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PubMed2006

Auditing as part of the terminology design life cycle.

OBJECTIVE: To develop and test an auditing methodology for detecting errors in medical terminologies satisfying systematic inheritance. This methodology is based on various abstraction taxonomies that provide high-level views of a terminology and highlight potentially erroneous concepts. DESIGN: Our auditing methodology is based on dividing concepts of a terminology into smaller, more manageable units. First, we divide the terminology's concepts into areas according to their relationships/roles. Then each multi-rooted area is further divided into partial-areas (p-areas) that are singly-rooted. Each p-area contains a set of structurally and semantically uniform concepts. Two kinds of abstraction networks, called the area taxonomy and p-area taxonomy, are derived. These taxonomies form the basis for the auditing approach. Taxonomies tend to highlight potentially erroneous concepts in areas and p-areas. Human reviewers can focus their auditing efforts on the limited number of problematic concepts following two hypotheses on the probable concentration of errors. RESULTS: A sample of the area taxonomy and p-area taxonomy for the Biological Process (BP) hierarchy of the National Cancer Institute Thesaurus (NCIT) was derived from the application of our methodology to its concepts. These views led to the detection of a number of different kinds of errors that are reported, and to confirmation of the hypotheses on error concentration in this hierarchy. CONCLUSION: Our auditing methodology based on area and p-area taxonomies is an efficient tool for detecting errors in terminologies satisfying systematic inheritance of roles, and thus facilitates their maintenance. This methodology concentrates a domain expert's manual review on portions of the concepts with a high likelihood of errors.

Biology↗
PubMed2003

Use of Read codes in diabetes management in a south London primary care group: implications for establishing disease registers.

OBJECTIVE: To establish current practice in the use of Read codes for diabetes. DESIGN: Cross sectional study. SETTING: 17 practices in the Battersea primary care group in southwest London. DATA SOURCES: Computerised medical records. MAIN OUTCOME MEASURES: Number of codes in use in all practices; variation in the use of codes between practices; and prevalence of Read code use in diabetic patients. RESULTS: At least 9 separate Read code groupings and 25 individual diabetes codes were in use in the 17 general practices. Only one Read code (C10, diabetes mellitus) and its subcodes was being used in all 17 practices, but its use varied from 14% to 98% of patients with diabetes. The use of other key Read codes for monitoring the care of patients with diabetes also varied widely between practices; for example, < 20% of practices used the code for the location of care. Less than half of patients (45%) with diabetes had their type of diabetes coded, and even fewer (21%) had measures such as the examination of the retina coded. CONCLUSIONS: The use of Read codes for diabetes needs to be standardised and coding levels improved if valid diabetic registers are to be constructed and the quality of care is to be monitored effectively. Until all patients with diabetes have the C10 Read code recorded, clinicians will have to use a wide range of Read codes and prescribing data to ensure that diabetes registers are complete.

Cross-Sectional Studies↗
PubMed2000

An overview of coding and its relationship to standardized clinical terminology.

Coding systems and standardized clinical terminologies are interrelated. Coding schemes can be developed for classification systems, nomenclatures, and clinical terminologies. The coding systems most commonly used in the United States lose clinical detail and cannot meet the demands of the clinical information systems needed to support the computer-based patient record, outcomes studies, or risk-adjusted comparative research. Systems using computerized encoding and structured as terminologies offer more promise of providing the needed clinical detail. Companion systems can be developed to automatically place standardized clinical terms into less granular classification systems, such as ICD-9-CM, to maintain international compatibility and to continue federal programs based on such classifications.

Abstracting and Indexing↗
PubMedDate not supplied

Natural language generation in health care.

Good communication is vital in health care, both among health care professionals, and between health care professionals and their patients. And well-written documents, describing and/or explaining the information in structured databases may be easier to comprehend, more edifying, and even more convincing than the structured data, even when presented in tabular or graphic form. Documents may be automatically generated from structured data, using techniques from the field of natural language generation. These techniques are concerned with how the content, organization and language used in a document can be dynamically selected, depending on the audience and context. They have been used to generate health education materials, explanations and critiques in decision support systems, and medical reports and progress notes.

Expert Systems↗
PubMed2006

Computerisation of endoscopy reports using standard reports and text blocks.

BACKGROUND: The widespread use of gastrointestinal endoscopy for diagnosis and treatment requires effective, standardised report systems. This need is further increased by the limited storage of images, and by the need for structured databases for surveillance and epidemiology. We therefore aimed for a report system which would be quick, easy to learn, and suitable for use in busy daily practice. METHODS: Endobase III is an endoscopy information system offering three different ways of report writing, i.e. standard reports, text blocks and Minimal Standard Terminology (MST). A working group of two university and four general hospitals worked as a reference group for the development of standard reports and text blocks. Guidelines from various gastrointestinal endoscopy societies were followed to compose the reports. RESULTS: Standard reports were based on a list of distinct diagnoses; text blocks were based on anatomic landmarks and individual procedures. As such, 316 standard reports were developed for upper and lower gastrointestinal endoscopy, and endoscopic retrograde cholangiopancreatography (ERCP). In this way selecting one diagnosis produces a complete report. A total of 1571 different text blocks were additionally developed for each part of the gastrointestinal tract and for procedures during endoscopy. This module allowed generation of a full report on the combination of text blocks. Reports could be composed and printed within two minutes for 90% of cases. CONCLUSION: Standard reports and text blocks are a quick, user-friendly way of report writing accepted and used by a number of gastroenterologists in the Netherlands.

