Thanksgiving – What I am Giving Thanks for This Year

This time of year reminds us to reflect with gratitude on our lives and our work. This week, I want to share what I am thankful for as the director of NLM. I could go on forever, as evidenced by this list. While I tried to do a top 10, that wasn’t enough — which is yet another thing to be thankful for!  

I am particularly thankful for

  • the 1,700 women and men working at NLM to advance biomedical science and improve access to trustable health information. There isn’t a day that passes that I’m not touched, moved, and impressed by the efforts of those around me.
  • the countless staff who are advancing NLM’s strategic plan, leading to the creation of our new Office of Engagement and Training, an expanded and more responsive Office of Communications and Public Liaison, and a stronger Office of Computer and Communications Systems. With great change can come great challenges, but the Library’s staff have gone above and beyond to create an even more efficient, effective, and impactful organization.
  • our budget office, who is working across NLM to improve our budget management process and bring together our program staff and acquisitions office to better manage the contracts and services required to make NLM offerings available 24 hours a day, seven days a week.
  • my team in the Office of the Director, who are managing the increased workflow with competence and goodwill. I know I can lean on them, and that makes every day easier.
  • the renovation team who are engaging with designers and architects to oversee our many important and necessary building improvement and reconstruction projects. This is a daunting task, but they are facing it head on, with great mindfulness and vision.
  • the people around the world who communicate with me directly via Twitter (@NLMdirector), letting me know how they like our products and offering suggestions for improvements. Their feedback goes a long way.
  • the Public Services Division staff, who promptly respond to the wide-ranging questions we receive about our resources and services.
  • the innovative Lister Hill National Center for Biomedical Communications investigators who, through their collaborations across NIH, are developing advanced Artificial Intelligence models that interpret complex images, from blood smears to diagnostic samples.
  • our growing Extramural Programs Division in biomedical informatics and data science. The strategic investments being made are positioning NLM as a key contributor to data science developments across NIH.
  • NLM’s National Center for Biotechnology Information staff, who have used NLM’s platform and expertise to help guide NIH as it accelerates access to big data, while devising ways to ensure that data rights management and patient privacy considerations are respected.
  • our Division of Library Operations staff, who guide the selection, acquisition, preservation, and management of more than 11 centuries of health and biomedical literature.
  • our building maintenance staff, who keep our space clean and make it a pleasant place to work.
  • my NIH Institute and Center director colleagues, all 27 of them. When I became director, I was encouraged to manage up, manage down, but — most importantly — treasure and cultivate peer relationships. What sound advice!
  • my leadership team, whose counsel not only helps me set the course, but keeps me from veering off course as we move NLM toward its third century.

Finally, I’m grateful for my friends and family, particularly my sisters and my son, Conor, who provide me with the personal sustenance that gives me the energy and drive to lead this amazing organization!

Best wishes for the Thanksgiving holiday to you and all of yours. And, as I mentioned, your input means a lot. So, let me know what NLM provides that you’re thankful for!

How NIH Is Using Artificial Intelligence To Improve Operations

Artificial intelligence (AI) is everywhere, from the online marketplace to the laboratory! When you read an article or shop online, the experience is probably supported by AI. And scientists are applying AI methods to find indications of disease, to design experiments, and to make discovery processes more efficient.

The National Institutes of Health (NIH) has been using AI to improve science and health, too, but it’s also using AI in other ways.

Earlier this fall, the White House Office of Science and Technology Policy hosted a summit to highlight ways that the Federal Government uses AI to achieve its mission and improve services to the American people. I was proud to represent NIH and provide examples of how AI is being used to make NIH more effective and efficient in its work.

For example, each year NIH faces the challenge of assigning the more than 80,000 grant applications it receives to the proper review group.

Here’s how the process works now:  Applications that address specific funding opportunity announcements are assigned directly by division directors. Then the Integrated Review Groups (clusters of study sections grouped around general scientific areas) assign the applications to the correct division or scientific branch. A triage officer handles assignments without an identified liaison. This process takes several weeks and may involve passing an application through multiple staff reviews.

