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PubMed2006

Developing a data dictionary for the irish nursing minimum dataset.

One of the challenges in health care in Ireland is the relatively slow acceptance of standardised clinical information systems. Yet the national Irish health reform programme indicates that an Electronic Health Care Record (EHCR) will be implemented on a phased basis. [3-5]. While nursing has a key role in ensuring the quality and comparability of health information, the so- called 'invisibility' of some nursing activities makes this a challenging aim to achieve [3-5]. Any integrated health care system requires the adoption of uniform standards for electronic data exchange [1-2]. One of the pre-requisites for uniform standards is the composition of a data dictionary. Inadequate definition of data elements in a particular dataset hinders the development of an integrated data depository or electronic health care record (EHCR). This paper outlines how work on the data dictionary for the Irish Nursing Minimum Dataset (INMDS) has addressed this issue. Data set elements were devised on the basis of a large scale empirical research programme. ISO 18104, the reference terminology for nursing [6], was used to cross-map the data set elements with semantic domains, categories and links and data set items were dissected.

Databases as Topic↗
PubMed1989

The data dictionary--a controlled vocabulary for integrating clinical databases and medical knowledge bases.

The medical information systems of the future will probably include the entire medical record as well as a knowledge base, providing decision support for the physician during patient care. Data dictionaries will play an important role in integrating the medical knowledge bases with the clinical databases. This article presents an infological data model of such an integrated medical information system. Medical events, medical terms, and medical facts are the basic concepts that constitute the model. To allow the transfer of information and knowledge between systems, the data dictionary should be organized with regard to several common classification schemes of medical nomenclature.

Database Management Systems↗
PubMedDate not supplied

Motivation and reinforcement. Interdisciplinary dictionary.

Pavlov (1954) considered the significance of various manifestations of the higher nervous system as a necessary preliminary condition of brain mechanisms. He wrote, "First of all it is important to comprehend psychologically and then translate into physiological language." Unfortunately, there are no conventional definitions of such notions as need, motivation, emotion, reinforcement, consciousness, will, etc. I. M. Sechenov (1952) wrote, more than a century ago, "...try to speak about one and the same subject with psychologists of different schools--each school has a new opinion; and if you start, by comparison, a conversation about sound, light, electricity with a physicist of any country--you'll receive, essentially, the same responses from all of them." There is a need to create such theoretic conceptions which would be initially of an interdisciplinary character and would be useful not only in one, but in a number of special fields of science, such as psychology, physiology, and sociology. In this article the author suggests a brief dictionary of terms, based on the need-informational approach to the study of the psyche and behavior. These were created over the last 25 years (Simonov 1986).

Dictionaries as Topic↗
PubMed2001

A commented dictionary of techniques for genotyping.

Several tools, differing in their technical and practical parameters, are available for the detection of point mutations as well as small deletions and insertions. In this article, a dictionary featuring over fifty methods for detection of mutation is presented. The distinguishing principle for each method is briefly explained. Sorting of and discussion on the methods give the reader a brief introduction to the field of genotyping.

Genotype↗
PubMed1999

The HLA dictionary 1999: a summary of HLA-A, -B, -C, -DRB1/3/4/5, -DQB1 alleles and their association with serologically defined HLA-A, -B, -C, -DR, and -DQ antigens.

This report presents serologic equivalents of 90 HLA-A, 190 HLA-B, and 145 HLA-DRB1 alleles. The equivalents cover over 70% of the presently identified HLA-A, -B, and -DRB1 alleles. The dictionary is an update of the one published in 1997 and now also includes equivalents for HLA-C, DRB3, DRB4, DRB5, and DQB1 alleles. The data summarize information obtained by the WHO HLA Nomenclature Committee, the International Cell Exchange (UCLA), the National Marrow Donor Program (NMDP), and by individual laboratories. In addition, a listing is provided of alleles that are expressed as antigens with serologic reaction patterns that differ from the well-established HLA specificities and that often lack official WHO nomenclature. The provided equivalents will be useful in guiding searches for unrelated donors in which patients and/or potential donors are typed by either serology or DNA-based methods. These equivalents will also serve typing and matching procedures for organ transplant programs where HLA typings from donors and from recipients on waiting lists represent mixtures of serologic and molecular typings. Some guidelines are provided for the use of appropriate WHO HLA nomenclature for serologic typings and for generic and allele specific typings obtained with molecular methods. The tables with HLA equivalents and the questionnaire for submission of serology on poorly identified alleles will also be available at the WMDA web page: www.bmdw.org/wmda.

