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The Role of the National Library of Medicine in Advancing the Science of Health Disparities

Brennan, Patricia F., RN, PhD

doi: 10.1097/MLR.0000000000001074

National Library of Medicine, National Institutes of Health, Bethesda, MD

The author declares no conflict of interest.

Reprints: Patricia F. Brennan, RN, PhD, 8600 Rockville Pike, Building 38, Bethesda, MD 20894. E-mail:

It’s likely that the National Library of Medicine (NLM) will continue playing a key role in every major biomedical and clinical discovery, just as it has done for the past 40 years. Our world-class citation database PubMed ( introduces investigators to foundational literature research supporting new inquiry as well as a pathway to papers documenting new results. NLM’s genomic and image data repositories, such as dbGaP and GenBank, foster data sharing and aid in characterizing new genomic variants. Through NLM’s intramural and extramural research programs, we develop new data science and biomedical informatics methods. And NLM’s outreach classes, programs, and training materials bring to scientists and citizens globally, the skills needed to effectively use NLM resources. NLM is a key partner in the discovery and translation of science into service and sharpens the attention to and understating of how health information and health informatics improves the characterization of and response to health disparities.

As part of this special issue of Medical Care exploring the role of health information in advancing the science of health disparities, NLM is pleased to share our work on role of health informatics and its impact on patient care and research, especially among minority and health disparities populations. NLM is strongly committed to support the National Institute on Minority Health (NIMHD) and Disparities’ Scientific Advancement Plan, as evident through our strategies to make the scientific literature accessible and available; to ensure our data repositories are safe, secure, and reflective of a diverse population; and to accelerate research that is responsive to a diverse population and to deliver outreach services globally.

NLM helps advance the science of health disparities by: (1) making the research literature that addresses health disparities research available and accessible; (2) supporting research that addresses some of the information-based precursors, consequences, and mitigators of health disparities; (3) ensuring that the formal terminology systems used to label health problems and annotate the health care literature are sufficiently broad to capture the breadth of the human experience; and (4) using pathways that disseminate relevant literature to people who can use it.

Finding literature relevant to minority health and health disparities within our massive PubMed literature repository presents significant challenges, even to the most sophisticated PubMed user. We provide targeted access through preformulated specialized queries to our citation database. We create and maintain PubMed Special Queries.1 Using the specialized query “health disparities,” a user can identify and locate the most recent articles by retrieving those that match a broad set of prepopulated key words including specific racial and ethnic designation (African Americans), indicators relevant to health disparities (culturally competent care, social inequities) or major headings (social dominants of health). By registering for the MyNCBI service, users can refine Special Queries with terms and phrases germane to their interests. Regular updates can be delivered via email periodically at the discretion of the user.

NLM also supports research at the intersection of informatics and health disparities. An example of this research is the work of Dean Schillinger, MD, of the University of California, San Francisco. His ECLIPPSE study2 employs computational linguistics to improve the understandability of patient-provided email communication. Schillinger’s team is developing an assessment survey to generate a measure of patient literacy, which can guide the tailoring of information provided to patients. The application of this assessment will result in the provision of information to patients that can be more easily comprehended.

In other research efforts, the Library aims to reduce health disparities by displaying information to patients and clinicians in ways that makes it more understandable. Zeng, PhD,3 of the University of Utah School of Medicine, and her team developed and evaluated pictographs and other visual displays of information that improved patients’ understanding of clinical instructions. Extensions of their work helped patients make better choices taking into consideration complex numerical estimates of medication efficacy or a drug’s side effects.

