A 21st-Century Approach to Health Services Research: NLM Moves Forward with You in Mind

Guest post by Doug Joubert, head of User Services and the National Information Center on Health Services Research and Health Care Technology, National Library of Medicine.

NLM has a strong record of involving its stakeholders in the strategic decisions that drive the products we develop and the services we offer. As the world’s largest biomedical library, NLM is committed to thinking strategically about how we can promote discovery while supporting the 21st-century data, data science, and information needs of our diverse user community.

Looking forward

As we consider how to better address the needs of everyone who produces or uses health services research, we invite you to be part of the process by responding to this Request for Information (RFI).

Through this RFI, NLM is seeking input on future resource and program directions in support of information related to health services research, practice guidelines, and health technology, including technology assessment. Specifically, feedback is requested on the following:

  • Products that NLM currently offers in the areas of health services delivery or health services research
  • Information types necessary for organizations to successfully support health services research or public health
  • Tools, resources, or health services literature that are the most critical for NLM to collect or support
  • Any other comments that would enable NLM to support future work related to health services delivery or health services research

Taking stock

The health services research community is supported by NLM’s many databases, tools, and services, including PubMed and PubMed Central, Bookshelf, MedlinePlus, and ClinicalTrials.gov. Our Unified Medical Language System and clinical vocabulary and data standards resources are used by individuals in clinical research and health practice in the United States and globally. Through our intramural and extramural research and training investments in biomedical informatics, computational biology, and genomics, we are advancing projects that address real-world challenges in public health surveillance, opioid intervention, social determinants of health, and other domains. NLM also promotes the use and reuse of data for research and discovery from both research studies and clinical data sources through publicly available national health surveys, diagnostic images, administrative claims, and electronic health records. 

Since the early 1990s, with the establishment of the National Information Center on Health Services Research and Health Care Technology (NICHSR), NLM has developed a number of specialized information resources targeting producers and users of health services research. These specialized resources were designed to address some of the challenges of finding and accessing credible and authoritative health services research information.

At the core of NLM’s service model is meeting the information needs of all those who seek current and trusted biomedical information. To this end, NLM has continued to increase, refine, and evaluate the health services research resources of NICHSR. These efforts reflect the changing needs of users and the ways in which health services delivery is evaluated. Through our products, services, and programs, we continue to strive to support the information needs of researchers, clinicians, health care professionals, policymakers, librarians, and the public.

We hope you’ll take the time to share your expertise and vision for health services research information at NLM so that our NICHSR can continue evolving to meet your needs. We can’t wait to hear from you!

Doug Joubert is the head of Users Services and the and the product owner for the NLM Health Services Research product portfolio. He supports a team that provides research and information services to the public. He also supports the NLM Strategic Plan by leveraging NLM tools and services to facilitate the management of data throughout the entire lifecycle. Doug works collaboratively to develop and support data science training for NLM Reference and Web Services staff.

Why Testing is the Key to Getting Back to Normal

This piece was authored in collaboration with the leadership across NIH and represents a unified effort to meet the challenges presented by the COVID-19 pandemic with excellence and innovation.

One thing we know for sure – every single person can help our country control the COVID-19 pandemic. From wearing a mask to washing your hands to maintaining physical distance and avoiding large indoor gatherings, each of us can follow proven public health practices that not only reduce our own chance of getting infected by SARS-CoV-2 (the virus that causes coronavirus disease, or COVID-19), but also prevent the spread of COVID-19 to our coworkers, friends and loved ones. Another thing that will help is testing as many people as possible.  

Testing for COVID-19 is so important that in April 2020, the NIH launched the Rapid Acceleration of Diagnostics (RADx) Initiative to develop rapid, easy-to-use, accurate testing and make it available nationwide. As part of this effort, the RADx Underserved Populations (RADx-UP) program is about finding solutions to stop the spread of COVID-19, particularly among racial and ethnic minorities, and other vulnerable populations that have been disproportionately affected by this pandemic. Previously, we reported about the launch of this project and our plans to develop community-based approaches to study how best to implement testing and prevention strategies for populations who are disproportionately affected by, have the highest infection rates of, or are most at risk for complications or poor outcomes from COVID-19.