Alleles↗
PubMed2000

The use of a medical dictionary for regulatory activities terminology (MedDRA) in prescription-event monitoring in Japan (J-PEM).

The Medical Dictionary for Regulatory Activities Terminology (MedDRA) version 2.1 (V2.1) was released in March 1999 accompanied by the MedDRA/J V2.1J specifically for Japanese users. In prescription-event monitoring in Japan (J-PEM), we have employed the MedDRA/J for data entry, signal generation and event listing. In J-PEM, the lowest level terms (LLTs) in the MedDRA/J are used in data entry because the richness of LLTs is judged to be advantageous. A signal is generated normally at the preferred term (PT) level, but it has been found that various reporters describe the same event using descriptions that are potentially encoded by LLTs under different PTs. In addition, some PTs are considered too specific to generate the proper signal. In the system used in J-PEM, when an LLT is selected as a candidate to encode an event, another LLT under a different PT, if any, is displayed on the computer screen so that it may be coded instead of, or in addition to, the candidate LLT. The five-level structure of the MedDRA is used when listing events but some modification is required to generate a functional event list.

Adverse Drug Reaction Reporting Systems↗
PubMed1999

Homonyms and synonyms in the Dictionary of Interfaces in Proteins (DIP).

MOTIVATION: Should reports on molecular mimicry in particular cases, e.g. responsible for cross-reactivity, be considered as accidental or as a general principle in protein evolution? To answer this question, two types of similarity have to be considered: those in homologues (synonyms) and resemblance between patches from unrelated proteins (homonyms). RESULTS: All interfaces from known protein structures were collected in a comprehensive data bank [Dictionary of Interfaces in Proteins (DIP)]. A fast, sequence-independent, three-dimensional superposition procedure was developed to search automatically for geometrically similar surface areas. Surprisingly, we found a large number of structurally similar interfaces on the surface of unrelated proteins. Even patches from different types of secondary structure were found resembling each other. The putative functional meaning of homonyms is demonstrated with striking examples.

Algorithms↗
PubMed2006

Building an abbreviation dictionary using a term recognition approach.

MOTIVATION: Acronyms result from a highly productive type of term variation and trigger the need for an acronym dictionary to establish associations between acronyms and their expanded forms. RESULTS: We propose a novel method for recognizing acronym definitions in a text collection. Assuming a word sequence co-occurring frequently with a parenthetical expression to be a potential expanded form, our method identifies acronym definitions in a similar manner to the statistical term recognition task. Applied to the whole MEDLINE (7 811 582 abstracts), the implemented system extracted 886 755 acronym candidates and recognized 300 954 expanded forms in reasonable time. Our method outperformed base-line systems, achieving 99% precision and 82-95% recall on our evaluation corpus that roughly emulates the whole MEDLINE. AVAILABILITY AND SUPPLEMENTARY INFORMATION: The implementations and supplementary information are available at our web site: http://www.chokkan.org/research/acromine/

Abbreviations as Topic↗
PubMed2007

MinSet: a general approach to derive maximally representative database subsets by using fragment dictionaries and its application to the SCOP database.