NLM supports collaborations between investigators in the community and its residents to determine ways to present information and make it locally relevant. Rita Kukafka, DrPH, and her team at the Columbia University Mailman School of Public Health demonstrated the positive value of participatory design processes when developing localized health information resources.4 The team then created the Conexion project to develop and evaluate whether high-quality information, customized by local information, out performs generic, high-quality information without customization in terms of patient understanding and management of chronic disease (depression, diabetes). Other investigators took a public information perspective. Bragg et al5 from Yale University built on their early work of sports endorsement on food choice to demonstrate the role of racially targeted food advertising on obesity. Kwate, associate professor of Africana Studies at Rutgers University, integrated geography, racism, and the penetration of fast food outlets in minority neighborhoods.6

One of the most important and least visible is the role of NLM in ensuring that formal vocabularies used to describe people, health problems, and health care processes are sufficiently robust to encompass the full range of health as experienced across all people, all populations, and all communities. In this data-intensive epoch of health care, people will be known through their data. It becomes essential that those data include indicators and the data captured in the course of clinical care becomes the indicators of what constitutes contemporary health care services. In addition, it is essential that there be sufficiently broad and diverse formal terms for a range of racial designations, ethnic characterizations, and sex identity. The work of NLM ensures that the data used to characterize people, their health problems, and the nature and effectiveness of clinical care be true and valid indicators of people, health problems, and care processes so delving into the nature of information is central to ensuring clear and accurate descriptions of real-world experience.

To foster rigor and reproductivity across research projects, the National Institutes of Health encourages the use of common data elements (CDEs7) in clinical research, patient registries, and other human subject research. These CDEs designate acceptable ways to measure human phenomena, such as anxiety, to improve data quality and opportunities for comparison and combination of data from multiple studies and with electronic health records. This work contributes to the quality and consistency of key demographic information and supports the capture of more granular information where needed. The NIMHD is partnering with the NLM and other Institutes and Centers to establish “health equity CDEs” through a supplement to the PhenX toolkit.8

Through its National Network of Libraries of Medicine and other efforts, NLM employs its community outreach services as an interpersonal, human network to provide community-specific pathways that make sure the research reported in NLM resources can be used by all people, in ways that are culturally congruent. The Environmental Health Information Partnership program includes Historically Black Colleges and Universities, a Predominately Black Institution, Hispanic-Serving Institutions, Tribal Colleges and Universities, and an Alaska Native-Serving Institution. This Partnership affords several benefits in advancing the science of health disparities. First, it provides direct engagement with the early stages of the pipeline in the development of scholars likely to contribute to the science of health disparities and our understanding of how to use science to mitigate them. Second, the program provides a pathway for translating research findings into health interventions in minority communities. Finally, the partnership supports a close conversation between NLM and highly diverse communities, providing early indications of new opportunities for research.

The NLM makes general and distinct contributions to advance the science of health disparities. It maintains a citation database that ensures access to the research literature and discoverability of new research. It fosters the conduct of research that illuminates how information provision can enhance or disrupt community-level health outcomes that may vary disproportionately based on the ethnic or racial status of a person, or on their sex identity. Finally, NLM uses its vast human network to make sure that the beneficiaries of the research literature can access and make use of this great national treasure.

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1. PubMed Special Queries. Directory of topic specific PubMed queries. 2005. Available at: Accessed September 7, 2018.
2. Schillinger D, McNamara D, Crossley S, et al. The next frontier in communication and the ECLIPPSE study: bridging the linguistic divide in secure messaging. J Diabetes Res. 2017;2017:1348242.
3. Zeng Q, Tse T, Divita G, et al. Term identification methods for consumer health vocabulary development. J Med Internet Res. 2007;9:e4.
4. Millery M, Ramos W, Lien C, et al. Design of a community-engaged health informatics platform with an architecture of participation. AMIA Annu Symp Proc. 2015;2015:905–914.
5. Bragg MA, Liu PJ, Roberto CA, et al. The use of sports references in marketing of food and beverage products in supermarkets. Public Health Nutr. 2013;16:738–742.
6. Kwate NO, Loh JM. Separate and unequal: the influence of neighborhood and school characteristics on spatial proximity between fast food and schools. Prev Med. 2010;51:153–156.
7. Common Data Element (CDE) Resource Portal. 2012. Available at: Accessed October 20, 2018.
8. PhenX Toolkit. 2007. Available at: Accessed October 20, 2018.
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