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A considerable number of robust vocabularies and thesauri have been developed for the healthcare and biomedical domain. No single vocabulary, however; provides complete coverage of the information needs from a public health perspective. The results of an investigation of vocabulary sources for the development of a comprehensive controlled vocabulary for the public health domain at the Centers for Disease Control and Prevention (CDC) is presented.

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The U.S. Environmental Protection Agency's revised proposed 222Rn in drinking water regulation gives states or individual community water systems the option of compliance with the maximum contaminant level or compliance with the higher, alternate maximum contaminant level accompanied by the implementation of a multimedia mitigation plan. If states or water suppliers choose to comply with the alternate maximum contaminant level, the health risk reduction achieved by multimedia mitigation programs must be equal to or greater than the health risk reduction that would be achieved by compliance with the maximum contaminant level rather than the alternate maximum contaminant level. We have developed a method to determine quantitative goals for mitigating existing homes and building new 222Rn-resistant homes to achieve a health risk reduction to the public equivalent to the health risk differential between alternate maximum contaminant level and maximum contaminant level compliance. This method can be applied to an entire state, a portion of a state, or to an individual water supplier. The method was applied to North Carolina, and it was concluded that, over time, the health risk reduction achievable from alternate maximum contaminant level compliance and the implementation of a multimedia mitigation program would be much greater than from compliance with the maximum contaminant level.

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The objective of this project was to assess the status of the use of 222Rn-resistant construction techniques in new home construction in the eight Zone 1 counties of North Carolina. Zone 1 counties have an average predicted indoor 222Rn screening potential greater than 148 Bq m(-3)(4 pCi L(-1)). To facilitate a response from builders, a brief survey form was designed and printed on the back of a self-addressed, postage-paid postcard. This survey form was mailed to 460 home builders in the Zone 1 counties. The response rate was 17%, which can be compared to the 4.9% response rate obtained in a national survey conducted by the National Association of Home Builders Research Center. In our survey, 62% of the responding builders reported that they had built some or many homes in 1996 "using construction techniques to reduce the entry of radon into homes," but only 10% of the builders reported using these techniques for many homes. The National Association of Home Builders survey determined that, nationally, 30% of homes built in Zone 1 counties had 222Rn venting features. There is the potential for bias in the results of our survey (as well as in the results of the National Association of Home Builders survey) since the response rates were low.

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This article will present a description of the semi-implicit semantic properties of the Systematized Nomenclature of Human and Veterinary Medicine, also called SNOMED International. It will focus on the formalism of SNOMED and its computational properties using the disease definition as an example. Additional information will be provided in order to convert semi-implicit links found between SNOMED concepts into explicit computational semantic links.

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We describe the framework for SNOMED RT (Reference Terminology), designed to complement the broad coverage of medical concepts in SNOMED with a set of enhanced features that significantly increases its value as a reference terminology for representing clinical data. We describe what is meant by a reference terminology, and differentiate SNOMED RT from specialized terminologies that enable user interfaces, electronic messaging, or natural language processing, as well as from other specialized reference terminologies whose primary purpose is for representing data that is not primarily clinical in nature. We then describe how SNOMED RT represents multiple hierarchies and incorporates description logic. We believe that such a comprehensive set of concepts at multiple levels of granularity, with multiple logic-based subsumption hierarchies can meet the requirements of a reference terminology for health care.

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SNOMED is an inventory of medical terms and concepts. Each concept has a unique representation, it's primary termcode. The primary termcode carries hierarchical and inheritable information about each concept it represents. Additional hierarchical and inheritable information is carried by cross references linked to each concept. The cross references provide the defining characteristics for each concept thereby creating a computer readable definition for each SNOMED entry. These are some of the attributes that define the SNOMED model.

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The Systematized Nomenclature of Medicine, Third Edition, SNOMED International, is a comprehensive structured nomenclature of human and veterinary medicine, the terms of which are detailed, fine grained and semantically typed. Terms are assigned to eleven independent modules (fields), each of which is systematized. Terms may be linked to on another to represent complex entities or manifestations or alternately complex terms dissected into their elemental parts. Terms are illustrated utilizing a frame representation. Efforts are in progress to build both a conceptual graph and a frame-based semantic network encompassing each SNOMED term, effectively building a knowledge base. In this way, the knowledge contained in each alphanumeric representation is made explicit. SNOMED is a linked data structure capable of faithfully representing the activities, observations and diagnoses found in the medical record in a computer processable form.

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The authors characterize the problems inherent to mapping across or combining terms from different vocabularies, focusing especially on MeSH and SNOMED. They also describe the exploration of the development of a frame-based representation of SNOMED.

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The subject is examined in accordance with recommendations made at two recent international conferences. The historical backgrounds of the International Classification of Diseases (ICD) and the Systematized Nomenclature of Medicine (SNOMED) are related to explain the current status and objectives of both as well as their structural differences. A Canadian alternative to the ICD is presented along with the reason for its non-acceptance. Finally, it is proposed that SNOMED and ICD be integrated in a practical way to obtain the benefits of a multiaxial nomenclature while retaining the equivalent ICD classes necessary for maintaining the continuity of statistical information. This approach would prepare the groundwork necessary for completely automated encoding in natural medical language for health care data banks, while providing ICD-based national and international statistics.

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