MOTIVATION: The size of current protein databases is a challenge for many Bioinformatics applications, both in terms of processing speed and information redundancy. It may be therefore desirable to efficiently reduce the database of interest to a maximally representative subset. RESULTS: The MinSet method employs a combination of a Suffix Tree and a Genetic Algorithm for the generation, selection and assessment of database subsets. The approach is generally applicable to any type of string-encoded data, allowing for a drastic reduction of the database size whilst retaining most of the information contained in the original set. We demonstrate the performance of the method on a database of protein domain structures encoded as strings. We used the SCOP40 domain database by translating protein structures into character strings by means of a structural alphabet and by extracting optimized subsets according to an entropy score that is based on a constant-length fragment dictionary. Therefore, optimized subsets are maximally representative for the distribution and range of local structures. Subsets containing only 10% of the SCOP structure classes show a coverage of >90% for fragments of length 1-4. AVAILABILITY: http://mathbio.nimr.mrc.ac.uk/~jkleinj/MinSet. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Algorithms↗
PubMedDate not supplied

From data to knowledge through concept-oriented terminologies: experience with the Medical Entities Dictionary.

Knowledge representation involves enumeration of conceptual symbols and arrangement of these symbols into some meaningful structure. Medical knowledge representation has traditionally focused more on the structure than the symbols. Several significant efforts are under way, at local, national, and international levels, to address the representation of the symbols though the creation of high-quality terminologies that are themselves knowledge based. This paper reviews these efforts, including the Medical Entities Dictionary (MED) in use at Columbia University and the New York Presbyterian Hospital. A decade's experience with the MED is summarized to serve as a proof-of-concept that knowledge-based terminologies can support the use of coded patient data for a variety of knowledge-based activities, including the improved understanding of patient data, the access of information sources relevant to specific patient care problems, the application of expert systems directly to the care of patients, and the discovery of new medical knowledge. The terminological knowledge in the MED has also been used successfully to support clinical application development and maintenance, including that of the MED itself. On the basis of this experience, current efforts to create standard knowledge-based terminologies appear to be justified.

Artificial Intelligence↗
PubMed2005

The Adult Mouse Anatomical Dictionary: a tool for annotating and integrating data.

We have developed an ontology to provide standardized nomenclature for anatomical terms in the postnatal mouse. The Adult Mouse Anatomical Dictionary is structured as a directed acyclic graph, and is organized hierarchically both spatially and functionally. The ontology will be used to annotate and integrate different types of data pertinent to anatomy, such as gene expression patterns and phenotype information, which will contribute to an integrated description of biological phenomena in the mouse.

Animals↗
PubMedDate not supplied

Creating an online dictionary of abbreviations from MEDLINE.

OBJECTIVE: The growth of the biomedical literature presents special challenges for both human readers and automatic algorithms. One such challenge derives from the common and uncontrolled use of abbreviations in the literature. Each additional abbreviation increases the effective size of the vocabulary for a field. Therefore, to create an automatically generated and maintained lexicon of abbreviations, we have developed an algorithm to match abbreviations in text with their expansions. DESIGN: Our method uses a statistical learning algorithm, logistic regression, to score abbreviation expansions based on their resemblance to a training set of human-annotated abbreviations. We applied it to Medstract, a corpus of MEDLINE abstracts in which abbreviations and their expansions have been manually annotated. We then ran the algorithm on all abstracts in MEDLINE, creating a dictionary of biomedical abbreviations. To test the coverage of the database, we used an independently created list of abbreviations from the China Medical Tribune. MEASUREMENTS: We measured the recall and precision of the algorithm in identifying abbreviations from the Medstract corpus. We also measured the recall when searching for abbreviations from the China Medical Tribune against the database. RESULTS: On the Medstract corpus, our algorithm achieves up to 83% recall at 80% precision. Applying the algorithm to all of MEDLINE yielded a database of 781,632 high-scoring abbreviations. Of all the abbreviations in the list from the China Medical Tribune, 88% were in the database. CONCLUSION: We have developed an algorithm to identify abbreviations from text. We are making this available as a public abbreviation server at \url[http://abbreviation.stanford.edu/].

Abbreviations as Topic↗
PubMed2003

Integrating nursing diagnostic concepts into the medical entities dictionary using the ISO Reference Terminology Model for Nursing Diagnosis.