Staff at NIH’s National Institute of General Medical Sciences (NIGMS) creatively addressed this challenge by developing and deploying natural language processing and machine learning to automate the process for their Institute. This approach uses a machine learning algorithm, trained on historical data, to find a relationship between the text (title, abstract, and specific aims) and the scientific research area of an application. The trained algorithm can then determine the most likely scientific area of a new application and automatically assign it a program officer who is a subject matter expert in that area.

The new process works impressively well, with 92% of applications referred to the correct scientific division and 84% assigned to the correct program officer, matching the accuracy rate routinely achieved by manual referrals. This change has resulted in substantial time savings, reducing the process from two to three weeks to less than one day. The new approach ensures the efficient and consistent referral of grant applications and liberates program officers from the labor-intensive and monotonous manual referral process, allowing them to focus on higher-value work. It even allows for related institutional knowledge to be retained after staff departures. NIGMS is currently working with the NIH electronic Research Administration (eRA) to incorporate the process into the enterprise database for NIH-wide use.

Now for a second example that’s more pertinent to NLM.

Our PubMed repository receives over 1.2 million new citations each year, and over 2.3 million people conduct about 2.5 million searches using PubMed every day. An average query returns hundreds to thousands of results presented in reverse chronological order of the date the record is added. Yet our internal process-monitoring determined that 80% of the people using PubMed do not go beyond the first page of results, a behavior also seen in general web searches. This means that even if a more relevant citation is on page 4 or page 18, the user may never know.

Zhiyong Lu, PhD and his team from NLM’s National Center for Biotechnology Information applied machine learning strategies to improve the way PubMed presents search results. Their goals were to increase the effectiveness of PubMed searches by helping users efficiently find the most relevant and high-quality information and improve usability and the user experience through a focus on the literature search behaviors and needs of users. Their approach is called the Best Match algorithm, and the technical details can be found in a paper by Fiorini N, Canese K, Starchenko G, et al., PLoS Biol. 2018.

The Best Match algorithm works like this:  In preparation for querying, all articles in the PubMed repository are tagged with key information and metadata, including the publication date, and with an indicator of how often the article has been returned and accessed by previous searches, as part of a model-training process called Learning-to-Rank (L2R). Then, when a user enters a query phrase in the search box on the PubMed website, the phrase is mapped using the PubMed syntax, and the search is launched. In a traditional search, the results are selected based on keyword matching and are presented in reverse chronological order. Through Best Match, the top 500 results—returned via a classic term-weighting algorithm—are re-sorted according to dozens of features of the L2R algorithm, including the past usage of an article, publication date, relevance score, and type of article. At the top of the page, the search results are clearly marked as being sorted by “Best Match.”

Image showing preparing and refining preparing, matching, ranking and refining articles in NLM's PubMed
Picture by Donald Bliss of NLM

Articles prepared prior to user searches; 1.Queries changed to PubMed syntax; 2.Initial Matching Hits presented in reverse chronological order; 3.Results are re-sorted according to the L2R algorithm to present the Best Match; and 4.The L2R algorithm is updated based on user top choices

This new approach will become the core of a new implementation of PubMed, due out by the spring of 2020.

In addition to the examples I described above, NIH is exploring other ways to use AI. For example, AI can help determine whether the themes of research projects align with the stated priorities of a specific Institute, and it can provide a powerful tool to accelerate government business practices. Because of AI’s novelty, NIH engages in many steps to validate the results of these new approaches, ensuring that unanticipated problems do not arise.

In future posts, I look forward to sharing more about how NIH is improving operations through innovative analytics.

Saluting All Veterans with a Salute to my Father, Thomas Michael Flatley

Occasionally, through Musings, I’ve introduced you to my family — my brothers, who sometimes read my posts; my sisters, with whom I’ve shared many joys; my mom, who proudly watches over my progress in life; and my son, who has been known to broadcast some of my posts to the Twitterverse. But I’ve never introduced you to my father.

My father served in World War II. This week we observe Veterans Day, a federal holiday to honor all military personnel, particularly living veterans, who have served the United States. I’ll talk more about my dad later in this post, but I want to take a moment to remind you of the strong link between NLM and the uniformed services.

NLM’s history dates back to 1836, when a field surgeon in the U.S. Army requested funds to buy medical textbooks. This growing collection officially became the Library of the Surgeon General (Army) and was later renamed the Army Medical Library.

