Do You Play Word Games?

There is an astoundingly popular word game in which the player gets six tries to guess the word of the day, which has been pre-drawn from a list of five-letter words. The only skills one needs are the ability to recognize the alphabet and basic English-language spelling ability. My sisters and I play every day and compare how many tries it takes each of us to come up with the answer. It’s fun, challenging, and easy at the same time, and it gives us a quick way to share time together.

Today’s answer got me thinking (no spoiler alerts here!), what words describe NLM, its mission, and its impact? Let me share a few with you:

HEALTH

Health, that state of optimal well-being for all, is the North Star of all we do here at the National Institutes of Health. NIH’s motto is “Turning Discovery Into Health,” and NLM’s job is to turn information into discovery. The literature collected by NLM provides rich descriptions that help scientists and clinicians understand health and illness, discover new therapies, and relay patients’ experience. In fact, NLM has played an important role in almost every biomedical and clinical discovery of the past 50 years, each of which fosters the world’s understanding of health.

TRUST

The cornerstone of our great national library is the provision of high-quality, trusted resources to the scientific community and general public. We imbue trust in our resources by following important principles of libraries, including collecting widely from literature resources recognized for meeting standards of scientific communication. We provide documentation and publicly available standard practices and policies. Our work is overseen by an NLM Board of Regents as well as by NIH leadership. These checks and balances help us accommodate a body of scientific resources that are congruent with the scientific and clinical knowledge at the time they are collected and reflective of diverse viewpoints and knowledge maturation.

SERVE

NLM serves science and society by collecting, curating, and connecting all types of scientific communication artifacts and making these accessible to the public. Our biomedical literature resources are open to the world, presenting almost 35 million citations, close to 8.5 million machine- and human-readable full-text articles, and over 1,000 consumer-level health information topics. We provide specialized genomic data resources that help scientists discover the origins of life for many species. By linking the genomic data with the literature, NLM can help clinicians make decisions about how to treat complex illnesses that arise from genetic anomalies.

ALIGN

Biologists use laboratory procedures to distill the genetic material out of samples collected from humans, animals, and other types of matter like wastewater and then compare the sampled genetic material to other known records of genetic materials. Using this process, scientists align and compare one set of proteins gleaned from their experiments to others stored in our genomic repositories to detect genetic anomalies or determine if a discovered sequence is actually a new organism or a variant of a known species. Researchers “align” this newly acquired genetic structure with known structures. But we have millions of records of genetic samples, so this process can be time consuming. However, NLM has built the tool to blast through this alignment challenge!

BLAST

The Basic Local Alignment Search Tool (BLAST) is an algorithm and program developed by NLM staff at our National Center for Biotechnology Information that finds regions of similarities between genetic sequences. The program compares nucleotide or protein sequences to reference sequence databases and calculates the statistical significance of any matches. BLAST helps scientists understand functional and evolutionary relationships between sequences, and it can also be used to identify members of gene families.

It actually takes more than a few five-letter words to describe what NLM does and what it means to science and society. Nonetheless, it was quite fun to wordplay NLM!

Who Really Are Our Users, and How Can We Help Them?

Well, this is a question too big for even the largest biomedical library in the world to answer. Our users are everywhere, and in fact, the same user may approach us with very different needs or personas, such as the brilliant cell biologist who is also the mother of a sick toddler. Today, I am thinking of that huge army of applied clinical informatics specialists and how we might begin to help them.

Applied clinical informatics specialists form the technical workforce that make health information technologies work for patients and clinicians. These individuals often have a background in nursing, medicine, or another clinical specialization. Their advanced training and advanced certifications can attest to their understanding of how health care is delivered, the data and information resources needed to deliver that health care, the data underlying care, and the person-professional-technology engagement needed to better deliver care through effective use of information technology.

NLM is pretty clear about its role in supporting the enormous research and development efforts that design, deploy, and evaluate computer systems for health care and in making the basic and clinical biological and biomedical literature accessible to patients, clinicians, and researchers. To the best of my knowledge, NLM has not done enough to think about the applied clinical informatics community as a distinct stakeholder group, and it is now time to do so!

Applied clinical informatics professionals are skilled at designing, installing, and implementing electronic health records. Some of them specialize in evidence-based practice, bringing the research evidence into the point of care. Others focus on human computer interaction, striving to harness the power of computing to support practitioners and to avoid cumbersome or ill-designed clinical records systems. Still other applied clinical informatics professionals are crafting the decision-support tools that bring effective, ethical artificial intelligence into practice. Some serve key roles in their institutions’ value-based health care deliberations, bringing to light through data where health care interventions bring value to the patient and the system. And some applied clinical informatics specialists focus on translating science into care. These positions are critical to making sure that the advantages of information technology reach into the realm of clinical practice… and man oh man, are they busy!