OBJECTIVE: The purposes of the study were (1) to evaluate the usefulness of the International Standards Organization (ISO) Reference Terminology Model for Nursing Diagnoses as a terminology model for defining nursing diagnostic concepts in the Medical Entities Dictionary (MED) and (2) to create the additional hierarchical structures required for integration of nursing diagnostic concepts into the MED. DESIGN AND MEASUREMENTS: The authors dissected nursing diagnostic terms from two source terminologies (Home Health Care Classification and the Omaha System) into the semantic categories of the ISO model. Consistent with the ISO model, they selected Focus and Judgment as required semantic categories for creating intensional definitions of nursing diagnostic concepts in the MED. Because the MED does not include Focus and Judgment hierarchies, the authors developed them to define the nursing diagnostic concepts. RESULTS: The ISO model was sufficient for dissecting the source terminologies into atomic terms. The authors identified 162 unique focus concepts from the 266 nursing diagnosis terms for inclusion in the Focus hierarchy. For the Judgment hierarchy, the authors precoordinated Judgment and Potentiality instead of using Potentiality as a qualifier of Judgment as in the ISO model. Impairment and Alteration were the most frequently occurring judgments. CONCLUSIONS: Nursing care represents a large proportion of health care activities; thus, it is vital that terms used by nurses are integrated into concept-oriented terminologies that provide broad coverage for the domain of health care. This study supports the utility of the ISO Reference Terminology Model for Nursing Diagnoses as a facilitator for the integration process.

Dictionaries, Medical as Topic↗
PubMed2006

Evaluation of the expressiveness of an ICNP-based nursing data dictionary in a computerized nursing record system.

This study evaluated the domain completeness and expressiveness issues of the International Classification for Nursing Practice-based (ICNP) nursing data dictionary (NDD) through its application in an enterprise electronic medical record (EMR) system as a standard vocabulary at a single tertiary hospital in Korea. Data from 2,262 inpatients obtained over a period of 9 weeks (May to July 2003) were extracted from the EMR system for analysis. Among the 530,218 data-input events, 401,190 (75.7%) were entered from the NDD, 20,550 (3.9%) used only free text, and 108,478 (20.4%) used a combination of coded data and free text. A content analysis of the free-text events showed that 80.3% of the expressions could be found in the NDD, whereas 10.9% were context-specific expressions such as direct quotations of patient complaints and responses, and references to the care plan or orders of physicians. A total of 7.8% of the expressions was used for a supplementary purpose such as adding a conjunction or end verb to make an expression appear as natural language. Only 1.0% of the expressions were identified as not being covered by the NDD. This evaluation study demonstrates that the ICNP-based NDD has sufficient power to cover most of the expressions used in a clinical nursing setting.

Dictionaries as Topic↗
PubMed1999

The medical dictionary for regulatory activities (MedDRA).

The International Conference on Harmonisation has agreed upon the structure and content of the Medical Dictionary for Regulatory Activities (MedDRA) version 2.0 which should become available in the early part of 1999. This medical terminology is intended for use in the pre- and postmarketing phases of the medicines regulatory process, covering diagnoses, symptoms and signs, adverse drug reactions and therapeutic indications, the names and qualitative results of investigations, surgical and medical procedures, and medical/social history. It can be used for recording adverse events and medical history in clinical trials, in the analysis and tabulations of data from these trials and in the expedited submission of safety data to government regulatory authorities, as well as in constructing standard product information and documentation for applications for marketing authorisation. After licensing of a medicine, it may be used in pharmacovigilance and is expected to be the preferred terminology for international electronic regulatory communication. MedDRA is a hierarchical terminology with 5 levels and is multiaxial: terms may exist in more than 1 vertical axis, providing specificity of terms for data entry and flexibility in data retrieval. Terms in MedDRA were derived from several sources including the WHO's adverse reaction terminology (WHO-ART), Coding Symbols for a Thesaurus of Adverse Reaction Terms (COSTART), International Classification of Diseases (ICD) 9 and ICD9-CM. It will be maintained, further developed and distributed by a Maintenance Support Services Organisation (MSSO). It is anticipated that using MedDRA will improve the quality of data captured on databases, support effective analysis by providing clinically relevant groupings of terms and facilitate electronic communication of data, although as a new tool, users will need to invest time in gaining expertise in its use.