In 1952, then Secretary of Defense Robert A. Lovett signed a directive converting the Army Medical Library into the Armed Forces Medical Library, a joint agency of the three military departments. Shortly after that, Congress transferred the Library to the Public Health Service and named it the National Library of Medicine (Public Law 84-941). These events coincided with our move to the campus of the National Institutes of Health in Bethesda, Maryland.

NLM’s relationship with the uniformed services continues to the present day.

By statute, our Board of Regents includes appointed representatives from the Surgeons General of the Army, Navy, Air Force, and Public Health Service. This representation is not merely ceremonial or historical; their perspectives and connections ensure that NLM continues to provide information and services that are useful to uniformed services personnel.

In addition, NLM is proud to count among its workforce many veterans who served or continue to serve our country as a member of our uniformed services. 

Left to right:
Dr. Brennan's grandfather, Michael Flatley, and her father, Thomas Michael Flatley (in uniform) walking down a street.
Left to right:
Dr. Brennan’s grandfather, Michael Flatley, and her father, Thomas Michael Flatley.

But one very special veteran has always guided my judgment and choices—my father, Thomas Michael Flatley. My dad was the seventh son of an Irish immigrant, Michael Flatley. Family lore said that the seventh son of a seventh son is destined to be king of Ireland. Well, Dad, like many Irish men, was married late, at the age of 32, to my wonderful mom, Lois, 10 years his junior. Then the children came along — Jean, Patti (me!), Kathy, Kevin, and Tim (looking promising), then Eileen, Brian, Sean, and Tom (the hope remains), followed by our lovely Bridget, ending the hope of a dynasty!

Dad was proud of his military service. He served in World War II as a transportation engineer making sure that supplies reached the Philippines. He managed logistics and used his military service to reach out to the indigenous population to make sure, to the extent possible, that the ravages of war did not disrupt the social justice commitment of those brave people. Dad realized that the U.S. engagement in the Philippines was not only about military force but also about information that fostered sustainability.

Throughout my childhood and growing up, Dad served in the U.S. Army Reserve. I remember every Thursday night and two weeks every summer when Dad went “to the Army”!

Dad died in 2006 and never got to see me in my role as director of the National Library of Medicine. This is a lot less sad than it sounds, for I carry him in my heart every day and most of my brothers and sisters were with me as I was sworn in as NLM Director. My dad would have liked this phase of my life!

But more importantly, Dad instilled in me a kernel of patriotism that brings deep satisfaction to my role as the director of NLM. We serve the public every day. We make health information accessible, available—whether through ClinicalTrials.gov or through our enormous public access repository of full-text scholarly articles through PubMed Central. NLM brings health information to the people.

In honor of my dad, I am proud to salute our veterans and reaffirm that the National Library of Medicine stands with our uniformed services personnel around the world as we continue on our mission to make sure that the biomedical informatics research and health information resources of NLM are available to everyone, everywhere!

Marking an Anniversary

It’s Tuesday, which means it’s time for Musings.

It’s also time to celebrate! Musings from the Mezzanine is now 3 years old, and we’re marking the occasion with a new masthead, and some reflections.

When I began this blog three years ago, I wanted to use it to reach NLM stakeholders and offer them a chance to get to know me better. Over time, it’s evolved into an important vehicle for communicating advances in the NLM portfolio, describing key policy issues, and highlighting events and other perspectives. To my great surprise, Musings has become a powerful tool for advancing the work we do every day at NLM.

Last year, I decided to direct more of my attention in this blog toward the science of NLM — computational biology, biomedical informatics, and data science. I promised more posts about basic biomedical informatics, data science research, and new partnerships with domain scientists who are building tools that are accelerating discovery. In addition, I wanted to discuss in detail some complex policy issues, such as the data life cycle and the Library’s responsibility to support rigor and reproducibility within federally funded research.

Focusing on the science of NLM, we’ve reported on the work of some of our intramural scientists. For example, Teresa Przytycka introduced the Musings audience to network biology, characterizing the complex way that cells interact with each other as a suite of networks and nodes. Utilizing data from high-throughput experiments, Teresa’s research group has shown how those interaction networks can be leveraged to identify disease-associated groups of related genes.