This makes it hard for applied clinical informatics specialists to make use of NLM’s vast resources in the ways different from the typical researcher uses of these resources – as part of a larger process of building or evaluating research ideas, in a reflective manner, through exploration of several articles on the same theme, and with the time, the patience, and the purpose to discern lines of reasoning out of multiple articles. To best support the applied clinical informatics community, NLM needs to expand its ways of doing business, and find ways to make in-the-moment search for best practices or clinical guidance available. How can we do this?

Rethink the “typical library user” and be open to the atypical user. NLM also serves as the repository of record for biomedical knowledge. We have presumed that the synthesis and application of that knowledge is the responsibility of the reader. Perhaps now is time for us to find new ways to partner with outside organizations that can cast their special eye over our resources and to cull their knowledge for the applied clinical informatics specialist.

Work on translating our research findings into practical practices. NLM makes a substantial investment in developing new algorithms that find better ways to link clinical records together. We have a small but fledgling program, our tech transfer funding to stimulate new businesses relevant to the use of data in health care. Perhaps we should better advertise the availability of these funds and target the challenges experienced by applied clinical informatics practitioners.

Expand our abilities to cull basic science and clinical care innovations from the literature. Applied clinical informatics professionals have, as part of their job, the building of the information tools to bring science into practice. We need to learn from them so we can better expose our literature for their needs, keeping them abreast of new and emerging findings in the literature that will someday make their trajectory into practice.

Partner with specialty organizations to make sure that the important lifelong skill development of being an applied clinical informatics professional becomes a realistic process in their career trajectory.

A few months ago, I spent a morning speaking with applied clinical informatics professionals to affirm their interest in NLM supporting them in their work and to listen to their needs, dreams, and demands. In a future blog, I will tell you more about what I learned from them!

Meet the NLM Investigators: Dr. Demner-Fushman Knows the Answers to Your Questions!

Meet my close colleague, Dr. Dina Demner-Fushman! This brilliant researcher is the face behind what many of you have already accessed on NLM’s websites. Many of you will agree with me when I say that having one PhD is extremely impressive–but would you believe she has TWO?! In addition to her master’s degree, Dr. Demner-Fushman has PhDs in immunology and computer science.

Dr. Demner-Fushman and her team use advanced artificial intelligence (AI), natural language processing, and data mining techniques to answer consumers’ questions about a variety of health topics. Did you know that it was Dr. Demner-Fushman’s research that led to the developmental stages of the indexing initiative that produced the current iteration of the MEDLINE resource? This work helps all of us navigate a plethora of NLM resources.

Check out the infographic below to learn more about the innovative, important research happening in Dr. Demner-Fushman’s lab.

Infographic titled: Biomedical Question Answering. The title area features a picture of Dr. Demner-Fushman along with her title and accreditations (MD, Phd): Investigator, Computational Health. The first column of the graphic explores her short and long-term goals  for her projects. The center column describes the processes she uses to achieve these goals, and the last column depicts a simple graphic illustrating a Q and A service.

What makes your team unique? Tell us more about the people working in your lab.   

It is a diverse, multicultural team. Some were even born after I got my first IT job checking computers at Hunter College for Y2K compliance. The team is united by the task of enabling computers to understand health-related information needs and the socioeconomic and professional status of people who come to NLM seeking information. It is a group of exceptionally dedicated and talented people. Our diverse backgrounds make us see all possible aspects of addressing the informational and emotional needs of our users. 

What is your advice for young scientists or people interested in pursuing a career in research?  

  • Be proactive: Seek information and take advantage of training opportunities.  
  • Be brave: Admit you don’t know or don’t understand something. Most people will try to help.  
  • Be bold: Reach out to people who you would like to work with or to discuss your ideas.  
  • Be honest.  
  • Be patient: Research implies working hard, sometimes without immediate results. Even if research is your passion and fun, sometimes you have to do things that you might not enjoy or you might fear but still have to do, like giving talks or writing paper.

What do you enjoy about working at NLM?  

The community of dedicated people across all divisions, the mission, and the intellectual freedom.  

Where are you planning to travel to this year?  

I was just in Dublin, Ireland, in May for the 60th meeting of the Association for Computational Linguistics and co-chaired the BioNLP workshop for the 15th time. I loved Dublin when I visited shortly before the pandemic. I enjoyed revisiting a place I loved and discovering new things to love.

What are you reading right now?  

In the Garden of Beasts by Erik Larson. It provides an amazing view of pre-World War II Germany and political relations. I hope some lessons have been learned! 

You’ve read her words, now hear them for yourself. Follow our NLM YouTube page for more exciting content from the NLM staff that make it all possible. If you’d like to learn more about our Intramural Research Program (IRP), view job opportunities, and explore research highlights, I invite you to explore our recently redesigned NLM IRP webpage.