Adverse Drug Reaction Reporting Systems↗
PubMed2002

Effects of coding dictionary on signal generation: a consideration of use of MedDRA compared with WHO-ART.

To support signal generation a terminology should facilitate recognition of medical conditions by using terms which represent unique concepts, providing appropriate, homogeneous grouping of related terms. It should allow intuitive or mathematical identification of adverse events reaching a threshold frequency or with disproportionate incidence, permit identification of important events which are commonly drug-related, and support recognition of new syndromes. It is probable that the Medical Dictionary for Regulatory Activities (MedDRA) preferred terms (PTs) or high level terms (HLTs) will be used to represent adverse events for the purposes of signal generation. A comparison with 315 WHO Adverse Reaction Terminology (WHO-ART) PTs showed that for about 72% of WHO-ART PTs, there were one or two corresponding MedDRA PTs. However, there were instances where there were many MedDRA PTs corresponding to single WHO-ART PTs. In many cases, MedDRA HLTs grouped large numbers of PTs and sometimes there could be problems when a single HLT comprises PTs which represent very different medical concepts, or conditions which differ greatly in their clinical importance. Further studies are needed to compare the way in which identical data sets coded with MedDRA and with other terminologies actually function in generating and exploring signals using the same methods of detection and evaluation.

Adverse Drug Reaction Reporting Systems↗
PubMed2003

Methods and pitfalls in searching drug safety databases utilising the Medical Dictionary for Regulatory Activities (MedDRA).

The Medical Dictionary for Regulatory Activities (MedDRA) is a unified standard terminology for recording and reporting adverse drug event data. Its introduction is widely seen as a significant improvement on the previous situation, where a multitude of terminologies of widely varying scope and quality were in use. However, there are some complexities that may cause difficulties, and these will form the focus for this paper. Two methods of searching MedDRA-coded databases are described: searching based on term selection from all of MedDRA and searching based on terms in the safety database. There are several potential traps for the unwary in safety searches. There may be multiple locations of relevant terms within a system organ class (SOC) and lack of recognition of appropriate group terms; the user may think that group terms are more inclusive than is the case. MedDRA may distribute terms relevant to one medical condition across several primary SOCs. If the database supports the MedDRA model, it is possible to perform multiaxial searching: while this may help find terms that might have been missed, it is still necessary to consider the entire contents of the SOCs to find all relevant terms and there are many instances of incomplete secondary linkages. It is important to adjust for multiaxiality if data are presented using primary and secondary locations. Other sources for errors in searching are non-intuitive placement and the selection of terms as preferred terms (PTs) that may not be widely recognised. Some MedDRA rules could also result in errors in data retrieval if the individual is unaware of these: in particular, the lack of multiaxial linkages for the Investigations SOC, Social circumstances SOC and Surgical and medical procedures SOC and the requirement that a PT may only be present under one High Level Term (HLT) and one High Level Group Term (HLGT) within any single SOC. Special Search Categories (collections of PTs assembled from various SOCs by searching all of MedDRA) are limited by the small number available and by lack of clarity about criteria applied in their construction. Difficulties in database searching may be addressed by suitable user training and experience, and by central reporting of detected deficiencies in MedDRA. Other remedies may include regulatory guidance on implementation and use of MedDRA. Further systematic review of MedDRA is needed and generation of standardised searches that may be used 'off the shelf' will help, particularly where the same search is performed repeatedly on multiple data sets. Until these enhancements are widely available, MedDRA users should take great care when searching a safety database to ensure that cases are not inadvertently missed.

Adverse Drug Reaction Reporting Systems↗