The 11th edition of Harrison's Principles of Internal Medicine welcomes Anthony Fauci to its editorial staff, in addition to more than 85 new contributors. While the organization of the book is similar to previous editions, major emphasis has been placed on disorders that affect multiple organ systems. Important advances in genetics, immunology, and oncology are emphasized. Many chapters of the book have been rewritten and describe major advances in internal medicine. Subjects that received only a paragraph or two of attention in previous editions are now covered in entire chapters. Among the chapters that have been extensively revised are the chapters on infections in the compromised host, on skin rashes in infections, on many of the viral infections, including cytomegalovirus and Epstein-Barr virus, on sexually transmitted diseases, on diabetes mellitus, on disorders of bone and mineral metabolism, and on lymphadenopathy and splenomegaly. The major revisions in these chapters and many

Harrison's Principles of Internal Medicine

What do a seventeenth-century mortality table (whose causes of death include "fainted in a bath," "frighted," and "itch"); the identification of South Africans during apartheid as European, Asian, colored, or black; and the separation of machine- from hand-washables have in common? All are examples of classification -- the scaffolding of information infrastructures. In Sorting Things Out, Geoffrey C. Bowker and Susan Leigh Star explore the role of categories and standards in shaping the modern world. In a clear and lively style, they investigate a variety of classification systems, including the International Classification of Diseases, the Nursing Interventions Classification, race classification under apartheid in South Africa, and the classification of viruses and of tuberculosis. The authors emphasize the role of invisibility in the process by which classification orders human interaction. They examine how categories are made and kept invisible, and how people can change this invisibility when necessary. They also explore systems of classification as part of the built information environment. Much as an urban historian would review highway permits and zoning decisions to tell a city's story, the authors review archives of classification design to understand how decisions have been made. Sorting Things Out has a moral agenda, for each standard and category valorizes some point of view and silences another. Standards and classifications produce advantage or suffering. Jobs are made and lost; some regions benefit at the expense of others. How these choices are made and how we think about that process are at the moral and political core of this work. The book is an important empirical source for understanding the building of information infrastructures.

https://www.reciis.icict.fiocruz.br/index.php/reciis/article/download/794/1436

Sorting Things Out: Classification and Its Consequences

The UMLS Metathesaurus, the largest thesaurus in the biomedical domain, provides a representation of biomedical knowledge consisting of concepts classified by semantic type and both hierarchical and non-hierarchical relationships among the concepts. This knowledge has proved useful for many applications including decision support systems, management of patient records, information retrieval (IR) and data mining. Gaining effective access to the knowledge is critical to the success of these applications. This paper describes MetaMap, a program developed at the National Library of Medicine (NLM) to map biomedical text to the Metathesaurus or, equivalently, to discover Metathesaurus concepts referred to in text. MetaMap uses a knowledge intensive approach based on symbolic, natural language processing (NLP) and computational linguistic techniques. Besides being applied for both IR and data mining applications, MetaMap is one of the foundations of NLM's Indexing Initiative System which is being applied to both semi-automatic and fully automatic indexing of the biomedical literature at the library.

Effective mapping of biomedical text to the UMLS Metathesaurus: the MetaMap program

This introduction presents the main motivations for the development of Description Logics (DLs) as a formalism for representing knowledge, as well as some important basic notions underlying all systems that have been created in the DL tradition. In addition, we provide the reader with an overview of the entire book and some guidelines for reading it. We first address the relationship between Description Logics and earlier semantic network and frame systems, which represent the original heritage of the field. We delve into some of the key problems encountered with the older efforts. Subsequently, we introduce the basic features of DL languages and related reasoning techniques. DL languages are then viewed as the core of knowledge representation systems, considering both the structure of a DL knowledge base and its associated reasoning services. The development of some implemented knowledge representation systems based on Description Logics and the first applications built with such systems are then reviewed. Finally, we address the relationship of Description Logics to other fields of Computer Science.We also discuss some extensions of the basic representation language machinery; these include features proposed for incorporation in the formalism that originally arose in implemented systems, and features proposed to cope with the needs of certain application domains.

https://assets.cambridge.org/97805218/76254/frontmatter/9780521876254_frontmatter.pdf

The Description Logic Handbook

https://www.acilci.net/wp-content/uploads/2014/02/Guidelines-for-reporting-reliability-and-agreement-studies-GRRAS-were-proposed.pdf

Guidelines for Reporting Reliability and Agreement Studies (GRRAS) were proposed.