Databases, Factual↗
PubMed2005

Extending a medical language processing system to the functional status domain.

The World Health Organization's International Classification of Functioning, Disability, and Health (ICF) provides a common framework for describing functional status information (FSI) in health records. Given the expense of manual coding, we are investigating the use of natural language processing (NLP) for automated FSI coding. We used an existing NLP system that was originally designed to encode clinical information. The system's lexicon and coding table were modified and preprocessing and postprocessing programs were created, allowing for automated assignment of selected ICF codes.

Activities of Daily Living↗
PubMed2004

SaRAD: a Simple and Robust Abbreviation Dictionary.

MOTIVATION: Due to recent interest in the use of textual material to augment traditional experiments it has become necessary to automatically cluster, classify and filter natural language information. RESULTS: The Simple and Robust Abbreviation Dictionary (SaRAD) provides an easy to implement, high performance tool for the construction of a biomedical symbol dictionary. The algorithms, applied to the MEDLINE document set, result in a high quality dictionary and toolset to disambiguate abbreviation symbols automatically.

Abbreviations as Topic↗
PubMed2001

The creation of an ontology of clinical document names.

The efficient use of documents from heterogeneous computer systems is hampered by differences in document-naming practices across organizations. Using an open-consensus method, the Document Ontology Task Force, with support from the Veterans Health Administration, addressed this pervasive problem by developing a clinical document ontology. Based on the analysis of over 2000 clinical document names, the ontology was used to formulate a terminology model which is currently being used to guide the creation of fully-specified document names in LOINC (Logical Observations, Identifiers, Names and Codes). Incorporation into LOINC will enable homogeneous management of documents in a widely distributed environment and will also give rise to a rich polyhierarchy of document names.

Documentation↗
PubMedDate not supplied

Children's perseverative appearance-reality errors are related to emerging language skills.

Two experiments explored the communicative bases of preschoolers' object appearance-reality (AR) errors. In Experiment 1, 3-, 4-, and 5-year-olds (N = 36) completed the AR test (with high- and low-deceptive objects), a control test with the same discourse structure but nondeceptive stimuli, and stimulus naming and memory tests. AR performance correlated positively with control (discourse) and naming test performance. Object deceptiveness had little effect. In Experiment 2, 3- and 4-year-olds (N = 64) completed AR tests that experimentally varied question phrasing and use of exemplar objects. Children also completed memory, vocabulary, and control tests (of verbal perseveration). AR performance variance was predicted by a composite perseveration score from three non-AR tasks, vocabulary, and exemplars. The results indicate that the discourse structure of the AR test elicits a perseverative tendency that is mediated by children's verbal knowledge.

Child↗
PubMed1995

On the linguistic representation of medical information: natural language, controlled language, and formal language.

Language is indispensable for the representation of medical information. We classified the methods of linguistic representation into three items: natural language, controlled language, and formal language. The characteristics of these are discussed; we focus especially on the preparation of data and data quality. We present the perspective that linguistic research in medical informatics can be considered as an effort to convert natural language into formal language and vice versa. The problems related to the conversion and the role of controlled language in medical linguistics are discussed in detail.

Language↗
PubMed2006

Human and automated coding of rehabilitation discharge summaries according to the International Classification of Functioning, Disability, and Health.

OBJECTIVE: The International Classification of Functioning, Disability, and Health (ICF) is designed to provide a common language and framework for describing health and health-related states. The goal of this research was to investigate human and automated coding of functional status information using the ICF framework. DESIGN: The authors extended an existing natural language processing (NLP) system to encode rehabilitation discharge summaries according to the ICF. MEASUREMENTS: The authors conducted a formal evaluation, comparing the coding performed by expert coders, non-expert coders, and the NLP system. RESULTS: Automated coding can be used to assign codes using the ICF, with results similar to those obtained by human coders, at least for the selection of ICF code and assignment of the performance qualifier. Coders achieved high agreement on ICF code assignment. CONCLUSION: This research is a key next step in the development of the ICF as a sensitive and universal classification of functional status information. It is worthwhile to continue to investigate automated ICF coding.

Activities of Daily Living↗
PubMed2001

Evaluation of a method that supports pathology report coding.