We’ve had many articles featuring data science this year — from David Hale’s discussion of the innovative NLM Data Discovery portal to Jim Ostell’s announcement of the launch of NLM’s Sequence Read Archive (SRA) in the cloud, making SRA the largest database of publicly available high-throughput accessible via the cloud. We also addressed whether our data are ready and fit for artificial intelligence, and Susan Gregurick described how the National Institutes of Health (NIH) enhances data sharing through NIH-supported repositories, PubMed Central’s data deposit, the Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) Initiative, and a pilot with the generalist repository Figshare.

I’m proud of how we expanded the focus on public policy germane to NLM. Earlier this year, Dina Paltoo, along with Jerry Sheehan and Rebecca Goodwin, updated us on public policy initiatives affecting NLM, including data sustainability, net neutrality, and open science. They reported on the work of an NLM policy team that brings experts together to deliberate on how NLM should address such issues. And, just last month, I shared the congressional testimony that I submitted to the U.S. House Congressional Subcommittee on Appropriations for NIH Investments in Medical Research.

My blog has also become a place to showcase important events and a variety of perspectives. In February, we celebrated the contributions of African American scientists at NIH. Guest bloggers have periodically provided insights into new developments, such as the introduction to authority-based security by Kurt Rodarmer and the overview of NLM’s new Office of Engagement and Training by Amanda Wilson, and shared their thoughts on important issues, such as the discussion of data reuse by Melissa Haendel of the Oregon Health & Science University.

And, true to the blog’s name, I’ve continued to share my own musings as I’ve matured as an NIH director, including on communicating and leading in a time of change and on my role as a nurse who directs a national library, in response to the oft-asked question, “Didn’t you used to be a nurse?” I was delighted to highlight the 10 women who lead institutes and centers at NIH, which has become my most popular post. I also made a plea for the appropriate use of sick leave — please stay home when you’re sick, if you can.

It’s a privilege and a pleasure to develop this blog and to work with NLM Office of Communications and Public Liaison staff to bring these posts to you. Please let me know your thoughts and ideas — and maybe consider contributing something yourself!

Thanks News Outlets for Getting the PubMed Central Word Out!

How do people find out about PubMed Central?

Some people access NLM’s vast bibliographic resources through our website. Others arrive after a Google search or through platforms such as Ovid MEDLINE. But recently I was reminded that news outlets help people find articles in PubMed Central, too. 

While reading an article about consumer electronics and consumer health, I noticed a link provided by the reporter, which I followed to find the original source material. Low and behold, the link took me back home — to PubMed Central (PMC).

PMC is a free, full-text archive of biomedical and life sciences journal literature here at the National Library of Medicine at NIH. Since its inception in 2000, PMC has grown from comprising only two journals, PNAS: Proceedings of the National Academy of Sciences and Molecular Biology of the Cell, to an archive of articles from thousands of journals.

Today, PMC contains more than five million full-text records, spanning biomedical and life science research from the late 1700s to the present!

PMC supports the NIH Public Access Policy, ensuring access to publicly-funded biomedical research. It also helps NLM meet one of its fundamental responsibilities, outlined in our 1956 enabling legislation, “to preserve permanently the content of books, periodicals, and other library materials pertinent to medicine.”

PMC is not a publisher and does not publish journal articles itself. Instead, content is added to the archive through collaborations with publishers, scholarly societies, research funders, and international organizations.

In December 2017, we reported that more than one billion articles had been retrieved within a single year. Since then, more than 300,000 articles in PMC now have associated supplemental material, frequently including the data to support their research findings.

Almost two-thirds of the articles come from journals that automatically deposit any article reporting on NIH-funded research or from journals that fall under PMC’s full-participation category. Another 25% or so represents “digitized content,” an important collection of articles that, through a collaboration with the Wellcome Trust, provides online access to thousands of complete back issues of historically significant biomedical journals. And about 10% of the articles are “author manuscripts,” which have been peer-reviewed and accepted for publication in a journal. These manuscripts are deposited directly by authors complying with their funders’ public and open access policy to make funded research results available widely, sometimes after an embargo period.

We’ve long known that PMC is a boon to scholarship and clinical practice, yet I’ve wondered how the general public would find articles in PMC.

Now I know.

