissent.

This recognition of the ongoing process of correction and refinement also drives the education we do with our partners from the National Network of Libraries of Medicine to build health literacy in communities across the country.

The Library further supports access to trustable health information by being a resource for journalists as they convey health information to the general public. NLM annually hosts a group of fellows from the Association of Health Care Journalists, bringing them to the National Institutes of Health campus for four days of training to enhance their use of our many health information offerings and to help them integrate biomedical research into their reporting. The journalists also learn about key topics in health care, such as health disparities, patient engagement, and clinical effectiveness research, better preparing them to report on these and other crucial or emerging issues.

Through it all, NLM collaborates with our sister federal agencies to deliver to the public quality health information and health data, working together to ensure freedom of ideas about biomedical discovery and health care delivery.

That’s worthy of fireworks, wouldn’t you say?

On the Ethics of Using Social Media Data for Health Research

Guest post by Dr. Graciela Gonzalez-Hernandez, associate professor of informatics at the Perelman School of Medicine, University of Pennsylvania.

Social media has grown in popularity for health-related research as it has become evident that it can be a good source of patient insights. Be it Twitter, Reddit, Instagram, Facebook, Amazon reviews or health forums, researchers have collected and processed user comments and published countless papers on different uses of social media data.

Using these data can be a perfectly acceptable research practice, provided they are used ethically and the research approach is solid. I will not discuss solid scientific principles and statistically sound methods for social media data use here, though. Instead, I will focus on the much-debated ethical principles that should guide observational studies done with social media data.

To help frame our discussion, let’s consider why the ethics of social media data use is called into question. Almost invariably when I present my work in this area or submit a proposal or paper, someone raises the question of ethics, often despite my efforts to address it upfront. I believe this reticence or discomfort comes from the idea that the data can be traced back to specific people and the fear that using the data could result in harm. Some research with social media data might seem innocuous enough. One might think no harm could possibly come from making available the collected data or specific tweets on topics like smoking cessation and the strategies people find effective or not. But consider data focusing on topics such as illegal substance use, addiction recovery, mental health, prescription medication abuse, or pregnancy. Black and white can quickly turn to gray.

Before going further, it is important to understand the fundamental rules for this type of research in an academic setting. In general, researchers who want to use social media data apply to their institutional review board (IRB) for review. Research activities involving human subjects and limited to one or more of the exempt categories defined by federal regulations receive an “exempt determination” rather than “IRB approval.” In the case of social media data, the exemption for existing data, documents, records, and specimens detailed in 45 CFR 46.101(b)(4) generally applies, as long as you don’t contact individual users as part of the research protocol and the data to be studied are openly and publicly available. If you will be contacting individual users, the study becomes more like a clinical trial, needing “informed consent” and full IRB review. (See the National Institutes of Health’s published guidelines for this case.)

Furthermore, exempt studies are so named because they are exempt from some of the federal regulations that apply to human-subjects research. They are not exempt from state laws, institutional policies, or the requirements for ethical research. Most of all, they are not exempt from plain old common sense.

But when it comes to the existing-data exemption, which data are “openly and publicly available” is open to question. To be safe, use only data available to all users of the platform without any extra permissions or approvals. No data from closed forums or groups that would require one to “join” within the platform should be considered “openly and publicly available.” After all, members of such groups generally expect their discussions are “private,” even if the group is large.

Beyond that, when deciding how to use the data or whether to publish the data directly, ask yourself whether revealing the information in a context other than where it was originally posted could result in harm to the people who posted it, either now or later. For example, you could include specific social media posts as examples in a scientific paper, but, if the topic was delicate, you might choose not to publish a post verbatim, instead changing the wording so a search of the host platform would not lead someone to the user. In the case of platforms like Reddit that are built around anonymity, this language modification would not be necessary. If possible, use aggregate data (e.g., counts or topics discussed) rather than individual social media posts.

However you approach your research, datasets used for automatic language processing experiments need to be shared for the results to be reproducible. Which format this takes depends on the data source, but reproducibility does not take a back seat just because these are social media data. To help you further consider the question of how to use or share these data, check out the guidelines published by the Association of Internet Researchers. These guidelines include a comprehensive set of practical questions to help you decide on an ethical approach, and I highly recommend them. In their study of the ethics of social media use, Moreno et al. also address some practical considerations and offer a good summary of the issues.