Scientists from the NIH and across the country are working around the clock to establish programs that will ensure access to and acceptance of rapid and reliable testing around the country. Testing can help people determine if they are infected with SARS-CoV-2 – regardless of whether they have symptoms – and whether they are at risk of spreading the infection to others. Taking measures to prevent the spread of infection will be the most effective strategy for getting us safely back to work and school.

We want to take this opportunity to articulate why widespread testing is necessary, important, and achievable.

  1. Testing saves lives

Testing of all people for SARS-CoV-2, including those who have no symptoms, who show symptoms of infection such as trouble breathing, fever, sore throat or loss of the sense of smell and taste, and who may have been exposed to the virus will help prevent the spread of COVID-19 by identifying people who are in need of care in a timely fashion. A positive test early in the course of the illness enables individuals to isolate themselves – reducing the chances that they will infect others and allowing them to seek treatment earlier, likely reducing disease severity and the risk of long-term disability, or death.

Testing of people who have been in contact with others who have a documented infection is also important. A negative test doesn’t mean you’re in the clear; you could become infectious later. Therefore, even if you test negative, you need to continue to protect yourself and others by washing your hands frequently, physically distancing, and wearing a face mask. A positive test makes it clear that you have to isolate yourself, and that others with whom you have been in contact since the time of your exposure should also get tested.

Since it is recognized that nearly half of all SARS-CoV-2 infections are transmitted by people who are not showing any symptoms, identifying infected individuals while they are presymptomatic, as well as those who are asymptomatic, will play a major role in stopping the pandemic.

  1. Testing can be easy and quick

Initially, the only test available required getting a sample from the back of a person’s throat. New developments, some of which are supported by two other NIH projects, RADx Tech and RADx-ATP (Advanced Technology Platforms), will provide more comfortable and equally accurate tests that obtain the sample from inside the nose. On the horizon for large-scale use are tests that will use a simple mouth swab or a saliva sample. 

A positive test for SARS-CoV-2 alerts an individual that they have the infection. Not only can they get treated faster, but they can take steps to minimize the spread of the virus.

This is why it is so important to get the test results quickly, ideally within a few hours or less.

Early in the pandemic, there was not enough capacity and limited supplies to collect and process the tests, which resulted in delays. However, lab equipment has improved, capacity and supply have expanded, and results are being returned, on average, within 3-4 days. In fact, point-of-care tests will be available that provide a result in less than 15 minutes!

  1. Testing matters more in the communities affected the most

Communities of color are disproportionately burdened by the COVID-19 pandemic. Some individuals in these communities are essential workers, who cannot work from home, increasing their risk of being exposed to the virus. In addition, multi-generational living situations or multi-family housing arrangements can allow the virus to spread more quickly if one household member gets infected. Comorbid conditions that worsen the health risks of COVID-19, such as heart disease, obesity and diabetes, are also more common in minority communities because of long-standing societal and environmental factors and impediments to healthcare access. Therefore, COVID-19 can spread quickly in these communities, and the impact of that spread is great. Testing, particularly of asymptomatic and pre-symptomatic individuals, is key to interrupting this spread.

Unfortunately, there still is a lot of confusion about where to get a test and who should get tested. It is becoming clear that for a person to test positive, they have to have a significant amount of the virus in their system. This means that if you have no symptoms but think or were told that you were in contact with a person with COVID-19, you should isolate yourself immediately, call your health care provider, and then get a test. If you have any question, always call your health care provider or local county public health office. You can also contact the CDC Hotline at 800-CDC-INFO (800-232-4636).

Staying informed is essential. We encourage you to look to up-to-date, trusted sources of information about COVID-19, such as resources from the NIH website or MedlinePlus, the National Library of Medicine’s consumer information resource. 

Over the next few months, you’ll have opportunities, such as those listed at the NIH’s vaccine trial sites, to help scientists discover if the vaccines being evaluated now are effective. If you become ill with COVID-19, you can to participate in clinical trials underway to develop and evaluate a wide range of potential treatments, as well as several possible vaccines. So that these therapies will work for everyone, it is important for people from diverse communities across the country to participate in this research. We hope that in the not too distant future, these efforts will lead to therapies that will put an end to the pandemic.

In the meantime, let’s all continue to protect ourselves and others from getting infected, and get tested if you believe you have been in contact with someone with COVID-19. 