Journalists who want to direct readers to the authoritative source of their reporting use PMC to provide the full text of the journal article, bringing the power of NLM to an even wider audience. I’m proud that PMC is viewed as a trusted resource and delighted that we’re reaching the public in this way.

Hispanic Heritage Month: Improving Access to Health Information

Hispanic Heritage Month (September 15 to October 15) celebrates the many contributions to U.S. society of people originating from Spain, Mexico, the Caribbean, and South and Central America.

Today, there are almost 60 million Latinx-identifying or Spanish-speaking people in the United States (about 18% of the total U.S. population). Representing our nation’s largest ethnic or racial minority, the median age of the Hispanic population is 29.5 years, which is younger than the median age of about 38 years for the overall U.S. population. About 50% are female, almost half are married, and, unlike their non-Hispanic counterparts, they tend to live in households with children. The number of U.S.-born Hispanics is growing faster than the number of Hispanic immigrants.

The Centers for Disease Control and Prevention reports that people of all races who identify as Hispanic are more likely to develop chronic conditions such as cardiovascular disease, type 2 diabetes, and obesity. Each of these conditions can be managed, or even delayed or prevented, by engaging in healthy lifestyle behaviors that include physical activity, healthy eating, and regular check-ups.

So, the health and the health information needs of Hispanics in the United States, and the well-documented disparities that exist between the Hispanic population and other populations, is of critical importance to NLM.

Our powerful consumer health information resource, MedlinePlus, and our Spanish-language version, MedlinePlus en Español, are trusted sources of accurate health information, and we strive to make them culturally sensitive, relevant, and accessible. Our amazing PubMed literature citation database promotes access to research literature in both English and Spanish, and our molecular resources allow for exploring the intersection of genetics and nationalistic identity.

In addition to these online resources, NLM supports Hispanic individuals, families, and groups through our National Network of Libraries of Medicine (NNLM). Serving diverse communities, the NNLM provides another pathway for providing linguistically and culturally relevant health information.  

The NNLM is a powerful human network of over 7,000 academic health science libraries, hospital and public libraries, and community organizations that provide a point of presence in almost every county in the United States. Its eight Regional Medical Libraries (RMLs) make sure that up-to-date information about NLM’s resources are accessible to communities that are often underrepresented in biomedical research. Although all the RMLs provide access to information in English and Spanish, I’d like to highlight the efforts of two of our regions: the South Central Region, serving Arkansas, Louisiana, New Mexico, Oklahoma, and Texas, and the Pacific Southwest Region, serving Arizona, California, Hawaii, Nevada, and the U.S. Territories in the Pacific. Together, these two regions serve 28 million Hispanics — reaching almost half of the Spanish-speaking population in the United States.

The South Central Region supports the Spanish-speaking community specifically through many programs, including outreach to Presbyterian Española Hospital in Española, New Mexico, a special award to the University of North Texas Health Science Center to support a Library School student from a minority community, and emergency funding for Mobile Programming/Pop-up Program Resources & Tools to support disaster relief and response. The Pacific Southwest Region offers programs that engage community health workers/promotores through activities that address social determinants of health as an approach to health education and promotion in the Hispanic community.

But service to the Spanish-speaking public is not limited to the South Central and Pacific Southwest regions. The Middle Atlantic Region offers Spanish language health information resources on topics ranging from AIDS to cancer to diabetes. An interesting program from the Pacific Northwest Region is a grant to bring health information and access to MedlinePlus en Español over the airways from local public libraries to the region.

Because NNLM members are embedded in their communities, they can utilize NLM resources to meet the particular needs of that community. The professional librarians in these communities provide a feedback loop that helps NLM appreciate both the professional terminology associated with critical health concerns and the need to map local colloquial language for Medical Subject Headings (MeSH) to index the literature.  

The NNLM not only helps us extend the amazing federal investment from Washington, DC, to local communities, but also helps ensure that federal staff in Washington understand, in the vernacular, the health concerns of this important population.

During Hispanic Heritage Month — and throughout the year — it’s important to think about how NLM can better engage with the populations we serve. I welcome your suggestions to ensure that our vast and trustable resources serve everyone, everywhere.