We are now ready to consider what constitutes ethical research. Ethics, or principles of right conduct, apply to institutions that conduct research, whether in academia or industry. Although ethics is sometimes used interchangeably with morals, what constitutes ethical behavior is less subjective and less personal, defining correct behavior within a relatively narrow area of activity. While there will likely never be a generally agreed upon code of ethics for every area of scientific activity, a number of groups have established principles relevant to social media-based research, including the American Public Health Association, the American Medical Informatics Association, and the previously mentioned Association of Internet Researchers. Principles of research ethics and ethical treatment of persons focus around the policy of “do no harm,” but it falls to IRBs to determine if harm could result from your approach and whether your proposed research is ethical. Even so, however, review boards might have discrepant opinions, as recent work looking into attitudes toward the use of social media data for health research has shown.

So where does that leave those of us looking to conduct health research using social media data?

Take a “stop and think” and “when in doubt, ask” approach before finalizing a study and investing time. Help ensure the researcher’s interests are balanced against those of the people involved (i.e., the users who posted the data) by putting yourself in their shoes. Be cognizant of the needs and concerns of vulnerable communities who might require greater protection, but don’t assume that research involving social media data should not be done or that the data cannot be shared. If the research was ethically conducted, then social media data can and should be shared as part of the scientific process to ensure reproducibility, and there is a lot that can be gained from pursuing it.

headshot of Dr. Graciela Gonzalez HernandezGraciela Gonzalez-Hernandez, MS, PhD, is a recognized expert and leader in natural language processing applied to bioinformatics, medical/clinical informatics, and public health informatics. She is an associate professor with tenure at the Perelman School of Medicine, University of Pennsylvania, where she leads the Health Language Processing Lab within the Institute for Biomedical Informatics and the Department of Biostatistics, Epidemiology, and Informatics.

Information Along the Underground Railroad

A couple years ago, I wrote about how the paintings in Jacob Lawrence’s Migration Series inspired me to think about how the National Library of Medicine gets information to people on the move—people displaced by violence, natural disasters, or economic crises. I felt a similar stirring after viewing the Jeanine Michna-Bales exhibition Photographs of the Underground Railroad at the Phillips Collection last month.

The deep indigo and shadowy black of Michna-Bales’ photographs stand in stark contrast to the oranges, greens, and yellows of Lawrence’s paintings, which occupy a room across the hall at the Phillips, but both have things to tell me.

Michna-Bales’ collection of nighttime photographs immediately pulled me in, helping me sense a whisper of the fear and anxiety escaping slaves might have felt as they slogged their way north toward freedom. The dark, shadowed images required me to peer in closely to detect a house or barn that might have provided a safe place to hide—or concealed danger. The Drinking Gourd constellation, isolated in the night sky, guided the travelers north along dirt roads and winding rivers, while cypress swamps, mangroves, and thick vegetation, barely perceptible in the moonlight, slowed passage.

It’s a chilling piece of history brought to life through the photographer’s lens, but as the exhibition curator underscored, slavery still exists today. More than 20 million people are enslaved around the world.  More than 50% are women; 25% are children under the age of 18. These staggering figures cry out for redress.

What can NLM do to help those working to combat this crisis or treat its victims?

We provide information to those on the front lines.

The Library’s literature can help primary care physicians and emergency room staff identify patients at risk and potentially rescue victims of human trafficking. It can help clinicians deliver health care that is both trauma-informed and culturally sensitive, attuned to victims’ needs and backgrounds. It can give educators ways to train health professionals to recognize and help victims, offer policy makers strategies to reduce human trafficking, and encourage the global health community to investigate the social and economic elements that drive such exploitation. The Library also has articles on human trafficking for the horrific purpose of organ removal and others on the relationship between human trafficking and stress-related illnesses and drug use among survivors.

It’s a harrowing collection but a necessary one, if we are to combat this crisis.

To further help those who are fighting this fight, PubMed lists articles similar to the ones initially found, helping to shape a coherent picture of the clinical challenges, health services, and public policies that can counteract this crime or mitigate its effects. We also provide the free full text of publicly funded research on this topic.

We may be able to do even more in the future. I see opportunities to tailor the health information we provide to the personal culture, worries, and recent experiences of the person searching. It’s a bold vision, but reaching the most vulnerable makes it worth the effort.


If you think someone may be a victim of human trafficking, call or encourage them to call the National Human Trafficking Hotline at (888) 373-7888 for help, resources, and information. You may also text 233733.

Socio-legal Barriers to Data Reuse

Envisioning a sustainable data trust

Guest post by Melissa Haendel, PhD, a leader of and advocate for open science initiatives.

