Betsy L. Humphreys

The Unified Medical Language System: an informatics research collaboration.

In 1986, the National Library of Medicine (NLM) assembled a large multidisciplinary, multisite team to work on the Unified Medical Language System (UMLS), a collaborative research project aimed at reducing fundamental barriers to the application of computers to medicine. Beyond its tangible products, the UMLS Knowledge Sources, and its influence on the field of informatics, the UMLS project is an interesting case study in collaborative research and development. It illustrates the strengths and challenges of substantive collaboration among widely distributed research groups. Over the past decade, advances in computing and communications have minimized the technical difficulties associated with UMLS collaboration and also facilitated the development, dissemination, and use of the UMLS Knowledge Sources. The spread of the World Wide Web has increased the visibility of the information access problems caused by multiple vocabularies and many information sources which are the focus of UMLS work. The time is propitious for building on UMLS accomplishments and making more progress on the informatics research issues first highlighted by the UMLS project more than 10 years ago.

Relationships in Medical Subject Headings (MeSH)

Recent efforts to make some of the relationships within MeSH more explicit have led to a deeper understanding of the nature of these relationships. This chapter will explore the relationships represented in MeSH in the light of that understanding. Every term that occurs may be thought of as representing a concept. One or more terms, comprising one or more concepts, grouped together for important reasons, form a descriptor class. The descriptor class is the basic building block of the thesaurus. Relationships among concepts can be represented explicitly in the thesaurus, most notably as relationships within the descriptor class. Hierarchical relationships are at the level of the descriptor class. The hierarchies are key in allowing expanded retrievals. The hierarchical relationships, traditionally thought of as broader or narrower (parent-child) relationships, are better understood as representing broader and narrower retrieval sets. Nevertheless, these hierarchical relationships often reflect important broader-narrower relationships between preferred concepts in descriptor classes. Other types of relationships present in the thesaurus include associative relationships, such as the Pharmacologic Actions or see-related cross references, as well as forbidden combination expressions, such as the Entry Combination.

A consensus action agenda for achieving the national health information infrastructure.

Abstract Background Improving the safety, quality, and efficiency of health care will require immediate and ubiquitous access to complete patient information and decision support provided through a National Health Information Infrastructure (NHII). Methods To help define the action steps needed to achieve an NHII, the U.S. Department of Health and Human Services sponsored a national consensus conference in July 2003. Results Attendees favored a public–private coordination group to guide NHII activities, provide education, share resources, and monitor relevant metrics to mark progress. They identified financial incentives, health information standards, and overcoming a few important legal obstacles as key NHII enablers. Community and regional implementation projects, including consumer access to a personal health record, were seen as necessary to demonstrate comprehensive functional systems that can serve as models for the entire nation. Finally, the participants identified the need for increased funding for research on the impact of health information technology on patient safety and quality of care. Individuals, organizations, and federal agencies are using these consensus recommendations to guide NHII efforts.

Evaluating the Coverage of Controlled Health Data Terminologies: Report on the Results of the NLM/AHCPR Large Scale Vocabulary Test

OBJECTIVE To determine the extent to which a combination of existing machine-readable health terminologies cover the concepts and terms needed for a comprehensive controlled vocabulary for health information systems by carrying out a distributed national experiment using the Internet and the UMLS Knowledge Sources, lexical programs, and server. METHODS Using a specially designed Web-based interface to the UMLS Knowledge Source Server, participants searched the more than 30 vocabularies in the 1996 UMLS Metathesaurus and three planned additions to determine if concepts for which they desired controlled terminology were present or absent. For each term submitted, the interface presented a candidate exact match or a set of potential approximate matches from which the participant selected the most closely related concept. The interface captured a profile of the terms submitted by the participant and for each term searched, information about the concept (if any) selected by the participant. The term information was loaded into a database at NLM for review and analysis and was also available to be downloaded by the participant. A team of subject experts reviewed records to identify matches missed by participants and to correct any obvious errors in relationships. The editors of SNOMED International and the Read Codes were given a random sample of reviewed terms for which exact meaning matches were not found to identify exact matches that were missed or any valid combinations of concepts that were synonymous to input terms. The 1997 UMLS Metathesaurus was used in the semantic type and vocabulary source analysis because it included most of the three planned additions. RESULTS Sixty-three participants submitted a total of 41,127 terms, which represented 32,679 normalized strings. More than 80% of the terms submitted were wanted for parts of the patient record related to the patients condition. Following review, 58% of all submitted terms had exact meaning matches in the controlled vocabularies in the test, 41% had related concepts, and 1% were not found. Of the 28% of the terms which were narrower in meaning than a concept in the controlled vocabularies, 86% shared lexical items with the broader concept, but had additional modification. The percentage of exact meanings matches varied by specialty from 45% to 71%. Twenty-nine different vocabularies contained meanings for some of the 23,837 terms (a maximum of 12,707 discrete concepts) with exact meaning matches. Based on preliminary data and analysis, individual vocabularies contained < 1% to 63% of the terms and < 1% to 54% of the concepts. Only SNOMED International and the Read Codes had more than 60% of the terms and more than 50% of the concepts. CONCLUSIONS The combination of existing controlled vocabularies included in the test represents the meanings of the majority of the terminology needed to record patient conditions, providing substantially more exact matches than any individual vocabulary in the set. From a technical and organizational perspective, the test was successful and should serve as a useful model, both for distributed input to the enhancement of controlled vocabularies and for other kinds of collaborative informatics research.