Taking NLM’s Story to Capitol Hill

Last month, I had the honor of joining National Institutes of Health (NIH) Director Francis Collins, MD, PhD, and four other NIH Institute Directors to provide testimony before the U.S. House Congressional Subcommittee on Appropriations for NIH Investments in Medical Research. This was the first time in 12 years that NLM provided testimony to Congress.

Each of us was given the opportunity to deliver a three-minute opening statement. As you can imagine, distilling our many successes and contributions down to a three-minute statement was incredibly challenging. I wish that there had been more time because we have so many wonderful stories to share. We were also able to submit a written statement, which is provided later in this post.

It is my hope that NLM will have more opportunities to share with Congress further insights and details about how NLM’s biomedical informatics and data science research play an integral role in supporting the mission of NIH and how we — true to the NIH tagline — turn discovery into health.

Below is the written testimony that was submitted:

PREPARED STATEMENT OF PATRICIA FLATLEY BRENNAN, RN, PhD, DIRECTOR, NATIONAL LIBRARY OF MEDICINE

Madam Chairwoman and Members of the Subcommittee: I am pleased to have this opportunity to speak to you about the exciting work taking place at the National Library of Medicine of the National Institutes of Health (NIH).

ACCELERATING BIOMEDICAL DISCOVERY & DATA-POWERED HEALTH

The National Library of Medicine (NLM) plays an essential role in catalyzing basic biomedical science through its cutting-edge data science and informatics research, comprehensive information systems, and extensive research training programs. As the world’s largest biomedical library, NLM acquires, organizes, and delivers up-to-date biomedical information across the United States and around the globe. NLM operates some of the most heavily used Federal websites.

Millions of data scientists, health professionals, and members of the public use NLM’s electronic information sources every day to translate research results into new treatments, products, and practices and provide the foundation for clinical decision making by health professionals and patients.

Leveraging its 180-year history of organizing and disseminating biomedical literature, NLM is committed to the application of emerging data science capabilities to challenges in biomedical research and public health.

It does this by enhancing its data and information resources and providing leadership in both the acquisition and analysis of data for discovery. It continues to expand its core biomedical literature and genomic collections to include a broad array of health, clinical, and biological data types. It makes these data findable, accessible, interoperable, and reusable (FAIR) for research.

NLM is investing in new research programs to systematically characterize and curate data describing complex health phenomena and to devise new methods to uncover the knowledge held in data. It has restructured its 16 biomedical informatics training programs to address data science as they continue to foster excellence and support a diverse workforce. NLM is in the process of developing an efficient organizational structure to accommodate emerging directions in research and services.

RESEARCH IN BIOMEDICAL INFORMATICS AND DATA SCIENCE

NLM’s research programs support pioneering research and development to advance knowledge in biomedical informatics and data science. Its research portfolio spans such areas as artificial intelligence, computational biology, clinical decision support, public health surveillance, visualization, and discovery mining in digital data sets. This research encompasses areas of high importance to NIH and society at large, and for audiences ranging from clinicians and scientists to consumers and patients.

Research in data science produces novel analytical approaches and visualization tools that help scientists accelerate discovery from data and translate these findings to clinical solutions. It also aims to solve problems consumers face in accessing, storing, using, and understanding their own health data and to produce tools that make precision medicine discoveries available and more understandable to patients.

Biomedical informatics research is yielding advanced analytical methods and tools for use against large scale data generated from clinical care, leading to fuller understanding of the effects of medications and procedures as well as individual factors important in the prevention and treatment of disease processes.

Recognized as a leader in clinical information analytics, NLM supports and conducts research in areas such as medical language processing, high-speed access to biomedical information, analysis and use of high-quality imaging data, health data standards; and analysis of large databases of clinical and administrative data to predict patient outcomes and validate findings from clinical research studies. Leveraging extensive machine learning experience and field-based projects, NLM is now advancing analytical tools and deep learning techniques for application in image analysis research.

NLM’s biomedical informatics research also addresses issues in computational biology. Research creates new ways to represent and link together genomic and biological data and biomedical literature and produces analytic software tools for gaining insights in areas such as genetic mutational patterns and factors in disease, molecular binding, and protein structure and function.

Last year, NLM established a new partnership with the National Science Foundation to support research on advanced analytical methods specifically applied to health.

BIOMEDICAL INFORMATION SYSTEMS FOR RESEARCH AND HEALTH

NLM develops and operates a set of richly linked databases that promote scientific breakthroughs and play an essential role in all phases of research and innovation.