Transcript [Demner-Fushman]*: When people need information, what they really like is to ask a question and get a really good comprehensive answer, and to also know that the answer is true and correct.

When I started my independent clinician career, I had lots of questions, but I was sometimes not even sure if I was getting the right answer. “Question answering” is this system to understand the question, what the question is about, and why it is asked. When the answer is found, it’s usually not a single answer: It’s parts of the answer in different places. It’s multiple answers. So, all of that then needs to be condensed into one comprehensive answer with evidence of where the answer came from. So that’s the focus of my research.

On the surface, very similar questions asked by clinicians and by the public should be answered very differently. Different deep-learning systems are needed to find the answers to the same question asked by two different people.

The long-term goal is one entry point to all the NLM resources. It doesn’t matter who the person is and how they ask their question or look for information. We should be able to recognize what the person needs and provide it. There is no one—other than NLM—who is specifically dedicated to biomedical information retrieval and biomedical question answering. Although it seems industry is doing that kind of research as well, it is not their main focus, whereas we keep people focused on what really matters for health and advancing medicine.

*Transcript edited for clarity

The Next Normal: Supporting Biomedical Discovery, Clinical Practice, and Self-Care

As we start year three of the COVID-19 pandemic, it’s time for NLM to take stock of the parts of our past that will support the next normal and what we might need to change as we continue to fulfill our mission to acquire, collect, preserve, and disseminate biomedical literature to the world.

Today, I invite you to join me in considering the assumptions and presumptions we made about how scientists, clinicians, librarians and patients are using critical NLM resources and how we might need to update those assumptions to meet future needs. I will give you a hint… it’s not all bad—in fact, I find it quite exciting!

Let’s highlight some of our assumptions about how people are using our services, at least from my perspective. We anticipated the need for access to medical literature across the Network of the National Library of Medicine and created DOCLINE, an interlibrary loan request routing system that quickly and efficiently links participating libraries’ journal holdings. We also anticipated that we were preparing the literature and our genomic databases for humans to read and peruse. Now we’re finding that more than half of the accesses to NLM resources are generated and driven by computers through application programming interfaces. Even our MedlinePlus resource for patients now connects tailored electronic responses through MedlinePlus Connect to computer-generated queries originating in electronic health records.

Perhaps, and most importantly, we realize that while sometimes the information we present is actually read by a living person, other times the information we provide—for example, about clinical trials (ClinicalTrials.gov) or genotype and phenotype data (dbGaP)—is actually processed by computers! Increasingly, we provide direct access to the raw, machine-readable versions of our resources so those versions can be entered into specialized analysis programs, which allow natural-language processing programs to find studies with similar findings or machine-learning models to determine the similarities between two gene sequences. For example, NLM makes it possible for advocacy groups to download study information from all ClinicalTrials.gov records so anyone can use their own programs to point out trials that may be of interest to their constituents or to compare summaries of research results for related studies.

Machine learning and artificial intelligence have progressed to the point that they perform reasonably well in connecting similar articles—to this end, our LitCovid open-resource literature hub has served as an electronic companion to the human curation of coronavirus literature. NLM’s LitCovid is more efficient and has a sophisticated search function to create pathways that are more relevant and are more likely to curate articles that fulfill the needs of our users. Most importantly, innovations such as LitCovid help our users manage the vast and ever-growing collection of biomedical literature, now numbering more than 34 million citations in NLM’s PubMed, the most heavily used biomedical literature citation database.

Partnerships are a critical asset to bring biomedical knowledge into the hands (and eyes) of those who need it. Over the last decade, NLM moved toward a new model for managing citation data in PubMed. We released the PubMed Data Management system that allows publishers to quickly update or correct nearly all elements of their citations and that accelerates the delivery of correct and complete citation data to PubMed users.

As part of the MEDLINE 2022 Initiative, NLM transitioned to automated Medical Subject Headings (MeSH) indexing of MEDLINE citations in PubMed. Automated MeSH indexing significantly decreases the time for indexed citations to appear in PubMed without sacrificing the quality MEDLINE is known to provide. Our human indexers can focus their expertise on curation efforts to validate assigned MeSH terms, thereby continuously improving the automated indexing algorithm and enhancing discoverability of gene and chemical information in the future.

We’re already preparing for the next normal—what do you think it will be like?

I envision making our vast resources increasingly available to those who need them and forging stronger partnerships that improve users’ ability to acquire and understand knowledge. Imagine a service, designed and run by patients, that could pull and synthesize the latest information about a disease, recommendations for managing a clinical issue, or help a young investigator better pinpoint areas ripe for new interrogation! The next normal will make the best use of human judgment and creativity by selecting and organizing relevant data to create a story that forms the foundation of new inquiry or the basis of new clinical care. Come along and help us co-create the next normal!

%d bloggers like this: