Semantic based concept differential retrieval & equivalence detection in clinical terms version 3 (Read Codes).
(9/1313)
Modern clinical terminologies are required to provide a large corpus of concepts to cover the complexity of medicine. It is well recognised that sufficient scalability is likely to be achieved only with those schemes that can build post-coordinated constructs compositionally. Clinical Terms Version 3 (Read Codes) uses a system of templates to both express the semantic definition (atoms) of concepts and to allow qualification of core concepts with additional detail. This common mechanism for expressing both intrinsic semantic information and additional information allows both pre- and post-coordinated concepts to be retrieved from different perspectives and to detect equivalence between alternative representations of the same concept. The practical application and experience of such an approach is described in relation to a live clinical database (Diabeta). The merits of such an approach are outlined and its relationship to other documented mechanisms outlined. (+info)
Aggregation and reclassification--assessment of GALEN methods in the domain of thoracic surgery.
(10/1313)
This paper reports on the experiences from evaluation of GALEN methods for mapping of follow-up categories in the domain of thoracic surgery to an existing classification of surgical procedures. The mapping of the aggregated levels or groups of thoracic procedures presents a genuine problem in relation to strict hierarchical classifications, since the follow-up categories not necessarily fit in the pre-set structure of the classification. The paper reports on the experiences from modelling of the traditional classification as well as modelling of the follow-up categories, together with an analysis of results with a discussion of opportunities and potential problems and pitfalls when applying GALEN models and tools. (+info)
Desiderata for a clinical terminology server.
(11/1313)
Clinical terminology servers are distinguished from more broadly based terminology servers intended for nomenclature development or mediation across classifications. Focusing upon the consistent and comparable entry of clinical observations, findings, and events, key desiderata are enumerated and expanded. These include 1) word normalization, 2) word completion, 3) target terminology specification, 4) spelling correction, 5) lexical matching, 6) term completion, 7) semantic locality, 8) term composition and 9) decomposition. Comparisons of this functionality to previously published models and specifications are made. Experience with a clinical terminology server, Metaphrase, is described. (+info)
Evaluation of a proposed method for representing drug terminology.
(12/1313)
In the absence of a single, standard, multipurpose terminology for representing medications, the HL7 Vocabulary Technical Committee has sought to develop a model for such terms in a way that will provide a unified method for representing them and supporting interoperability among various terminology systems. We evaluated the preliminary model by obtaining terms, represented in our model, from three leading vendors of pharmacy system knowledge bases. A total of 2303 terms were obtained, and 3982 pair-wise comparisons were possible. We found that the components of the term descriptions matched 68-87% of the time and that the overall descriptions matched 53% of the time. The evaluation has identified a number of areas in the model where more rigorous definitions will be needed in order to improve the matching rate. This paper discusses the implications of these results. (+info)
Detailed content and terminological properties of DSM-IV.
(13/1313)
DSM-IV, the Diagnostic and Statistical Manual of Mental Disorders, is the internationally accepted standard for nomenclature and diagnosis in psychiatric practice. The objective of this project is to parse the rubric criteria of the DSM to extract the clinically detailed signs, symptoms, findings, and conditions that are present. These are a "latent terminology" implicit within the DSM, which is highly granular and clinically specific. This manuscript describes the content of these terms that heretofore existed sub rosa, though we recognize that during the authorship of the DSM such terms were constructed deliberately and systematically. Relevant characteristics of the classification system are briefly reviewed. Summary results of parsing the defining criteria for the 400 ICD-9 Codes enumerated in DSM-IV are presented. (+info)
A randomized double-blind controlled trial of automated term dissection.
(14/1313)
OBJECTIVE: To compare the accuracy of an automated mechanism for term dissection to represent the semantic dependencies within a compositional expression, with the accuracy of a practicing Internist to perform this same task. We also compare the results of four evaluators to determine the inter-observer variability and the variance between term sets, with respect to the accuracy of the mappings and the consistency of the failure analysis. METHODS: 500 terms, which required a compositional expression to effect an exact match, were randomly distributed into two sets of 250 terms (Set A and Set B). Set A was dissected using the Automated Term Dissection (ATD) Algorithm. A physician specializing in Internal Medicine dissected set B. He had no prior knowledge of the dissection algorithm or how it functioned. In this manuscript, the authors use Human Term Dissection (HTD) to refer to this method. Set A was randomized to two sets of 125 terms (Set A1 and Set A2). Set B was randomized to two sets of 125 terms (Set B1 and Set B2). A new set of 250 terms Set C was created from Set A1 and Set B2. A second new set of 250 terms Set D was created from Set A2 and Set B1. Two expert Indexers reviewed Set C and another two expert Indexers reviewed Set D. They were blinded to which terms were dissected by the clinician and which terms were dissected by the automated term dissection algorithm. The person providing the files for review to the Indexers was also unaware of which terms were dissected by ATD vs. the HTD method. The Indexers recorded whether or not the dissection was the best possible representation of the input concept. If not, a failure analysis was conducted. They recorded whether or not the dissection was in error and if so was a modifier not subsumed or was a Kernel concept subsumed when it should not have been. If a concept was missing, the Indexers recorded whether it was a Kernel concept, a modifier, a qualifier or a negative qualifier. RESULTS: The ATD method was judged to be accurate and readable in 265 out of the 424 terms with adequate content (62.7%). The HTD method was judged to be accurate in 272 out of 414 terms with adequate content (65.7%). There was no statistically significant difference between the rates of acceptability of the ATD and HTD methods (p = 0.33). There was a non-significant trend toward greater acceptability of the ATD method in the subgroup of terms with three or more compositional elements. ATD was acceptable in 53.6% of the terms where the HTD was only acceptable in 43.6% (p = 0.11). The failure analysis showed that both methods misrepresented kernel concepts and modifiers much more commonly than qualifiers (p < 0.001). CONCLUSIONS: There is no statistically significant difference in the accuracy and readability of terms dissected using the automated term dissection method when compared with human term dissection, as judged by four expert medical indexers. There is a non-significant trend toward improved performance of the ATD method in the subset of more complex terms. The authors submit that this may be due to a tendency for users to be less compulsive when the time to complete the task is long. Automated term dissection is a useful and perhaps preferable method for representing readable and accurate compound terminological expressions. (+info)
Modeling the UMLS using an OODB.
(15/1313)
The Unified Medical Language System combines many well established authoritative medical informatics terminologies in one system. Such a resource is very valuable to the healthcare industry. However, the UMLS is very large and complex and poses serious comprehension problems for users and maintenance personnel. Furthermore, the sets of concepts of semantic types are not semantically uniform and thus are difficult to study. We describe a method to represent two components of the UMLS, the Metathesaurus (META) and the Semantic Network, as an OODB. The resulting UMLS OODB schema is deeper and more refined than the Semantic Network. It offers semantically uniform classes, which improves support for comprehension and navigation of META. The UMLS OODB also exposes problems in the semantic type classifications. (+info)
Applying the desiderata for controlled medical vocabularies to drug information databases.
(16/1313)
Medication history has always been an integral part of the patient's medical record. With the advent of the computerized medical record and the longitudinal clinical data repository, having the medication history has enabled the development of clinical decision support system that alerts for drug to drug interactions and drug allergies. Furthermore, medication data is increasingly being analyzed from a utilization and clinical outcomes standpoint. For these activities to occur, a controlled pharmacy vocabulary akin to a controlled medical vocabulary is essential. Drug information databases are well-established sources of information for pharmacy-related data and products. However, do they measure up as a controlled vocabulary? Recent experience reviewing drug information databases and integrating pharmacy-related information into a data dictionary in real-time clinical use at multiple health care institutions have revealed several challenges and issues. These are discussed according to Cimino's desiderata for controlled medical vocabularies. (+info)