OBJECTIVES: The paper focuses on the problem of adequately coding pathology reports using SNOMED. Both the agreement between pathologists in coding and the quality of a system that supports pathologists in coding pathology reports were evaluated. METHODS: Six sets of three pathologists each received a different set of 40 pathology reports. Five different SNOMED code lines accompanied each pathology report. Three pathologists evaluated the correctness of each of these code lines. Kappa values and values for the reliability coefficients were determined to gain insight in the variance observed when coding pathology reports. The system that is evaluated compares a newly entered report, represented as a multi-dimensional word vector, with reports in a library, represented in the same way. The reports in the library are already coded. The system presents the code lines belonging to the five library reports most similar to the newly entered one to the pathologist in this way supporting the pathologist in determining the correct codes. A high similarity between two reports is indicated by a large value of the inproduct of the vector of the newly entered report and the vector of a report in the library. RESULTS: Agreement between pathologists in coding was fair (average kappa of 0.44). The reliability coefficient varied from 0.81 to 0.89 for the six sets of pathology reports. The system gave correct suggestions in 50% of the reports. In another 30% it was helpful for the pathologists. CONCLUSIONS: On the basis of the level of the reliability coefficients it could be concluded that three pathologists are indeed sufficient for obtaining a gold standard for evaluating the system. The method used for comparing reports is not strong enough to allow fully automatic coding. It could be shown that the system induces a more uniform coding by pathologists. An evaluation of the incorrect suggestions of the system indicates that the performance of the system can still be improved.

Clinical Laboratory Information Systems↗
PubMed2004

Modeling, the essential step to consolidate and integrate a national NMDS.

How to develop a nursing minimum data set (NMDS) as a part of a nursing information system, which is itself a part of a health information system, this is the challenge presented in this paper and realized in Switzerland through the NURSING data project. The development of the CH-NMDS is not just a selection of data but a real conceptual work consisting in making the link between the information system and the terminology system and this for any level of aggregation. The building of a conceptual coherence between the collection of the data, their storage and their utilization for decision making was made by using the object modeling language, not for programming aims but statistical purposes. For example, the nursing phenomena and the nursing interventions are considered as classification concepts as well as sets of data.

Data Collection↗
PubMedDate not supplied

Medical dictionaries for patient encoding systems: a methodology.

Medical language is highly compositional and makes extensive use of common roots, especially Latino-Greek roots. Besides words devoted to common sense, medical language presents some typical characteristics, especially on morphological and semantic aspects of word formation. Morphological decomposition and identification precedes semantic analysis. It is only when these two prerequisites are fulfilled that an attempt to grasp the meaning of a whole expression is made possible. The main aim of the proposed approach is that of coping with 'the lack of coverage of the medical lexical knowledge', in order to help physicians find the correct international classification for diseases (ICD) codes for a written diagnosis. The proposed methodology allows the development of a powerful dynamic dictionary dedicated to natural language processing in the field of diagnoses and narrative procedures. It describes the design of an analyser that can profit from a dictionary. The methods used have proved to be efficient for various classifications, s well as for multiple languages, as the system presently supports French, German, English and Dutch for ICD-9 and ICD-10 classifications.

Classification↗
PubMed1995

The relationship between phonological awareness and reading and spelling achievement eleven years later.

This study reports follow-up data from 24 teenagers (mean age = 17 years; 11 boys and 13 girls) who had participated in a study of phonological analysis and reading and spelling abilities 11 years earlier, when they were enrolled in kindergarten. The results indicated that phonological awareness ability assessed during kindergarten (via the Auditory Analysis Test) was a significant predictor of word identification and spelling skills 11 years later, when both socioeconomic status and vocabulary development were controlled. In contrast, socioeconomic status, vocabulary development, word recognition, and spelling achievement assessed at kindergarten were not significantly correlated with reading and spelling achievement 11 years later. Results are discussed regarding the relative stability of phonological awareness and the importance of this awareness as a precursor to the development of word identification and spelling skills.

Adolescent↗
PubMed1998

An evaluation of UMLS as a controlled terminology for the Problem List Toolkit.

We are developing a set of software components--the Problem List Toolkit (PL-Tk)--to support operations on clinical problem labels. An adaptation of the National Library of Medicine's Unified Medical Language System (UMLS) provides general vocabulary services to domain-specific software components. Our initial investigation centers on the inclusion in UMLS of problem labels used in the Beth Israel Deaconess Medical Center's Online Medical Record (OMR). We also explore the semantic typing of problem labels matched in UMLS. We have operationally defined a clinical problem to derive its semantic type from classes of terms representing findings or processes typically requiring diagnostic evaluation or therapeutic management in clinical practice. Of 1262 unique OMR problem labels, 999 terms (79%) have matches in UMLS. 986 of 999 terms (99%) map to the UMLS concept of the corresponding lexical match. 952 of 999 terms (95%) have semantic types that comply with our operational definition of clinical problems. These 952 terms (75%) constitute Version 1.0 of the problem list vocabulary B196. Matching terms with inappropriate semantic types raise issues regarding requirements for PL-Tk, typing of existing UMLS terms, and the adequacy of our operational definition for clinical problems. UMLS provides a large repertoire of pre-coordinated terms that are used as problem labels in a heavily used computer-based patient record system. The semantic type hierarchy provides a framework for the consistent use of clinical concepts in problem lists such that clinical problem labels represent "good" clinical problems.

Evaluation Studies as Topic↗