We have mapped clinically used diagnostic terms from a legacy ambulatory care system to the separate controlled vocabulary of our central clinical information system. The methodology combines elements of lexical and morphologic text matching techniques, followed by manual physician review. Results of the automated matching algorithm before and after partial manual review are presented. The results of this effort will permit the migration of coded clinical data from one system to another. Output from the system after the term review process will be fed back to the target vocabulary via automated and semi-automated means to improve its clinical utility.

Mapping Clinically Useful Terminology to a Controlled Medical Vocabulary.

Controlled terminologies play an integral role in biomedical informatics applications whenever such applications use information to carry out symbolic reasoning. Early, prominent examples include Mycin [1], which included terms for clinical findings in its rules and presented diagnosis and treatment terms in its recommendations, and the Internist-1 system [2], which matched a list of symptom and physical finding terms against a knowledge base of disease terms. While PubMed [3], at the US National Library of Medicine (NLM), can carry out literature retrieval with simple text searching, it also makes use of controlled terms to focus that retrieval. Today, everything from automated health surveys to electronic health records makes use of some kind of controlled terminology to condense users’ input into a set of symbols that can be recognized and manipulated.

/pdf/high-quality-standard-controlled-healthcare-terminologies-3w0wj0g552.pdf

High-quality, Standard, Controlled Healthcare Terminologies Come of Age

Clinicians' patient care information needs are frequent and largely unmet. Online knowledge resources are available that can help clinicians meet these information needs. Yet, significant barriers limit the use of these resources within the clinical workflow. Infobuttons are clinical decision support tools that use the clinical context (e.g., institution, user, patient) within electronic health record (EHR) systems to anticipate clinicians' questions and provide automated links to relevant information in knowledge resources. This paper describes OpenInfobutton (www.openinfobutton.org): a standards-based, open source Web service that was designed to disseminate infobutton capabilities in multiple EHR systems and healthcare organizations. OpenInfobutton has been successfully integrated with 38 knowledge resources at 5 large healthcare organizations in the United States. We describe the OpenInfobutton architecture, knowledge resource integration, and experiences at five large healthcare organizations.

Disseminating context-specific access to online knowledge resources within electronic health record systems.

Attempts to link clinical information systems to on-line information resources date back over a decade The World Wide Web presents new opportunities to create such links, which we refer to as "infobuttons" This capability is partly due to the ease with which a link (called a Uniform Resource Locator, or URL) in one Web-based system can take users to another Web-based system, and partly due to the proliferation of high-quality Web-based resources Typically, contextual information from the clinical system (such as patient data) is passed to a search engine that is evoked and, in turn, presents search results to the user Impediments to infobutton development include customized programming to pass context information to the information resource, lack of standards for types and values of context information, variability of search engine interfaces, and a lack of understanding of clinicians' information needs We are addressing these limitations with an Infobutton Manager (IM) that provides a standardized interface for matching user contexts to information resources

Sharing infobuttons to resolve clinicians' information needs.

Medication reconciliation (MR) is a process that seeks to assure that the medications a patient is supposed to take are the same as what they are actually taking. We have developed a method in which medication information (consisting of both coded data and narrative text) is extracted from twelve sources from two clinical information systems and assembled into a chronological sequence of medication history, plans, and orders that correspond to periods before, during and after a hospital admission. We use natural language processing, a controlled terminology, and a medication classification system to create matrices that can be used to determine the initiation, changes and discontinuation of medications over time. We applied the process to a set of 17 patient records and successfully abstracted and summarized the medication data. This approach has implications for efforts to improve medication history-taking, order entry, and automated auditing of patient records for quality assurance.

James J. Cimino

Papers

Mapping Clinically Useful Terminology to a Controlled Medical Vocabulary.

High-quality, Standard, Controlled Healthcare Terminologies Come of Age

Disseminating context-specific access to online knowledge resources within electronic health record systems.

Sharing infobuttons to resolve clinicians' information needs.

Medication reconciliation using natural language processing and controlled terminologies.