A national agenda for public health informatics: summarized recommendations from the 2001 AMIA Spring Congress.

The AMIA 2001 Spring Congress brought together members of the the public health and informatics communities to develop a national agenda for public health informatics. Discussions of funding and governance; architecture and infrastructure; standards and vocabulary; research, evaluation, and best practices; privacy, confidentiality, and security; and training and workforce resulted in 74 recommendations with two key themes-that all stakeholders need to be engaged in coordinated activities related to public health information architecture, standards, confidentiality, best practices, and research; and that informatics training is needed throughout the public health workforce. Implementation of this consensus agenda will help promote progress in the application of information technology to improve public health.

Integrating Intimate Partner Violence Assessment and Intervention into Healthcare in the United States: A Systems Approach

The Institute of Medicine, United States Preventive Services Task Force (USPSTF), and national healthcare organizations recommend screening and counseling for intimate partner violence (IPV) within the US healthcare setting. The Affordable Care Act includes screening and brief counseling for IPV as part of required free preventive services for women. Thus, IPV screening and counseling must be implemented safely and effectively throughout the healthcare delivery system. Health professional education is one strategy for increasing screening and counseling in healthcare settings, but studies on improving screening and counseling for other health conditions highlight the critical role of making changes within the healthcare delivery system to drive desired improvements in clinician screening practices and health outcomes. This article outlines a systems approach to the implementation of IPV screening and counseling, with a focus on integrated health and advocacy service delivery to support identification and interventions, use of electronic health record (EHR) tools, and cross-sector partnerships. Practice and policy recommendations include (1) ensuring staff and clinician training in effective, client-centered IPV assessment that connects patients to support and services regardless of disclosure; (2) supporting enhancement of EHRs to prompt appropriate clinical care for IPV and facilitate capturing more detailed and standardized IPV data; and (3) integrating IPV care into quality and meaningful use measures. Research directions include studies across various health settings and populations, development of quality measures and patient-centered outcomes, and tests of multilevel approaches to improve the uptake and consistent implementation of evidence-informed IPV screening and counseling guidelines.

Electronic health record meets digital library: a new environment for achieving an old goal.

Linking the electronic health record to the digital library is a Web-era reformulation of the long-standing informatics goal of seamless integration of automated clinical data and relevant knowledge-based information to support informed decisions. The spread of the Internet, the development of the World Wide Web, and converging format standards for electronic health data and digital publications make effective linking increasingly feasible. Some existing systems link electronic health data and knowledge-based information in limited settings or limited ways. Yet many challenging informatics research problems remain to be solved before flexible and seamless linking becomes a reality and before systems become capable of delivering the specific piece of information needed at the time and place a decision must be made. Connecting the electronic health record to the digital library also requires positive resolution of important policy issues, including health data privacy, government encouragement of high-speed communications, electronic intellectual property rights, and standards for health data and for digital libraries. Both the research problems and the policy issues should be important priorities for the field of medical informatics.

A national agenda for public health informatics.

The American Medical Informatics Association 2001 Spring Congress brought together the public health and informatics communities to develop a national agenda for public health informatics. Discussions on funding and governance; architecture and infrastructure; standards and vocabulary; research, evaluation, and best practices; privacy, confidentiality, and security; and training and workforce resulted in 74 recommendations with two key themes: (1) all stakeholders need to be engaged in coordinated activities related to public health information architecture, standards, confidentiality, best practices, and research and (2) informatics training is needed throughout the public health workforce. Implementation of this consensus agenda will help promote progress in the application of information technology to improve public health.

A retrospective cohort study of structured abstracts in MEDLINE, 1992–2006

Structured abstracts contain distinct labeled sections (e.g., “RESULTS”). The MEDLINE/PubMed database incorporates English-language abstracts that appear in the journals that the US National Library of Medicine (NLM) indexes. If English-language structured abstracts appear in a journal that is indexed, the labels in these abstracts usually appear in all uppercase letters, generally followed by a colon, in MEDLINE/PubMed citations [1]. Several years after formats for more informative abstracts were proposed [2–,5], NLM studied the structured abstracts that appeared in MEDLINE from 1989–1991 as an initial step in exploring their utility in enhancing bibliographic retrieval [6]. This early study showed that structured abstracts were an emerging, but rapidly growing phenomenon; that MEDLINE records with structured abstracts tended to have more access points (Medical Subject Headings [MeSH] terms and text words) than MEDLINE records as a whole; and that there was significant variation in the structured abstract formats that different journals prescribed. Implementation of structured abstracts by biomedical journals has been examined on a small scale in the clinical medicine domain [7, 8], but no large-scale examination across all of MEDLINE has occurred since the first exploratory study by NLM. Hence, the objective of this study was to conduct a retrospective cohort study to measure and characterize the growth in structured abstracts in MEDLINE since 1991, with a view, again, toward exploring their utility in enhancing information display and retrieval.

Basic science: Bedrock of progress

Almost 4 years ago, one of us (F.S.C.) wrote an Editorial ([ 1 ][1]) affirming the continued importance of basic research to the National Institutes of Health (NIH) mission. The Editorial emphasized that basic scientific discovery is the engine that powers the biomedical enterprise, and NIH