Top Row (left to right):
Diana W. Bianchi, M.D., Director, Eunice Kennedy Shriver National Institute of Child Health and Human Development 
Patricia Flatley Brennan, R.N., Ph.D., Director, National Library of Medicine
Gary H. Gibbons, M.D., Director, National Heart, Lung, and Blood Institute
Joshua Gordon, M.D., Ph.D., Director, National Institute of Mental Health

Middle Row (left to right):
Richard J. Hodes, M.D., Director, National Institute on Aging
Jon R. Lorsch, Ph.D., Director, National Institute of General Medical Sciences
George A. Mensah, M.D., Division Director, National Heart, Lung, and Blood Institute
Eliseo J. Pérez-Stable, M.D., Director, National Institute on Minority Health and Health Disparities

Bottom Row (left to right):
William Riley, Ph.D., Director, NIH Office of Behavioral and Social Sciences Research
Tara A. Schwetz, Ph.D., Associate Deputy Director, National Institutes of Health and Acting Director, National Institute of Nursing Research
Nora D. Volkow, M.D., Director, National Institute on Drug Abuse

NLM Strategic Opportunities and Challenges: We Want to Hear from You!

Guest post by Mike Huerta, PhD, director of the Office of Strategic Initiatives and associate director of the National Library of Medicine, National Institutes of Health.

A Platform for Biomedical Discovery and Data-Powered Health,” NLM’s current 10-year strategic plan, envisions three goals with a 2027 horizon: 

  1. Accelerate discovery and advance health through data-driven research.
  2. Reach more people in more ways through enhanced dissemination and engagement.
  3. Build a workforce for data-driven research and health.

Discussions among panels of experts, conversations with NLM’s diverse stakeholder communities, and feedback from the public informed this ambitious plan. In the years since the plan was issued, in 2017, NLM has conducted more than 100 initiatives, projects, and other activities in pursuit of these goals.

Shaping the continuing implementation of NLM’s strategic plan

To make sure that our strategic plan implementation activities remain relevant and attuned to the needs of the public, NLM released a Request for Information (RFI) to learn from you about any related major opportunities or challenges that have arisen or become significantly more important since the plan was created.

While NLM has been advancing its strategic goals, there have been many changes in science, technology, and society that are relevant to our mission. For example, the use of artificial intelligence in research and health care has greatly increased, biomedical scientists are increasingly using nontraditional channels to share their research results, and, of course, there is an urgent need to understand the novel coronavirus and figure out how to quell the pandemic that has affected so many lives around the world. 

Your feedback will help us ensure that the implementation of NLM’s strategic plan remains current. Responses to the RFI will be accepted through October 19, 2020.

Progress toward the plan’s goals

NLM is leading the way in the use of large data sets to make new discoveries and achieve greater efficiencies in the fields of data science and health care — all in pursuit of our current strategic goals. Recent examples of how we have accelerated discovery and data-driven health research include:

  • Expanding and enhancing data science research in both our extramural and intramural research programs
  • Moving dozens of terabytes of genomic data and associated tools to a secure commercial cloud solution to allow researchers to tackle new questions in new ways
  • Leading the promotion and adoption of health-related data standards, thereby adding value to extramural and intramural research across NIH
  • Stimulating cross-NIH discussions of the ethical and societal implications of computational algorithms and artificial intelligence 

NLM also carried out a broad set of analyses, assessments, and evaluations to improve our products, services, and infrastructure and bolster their sustainability.

Reaching more people in more ways through enhanced dissemination and engagement, raising awareness, and ensuring optimal use of NLM’s many diverse offerings have been supported by a major reorganization of NLM that consolidated many important engagement and training activities in one office while maintaining deep channels of communication with subject matter experts across different parts of the Library. NLM has also advanced this goal through:

  • Public communication initiatives to reinforce the recognition of NLM as a trusted source of information
  • Investments in systems to enhance information delivery, which include user experience and usability studies of ClinicalTrials.gov and the NIH Common Data Elements Repository to ensure that users can find the information they need with ease

NLM has implemented many successful strategic activities to build a workforce for data-driven research and health. These activities include multifaceted approaches to meeting the needs of NLM staff, emerging professionals, researchers, and health care professionals, such as:

  • Conducting a comprehensive analysis of data science training at NIH. This involved working with our extramural communities, in both research labs and libraries, as well as with program and other NIH staff.
  • Convening thought leaders from the library community to produce a road map to identify and develop the skill set that librarians need to advance efforts in data science and open science.
  • Hosting workshops to train intramural scientists across NIH on data science tools and approaches, along with a targeted training program in data science engaging more than a thousand NLM staff members.

These activities have been highly influential in developing a data-savvy biomedical workforce comprising scientists, librarians, and NIH staff. The aforementioned NLM staff training program is now in its second year and serves as a model for developing data science capacity across the federal workforce.

Where you come in

I urge you to respond to the RFI to share your perspective and also to encourage your friends and colleagues to do the same. With your help, NLM can continue to be a leader in data science and open science and continue to innovate as a national library, fueling biomedical research and health care advances as an invaluable asset to the public and professionals everywhere.   

Dr. Huerta directs the Office of Strategic Initiatives to identify, implement, and assess the strategic direction of NLM. In his 30 years at NIH, he has led many trans-NIH research initiatives and helped establish neuroinformatics as a field. Dr. Huerta joined NIH’s National Institute of Mental Health in 1991, before moving to NLM in 2011.

Watch All About It!

Guest post by Bart Trawick, PhD, director of the Customer Services Division at the National Library of Medicine’s National Center for Biotechnology Information, National Institutes of Health.

NLM’s PubMed is the most heavily used biomedical literature citation database in the world. PubMed provides free access to more than 30 million citations and is searched by more than 2.5 million users daily. It is a critical resource for helping researchers, health care professionals, students, and the public share information and learn more about the latest developments in life sciences.

Earlier this year, NLM launched an updated version of PubMed with an enhanced design that provides advanced technology to improve the user experience on mobile as well as desktop devices. This modern interface includes updated web elements for easier navigation and enhanced search results, including previews with highlighted text snippets that can help you scan your results.

Instead of telling you more about these new features and how they work, I invite you to check out a few of them in this video.

Click to watch and learn more about a few of PubMed’s exciting features.

Video Transcript (below):

PubMed is the most heavily used biomedical citation database in the world, guiding over two and a half million users per day to the latest advances in life sciences research. We’re constantly improving PubMed to meet the needs of its diverse user base and to take advantage of ever-evolving internet technologies and standards.

The latest version of PubMed, released in May 2020, is the product of hundreds of hours of stakeholder engagement and research undertaken to give you a better experience.

And it’s not the first time we’ve made big changes.

From its humble beginnings in 1997, PubMed now comprises more than 30 million biomedical literature citations from MEDLINE, life science journals, and online books. These citations may include links to full-text content in PubMed Central and publisher websites to take you directly to the information you need.

To be sustainable going forward, the latest release of PubMed required major changes including new databases, web architecture and cloud delivery. Combined, these changes resulted in a much more resilient version of PubMed with a modern design that looks and works great on your desktop, your laptop, and your mobile device!

We realize this feels like a big change, but we’ve been working hard to help everyone make the transition to the new site and have continued to make improvements along the way.

Here are a couple new and revamped features designed to improve the user experience.

The new Cite button makes it easy to retrieve styled citations you can copy and paste into a document or download an .nbib file to use with your reference manager software.

Using the Cite button for an item will open a pop-up window where you can copy the citation formatted in four popular styles.

Automatic Term Mapping, also called “ATM”, was present in the legacy PubMed, but it’s been expanded to include additional British and American spellings, singular and plural word forms, and other synonyms to provide more consistent and comprehensive search retrieval.

We’re always looking for ways to improve PubMed. Just as we’ve done for the past 24 years, we’ll continue to add features and data to stay current as technology, publishing standards, and our users’ needs evolve.

Please think about other ways that NLM can help you, and share your ideas  with us.  

Headshot image of Bart Trawick, PhD

As director of the Customer Services Division, Dr. Trawick works to connect customers with the vast information resources available from NLM’s National Center for Biotechnology Information. He has also worked to support the National Institutes of Health Public Access Policy since its establishment in 2005. Dr. Trawick is a graduate of Texas A&M University and the University of Texas Health Science Center at Houston.

The Significance of Network Biology

Guest post by Teresa Przytycka, PhD, Senior Investigator, Computational and Systems Biology section of the Computational Biology Branch at the National Library of Medicine’s National Center for Biotechnology Information, National Institutes of Health.

The functioning of any complex system involves interactions between elements of that system. This is true at the cellular level, the macro level, and every point in between.