The increasing volume and variety of biomedical data have created new opportunities to integrate data for novel analytics and discovery. Despite a number of clinical success stories that rely on data integration (e.g., rare disease diagnostics, cancer therapeutic discovery, drug repurposing), within the academic research community, data reuse is not typically promoted. In fact, data reuse is often considered “not innovative” in funding proposals and has even come under attack. (See the now infamous “research parasites” editorial in The New England Journal of Medicine.)

The FAIR data principles—Findable, Accessible, Interoperable, and Reusable—are a terrific set of goals for all of us to strive for in our data sharing, but they detail little about how to realize effective data reuse. If we are to grow innovation from our collective data resources, we must look to pioneers in data harmonization for insight into the specific advantages and challenges of data reuse at scale. Current data-licensing practices for most public data resources severely hamper data reuse, especially at scale. Integrative platforms such as the Monarch Initiative, the NCATS Biomedical Data Translator, the Gabriella Miller Kids First Data Resource Portal, and myriad other cloud data platforms will be able to accelerate scientific progress more effectively if licensing issues can be resolved. As a member of these various consortia, I want to facilitate the legal use and reuse of increasingly interconnected, derived, and reprocessed data. The community has previously raised this concern in a letter to NIH.

How reusable are most data resources? In our recently published manuscript, we created a rubric for evaluating the reusability of a data resource from the licensing standpoint. We applied this rubric to more than 50 biomedical data and knowledge resources. These assessments and the evaluation platform are openly available at the (Re)usable Data Project (RDP). Each resource was scored on a scale of zero to five stars on the following measures:

  • findability and type of licensing terms
  • scope and completeness of the licensing
  • ability to access the data in a reasonable way
  • restrictions on how the data may be reused, and
  • restrictions on who may reuse the data.

We found that 57% of the resources scored three stars or fewer, indicating that license terms may significantly impede the use, reuse, and redistribution of the data.

Custom licenses constituted the largest single class of licenses found in these data resources. This suggests the resource providers either did not know about standard licenses or believed the standard licenses did not meet their needs. Moreover, while the majority of custom licenses were restrictive, just over two-thirds of the standard licenses were permissive, leading us to wonder whether some needs and intentions are not being met by the existing set of standard permissive licenses. In addition, about 15% of resources had either missing or inconsistent licensing. This ambiguity and lack of clear intent requires clarification and possibly legal counsel.

A total of 61.8% of data resources use nonpermissive licenses.

Putting this all together, a majority of resources would not meet basic criteria for legal frictionless use for downstream data integration and redistribution, despite the fact that most of these resources are publicly funded, which should mean the content is freely available for reuse by the public.

If we in the United States have a hard time understanding how we may reuse data given these legal restrictions, we must consider the rest of the world—which presumably we aim to serve—and how hard it would be for anyone in another country to navigate this legalese. I hope the RDP’s findings will encourage the worldwide community to work together to improve licensing practices to facilitate reusable data resources for all.

Given what I have learned from the RDP and a wealth of experience in dealing with these issues, I recommend the following actions:

  • Funding agencies and publishers should ensure that all publicly funded databases and knowledge bases are evaluated against licensing criteria (whether the RDP’s or something similar).
  • Database providers should use these criteria to evaluate their resources from the perspective of a downstream data user and update their licensing terms, if appropriate.
  • Downstream data re-users should provide clear source attribution and should always confirm it is legal to redistribute the data. It is very often the case that it is legal to use the data but not to redistribute it. In addition, many uses are actually illegal.
  • Database providers should guide users on how to cite the resource as a whole, as individual records, or as portions of the content when mashed up in other contexts (which can include schemas, ontologies, and other non-data products). Where relevant, providers should follow best practices declared by a community, for example the Open Biological Ontologies citation policy, which supports using native object identifiers rather than creating new digital objects.
  • Data re-users should follow best practices in identifier provisioning and reference within the reused data so it is clear to downstream users what the license actually applies to.

To be useful and sustainable, data repositories and curated knowledge bases need to clearly credit their sources and specify the terms of reuse and redistribution.

I believe that, to be useful and sustainable, data repositories and curated knowledge bases need to clearly credit their sources and specify the terms of reuse and redistribution. Unfortunately, these resources are currently and independently making noncompatible choices about how to license their data. The reasons are multifold but often include the requirement for sustainable revenue that is counter to integrative and innovative data science.