Every day, NLM receives up to 15 terabytes of new data and information, enhances their quality and consistency, and integrates them with other NLM information. It responds to millions of inquiries per day from individuals and computer systems, serving up some 115 terabytes of information. This includes genomic data, such as that contained in the Sequence Read Archive, as well as citations to more than 30 million journal article records in PubMed.

On any given day, more than 2.5 million people use NLM’s PubMed Central (PMC) to retrieve more than 5 million full-text biomedical journal articles. PMC serves as the repository for NIH’s Public Access Policy and includes more than one million articles summarizing the results of NIH-funded research. Additionally, ten other federal agencies use PMC as the repository for publications collected under their public access policies.

Recently, NLM enhanced the ability to connect articles in PMC to openly available datasets that support reported research findings. Currently, more than 300,000 articles in PMC include datasets as supplemental materials. Others link to datasets hosted in other trusted repositories. The addition of this information has resulted in a 30 percent increase in daily downloads of supplementary material from PMC.

NLM also offers sophisticated retrieval methods and analysis tools to mine this wealth of data, many of which grow out NLM’s research and development programs.

For example, NLM tools are used to mine journal articles and electronic health records (EHRs) to discover adverse drug reactions, analyze high throughput genomic data to identify promising drug targets, and detect transplant rejection earlier so interventions to help clinical research participants can begin more quickly. Data analysis tools also support complex analyses of richly annotated genomics data resources, yielding important molecular biology discoveries and health advances for applications to clinical care. Such applications demonstrate how the benefits of big data critically depend upon the existence of algorithms that can transform such data into information.

As a major force in health data standards for more than 30 years, NLM’s investments have led to major advances in the ways high volume research and clinical data are collected, structured, standardized, mined, and delivered.

In close collaboration with other HHS agencies, NLM develops, funds, and disseminates clinical terminologies designated as essential for demonstrating meaningful use of EHRs and health information exchange. The goal is to ensure that clinical data created in one system can be transmitted, interpreted, and aggregated appropriately in other systems to support health care, public health, and research. NLM produces a range of tools to help EHR developers and users implement these standards and makes them available in multiple formats, including via application programming interfaces or APIs.

NLM is now providing support to develop tools to facilitate research use of the Fast Healthcare Interoperability Resource, or FHIR, standard that is being widely adopted for use in electronic health records.

ENGAGING THE PUBLIC WITH HEALTH INFORMATION

NLM uses multiple channels to reach the public with health information, including development of consumer-friendly websites, direct contact, and human networks that reach out to communities.

Direct-to-consumer information is made available in lay language through MedlinePlus, which covers more than 1,000 health topics. EHR systems can connect directly with MedlinePlus to deliver information to patients and health care providers at the point of need in healthcare systems. In collaboration with other NIH Institutes and Centers and other partners, NLM produces the print and online NIH MedlinePlus magazine, and its Spanish counterpart, NIH Salud.

The National Network of Libraries of Medicine (NNLM) engages more than 7,000 academic health sciences libraries, hospital libraries, public libraries, and community-based organizations as valued partners in conducting outreach to ensure the availability of health information and efficient access to NLM services. The NNLM provides a community-level resource for NIH’s All of Us program, ensuring a point of presence in almost every county in the U.S. The NNLM provides a robust network that reaches communities that are often underrepresented in biomedical research.

NNLM partners with local, state, and national disaster preparedness and response efforts to promote more effective use of libraries and librarians and ensure access to health information in disasters and emergencies. NNLM also plays an important role in increasing the capacity of research libraries and librarians to support data science and improve institutional capacity in management and analysis of biomedical data.

CONCLUSION

To conclude, through its research, information systems and public engagement, NLM supports discovery and the clinical application of knowledge to improve health. Its programs provide important foundations for the field of biomedical informatics and data science, bringing the methods and concepts of computational, informational, quantitative, social, behavioral, and engineering sciences to bear on problems related to basic biomedical and behavioral research, health care, public health, and consumer use of health-related information.

To watch the entire proceedings, click here: https://appropriations.house.gov/events/hearings/investments-in-medical-research-at-five-institutes-and-centers-of-the-national