For example, within a cell, diverse molecules coordinate their activities and work together to carry out specific cellular functions. Cells then interact with each other to shape an organism’s development, tissue-level organization, and immune response. In turn, the organisms themselves interact to form various types of connections. In the case of people, those connections form the backbone of social systems.

These many interactions, from the microscopic to the macroscopic, can be described as networks, which comprise nodes connected via links that designate the relationships between nodes.

But how can we discover which nodes are connected? And how can we learn about the nature of those connections?

My research group and I try to answer these questions using network analysis, that is, working at the network level to uncover insights about the underlying system.

We can trace the beginnings of network analysis (also known as graph theory in mathematical circles) to Gottfried Leibniz’s geometria situs (“geometry of position”), a mathematical discipline focused on the relationship between positions and objects. The first recorded application of this new way of thinking was the famous solution to the problem known as “The Bridges of Königsberg,” published by Leonhard Euler in 1736.

Königsberg (now Kaliningrad) straddles the Pregel River. In Euler’s time, seven bridges connected the various parts of the city, including two islands in the middle of the river. The question asked was whether one could chart a walk through the city that required crossing each bridge only once and return to the start.

Euler tackled this question using what we today call network theory. If the regions of Königsberg are nodes and the bridges are links, Euler showed that, for such a walk to be possible, each node must have an even number of links. Why an even number? Because if we cannot cross the same bridge twice, then for every way into each region of the city there must be a new way out. Because that property did not hold for Königsberg, Euler concluded that no such walk could be devised.

As Euler’s argument shows, representing a complex system as a network of nodes and links can help uncover properties of the system that might have otherwise been obscured.

In biology and medicine, such network-centric approaches coincided with the emergence of high-throughput experimental techniques and advanced methods for collecting and storing diverse biomedical data. The protein interaction network for yeast became one of the first large biological networks obtained from high-throughput experiments. Analyzing that network revealed that a small fraction of proteins interacted with a disproportionately large number of other proteins. Additional research showed that these “hub” proteins are essential to the cell’s survival.

This intriguing relationship between a network property and a biological property begged for an explanation.

Our 2008 paper demonstrated that the majority of protein hubs are essential because of their involvement in complex, densely connected modules that carry out functions essential for cell survival. These results illustrate that, in addition to reporting binary relationships between individual nodes, interaction networks encode hidden higher-level organization.

In many networks, including biological and social ones, groups of nodes that interact with each other more tightly than with the rest of the network can be identified. We call these groups “modules.” In the context of biological networks, modules are often associated with groups of genes that work together to perform a specific biological function. At the same time, we’re beginning to see that complex diseases, such as cancer, are more likely caused by the dysregulation of a specific functional module than a dysfunction of an individual gene. That’s why, in recent years, cancer research has turned its attention to identifying dysregulated modules.

This effort includes several methods developed by our research group—Module Cover, Mutual Exclusivity Module Cover, and BeWith. These methods combine information from the human-interaction network with disease-specific information, such as abnormally expressed or mutated genes, to identify disease-associated modules. These modules can shed light on the mechanism of the disease, suggesting areas for further study and possible means of intervention.

We also use networks to discover how information flows between individual nodes. For example, by applying the principles of current flow within an electric circuit, we have been able to identify the causal (altered) disease genes and the pathways they dysregulate, providing another way to discover groups of genes involved in a disease.

Unfortunately, most currently available interaction networks are static depictions of a dynamically changing system. They typically do not account for tissue types, developmental stages, disease status, and other factors. As a result, these networks cannot tell us the full story.

To consider these and other factors, we need a context-specific network. But to build one, we must use context-specific data. How can we do that, given the myriad conditions we must consider? Our new method, NetREX, moves us in that direction.

Network biology has facilitated progress in many areas of biomedical science. This simple, yet powerful, concept allows us to abstract the essence of relations between genes and proteins, predict interactions between drugs, study disease comorbidity, and discover important associations. Of course, discovering an association is just the first step in uncovering a mechanism, but it is often a crucial step.

headshot of Dr. Teresa Przytycka

Teresa M. Przytycka, PhD, leads the Algorithmic Methods in Computational and Systems Biology section at the National Center for Biotechnology Information. Dr. Przytycka is particularly interested in the dynamical properties of biological systems, including spatial, temporal and contextual variations, and exploring how such variations impact gene expression, the functioning of biological pathways, and the phenotype of the organism.