Based on the productive discussions my collaborators and I have had with data resource providers, I propose the community work together to develop a “data trust.” In this model, database resource providers could join a collective bargaining organization (perhaps organized as a nonprofit), through which they could make their data available under compatible licensing terms. The aggregate data sources would be free and redistributable for research purposes, but they could also have commercial use terms to support research sustainability. Such a model could leverage value- or use-based revenue to incentivize resource evolution and innovation in support of emerging needs and new technologies, and would be governed by the constituent member organizations.

casual headshot of Melissa Haendel, PhD Melissa Haendel, PhD, leads numerous local, national, and global open science initiatives focused on semantic data integration and disease mechanism discovery and diagnosis, namely, the Monarch Initiative, the Global Alliance for Genomics and Health (GA4GH), the National Center for Data to Health (CD2H), and the NCATS Biomedical Data Translator.

The Wisdom in Asking Questions

The following has been adapted from a commencement address I gave last month.

Congratulations, graduates! You’ve spent years preparing for this day, years of answering questions—on exams, in clinical debriefings, and in response to your patients’ inquiries. Knowing those answers has been essential to getting you to where you are today.

But now, as you launch a career of service to patients and society, you must become as adept at asking questions as you are at answering them. To be successful, you will need to embrace intentional questioning.

Intentional questioning:

  • Is asking purposeful, well thought-out, understandable, and well-timed inquiries
  • Inspires the responder to take the next step into awareness, action, and insight
  • Is not intended to stimulate recall or appraise comprehension, but to engage with another to engender wonder, reasoning, and action

Think back to the first questions you asked: Why is the sky blue? When is dinner? Where is Mom? These questions were motivated by a curiosity about the world, coupled with a need to feel tethered or secure. I want you to return to that childhood questioning—be curious, know your tethers.

Questions convey wonder about the world and about the “other.” Asking questions of our patients helps them reveal themselves and their concerns. Asking questions of science advances the knowledge needed to diagnose and treat the human response to disease, disability, and developmental challenges. Asking questions reveals where new technologies might help resolve complex health problems, and where innovative technologies may have inadvertently disenfranchised some of our sisters and brothers.

So, embrace asking questions, but ask your questions judiciously. Make sure the questions are worthy.

What does it take to ask good questions?

  • Curiosity
  • Interest
  • A compelling need to know
  • Humility
  • An understanding of the knowledge, skills, motivation, and cultural characteristics of the other

Forty years ago, when I attended my own MSN graduation at Penn, there was no iPhone, no internet, and no PubMed. Now I direct the largest biomedical library in the world, and every day five million people use our resources to answer questions. So, right now you could say I’m in the question-answering business.

But I got here by asking questions: How can computers help nursing? In what ways can we help people better take care of themselves? If we broadened the definition of health to encompass the social and behavioral domains, could we improve health overall?

These questions propelled my research forward and shaped my career. But I didn’t even know enough to ask them early on. No one did. No matter how skilled they were, my faculty—like your faculty—could not have anticipated the knowledge nurses would need in ten years, twenty years, fifty years. You must discover that knowledge, often on your own. That is exactly why you must become adept at intentional questioning.

Intentional questioning addresses three realms.

  1. Knowing self
    • Am I ready?
    • What more do I need to know?
    • Who else should be with me?
    • What would my future self wish I had asked of me now?
  2. Knowing the world (which can guide our research)
    • Why?
    • What if … ?
    • Who can help me know this better?
    • What might be, or has been, the impact of innovation?
  3. Knowing others (such as patients)
    • What brings you here?
    • What can I do for you?
    • What questions do you have? Because listening to the types of questions people ask and the way they ask them can teach us a lot about how they frame the world and add meaning to the important issues in their lives.

Questions are the starting point of dialogue and the starting point of engagement.

And once you ask a question, you must be ready to accept the answer. You don’t always have to like it—the answer to the first research question I posed turned out to be the exact opposite of what I wanted it to be, and then I had to do some fast thinking—but you must always deal with the answer.

Not asking questions

Finally, I must point out that sometimes not asking a question is more powerful than asking it.

Let me tell you a story about one of the most important questions never asked.

In Michael Frayn’s Tony Award-winning play “Copenhagen,” Niels Bohr, his wife Margrethe, and Werner Heisenberg reflect on a long-ago evening when Heisenberg visited Bohr to learn the secret of creating heavy water, which would have accelerated Germany’s development of the atomic bomb. Bohr, in a later conversation with his wife, confessed that he deliberately did not ask Heisenberg the one question that would have led Heisenberg along the line of reasoning that could have resulted in Germany successfully creating an atomic bomb.

Why am I telling you this story? To bring home the idea that sometimes the most important aspect of intentional questioning lies in not asking a question.

When during our practices do we intentionally not pose a question?

As nurses, we might hold off because the person is not ready to hear the answer. Questions confront people with uncertainties and consequences, possibly long before a person is ready to face them.

Cultural factors can also influence our decision. Is this a culture in which an individual has the self-efficacy to answer? Or is this a culture in which complex questions are answered by elders, a family network, or friends?

Sometimes we hold questions because the moment demands our attention and we cannot be distracted from the focus and energy needed to resolve the crisis. And sometimes we don’t ask because we recognize that current circumstances—the state of knowledge or measurement or analytics—aren’t at a place to deliver a proper answer.

My wisdom for you

Graduation speakers are supposed to impart wisdom. In my life the deepest wisdom has arisen from conversations that began with questions. So my wisdom for you: Ask questions early and often.

Questions are part of your future—whether judiciously asking a question or intentionally withholding one. Your education will provide a solid foundation on which to formulate those questions and the base of a scaffolding on which to hang your new understanding.

So I leave you with a bold direction: Stop knowing so much—and be ready to ask more questions! You are ready to be intentional questioners. Please embrace the role because someday, I may be your patient.

Photo credit (commencement, top): Angela Radulescu [Flickr (CC BY-NC-SA 2.0)] | cropped

Next Up for the NLM Biomedical Informatics Training Program

Guest post by Katherine Majewski, NLM Librarian.

How are librarians applying informatics?

This is the question we want to answer in re-envisioning the NLM Biomedical Informatics training program. The survey-style course, most recently hosted by Augusta University in Georgia, provided a sampling of the vast realms of informatics research and application in the health sciences. We want to build on the success of that course by targeting the specific skills and knowledge that librarians can use right now to tackle real-world challenges.

headshot of Barbara Platts
Barbara Platts

For example, Barbara Platts and her team provide clinical information services for Munson Healthcare in Traverse City, Michigan. Over the last several years, Barbara’s role at Munson has expanded into electronic health records (EHR). She now contributes to the policy and management of clinical information flow both within and outside the EHR system. As part of that effort, Barbara enhances the functionality of Munson’s EHR; increases the usable clinical content provided across multiple platforms; develops efficient knowledge management structures for hospital communities of practice; and trains hospital employees to use critical appraisal skills to find the best information services available.

How can NLM support this important work and help other librarians follow Barbara’s lead in using information tools to improve patient care?

In trying to answer that question, we’ve been exploring the connections between clinical librarians, informatics, and patient care to better understand NLM’s role. This past year we offered a webinar series entitled “Clinical Information, Librarians, and the NLM: From Health Data Standards to Better Health,” which focused on the roles and products of the National Library of Medicine related to applied clinical informatics, particularly within electronic health records systems and clinical research.  We devoted one of the six sessions in the series to discussing emerging roles and training needs for aspiring informatics librarians. In conjunction with the series, we solicited interviews, visited clinical sites, and polled webinar participants to learn about the specific skills and knowledge clinical librarians are using now or will need in the future.

Along the way we heard from many librarians like Barbara who are part of the clinical information flow, though not always integrated into clinical systems as much as they would like.

We learned that librarians are:

  • working with clinical teams to improve patient care and safety by improving the efficiency and effectiveness of information delivery;
  • connecting systems to systems, bridging the divide between clinicians and information technology staff;
  • crafting information policies and practices within and between health institutions to reduce waste and redundancy and improve patient care;
  • supporting research by:
    • framing research questions,
    • informing research design methods, and
    • managing research data;
  • conducting research in text mining, artificial intelligence and machine learning;
  • selecting and licensing content, including patient education content; and
  • educating users.

How can NLM support these current and future roles for librarians?

Underlying any work related to health information must be a strong facility with the information services NLM provides. This should not be understated or undervalued: Librarians make significant contributions to health using their knowledge of information sources and retrieval techniques, and NLM resources are at the center.

But those librarians who managing data or making system-level connections between patients and health information need additional skills and knowledge from NLM. These fall into two general areas:

  • The ability to manage and direct access to NLM systems and data (e.g., through APIs), and
  • An understanding of the terminologies that can be used to connect systems.

What is the NLM plan for informatics training for librarians and other information professionals?

To support patient care, we are:

To support research, we will:

What about other realms of informatics?

We’re not done yet. Understanding additional areas where librarianship, informatics, and NLM intersect will require more communication with you. Look for opportunities to engage with us through the National Network of Libraries of Medicine and on our page Training on Biomedical Informatics, Data Science, and Data Management.

headshot of Katherine MajewskiKatherine Majewski is a trainer, instructional designer, and technical writer for NLM products. Kate received her master’s degree in library and information science from the State University of New York at Buffalo and has worked in libraries since 1989.