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Biomedical subjects

S M Huff

Publications and source records attributed to S M Huff.

36 records · Page 2Linked to original sources
PubMed1993

Automated translation between medical vocabularies using a frame-based interlingua.

The integration of clinical systems almost always requires a translation phase, where vocabularies are compared and the similar concepts are matched. The lack of standards in the area of medical concept representation makes this task very difficult. The authors describe the development of a frame-based application that automatically translates terms found in one vocabulary to another. The application implements an innovative scoring algorithm that ranks the best matches using an exponential scale. Preliminary results and the comparison against a manual process in the same domain are also discussed.

Electronic Data Processing↗
PubMed1992

Pick from thousands: a collaborative processing model for coded data entry.

Methods for optimizing coded data entry in clinical systems are a frequent topic of system design. We have developed a new mechanism for this type of data entry that we call "Pick From Thousands" (PFT). It combines several known methods, including menu selection, keyword entry, and initial character matching, but adds a new string matching algorithm. The PFT method is more selective than initial character matching for a given number of keystrokes if entries in the coded list have more than one word. Collaborative processing between a PC workstation and the central HELP system computer is used to optimize ease of maintenance and increase the flexibility and performance of the system.

Algorithms↗
PubMed1992

Integration of a stand-alone expert system with a hospital information system.

A stand-alone PC expert system for evaluating the appropriateness of inpatient admissions has been integrated with an existing hospital information system. The expert system supports preadmission screening for appropriateness of inpatient admissions. The HIS provides extensive clinical data in a coded electronic form, permitting high-level decision support. The integrated system was developed for a 20 week randomized clinical trial to evaluate the effects of preadmission screening on inappropriate inpatient admissions. Three factors of the integration are considered: programmatic integration of the expert system, seamless presentation of mixed platform applications, and integration of coded data from the stand-alone application into the HIS data structure.

Evaluation Studies as Topic↗
PubMed1992

The development of a virtual database to provide on-line access to a large archive of clinical data.

The archival database of the HELP Hospital Information System at LDS Hospital is too large to be stored on line. The archival data are important for clinical and research applications. Demountable disk packs have been used to store the archival database. This method of storage has four significant disadvantages. A virtual database was developed to overcome the limitations of this data-management scheme. This virtual database enables the transparent use of appropriate low-cost network-based storage technology to provide on-line availability of the entire archive of clinical data. The virtual database successfully resolves the problems associated with disk packs, and opens the door to enhanced use of the data for clinical and research applications.

Computer Storage Devices↗
PubMed1991

Evaluation of an SQL model of the HELP patient database.

We tested a new model of the HELP patient database that makes use of relational tables to store patient data and provides access to data using SQL (Structured Query Language). The SQL database required more storage space and had many more physical records than the HELP database, but it was faster and more efficient in storing data than the standard HELP utilities. The HELP utilities used disk space more efficiently and were faster than the SQL tools when retrieving data for typical clinical reports. However, the SQL model provides networking capabilities, general report writing tools, detailed user documentation, and an ability for creating secondary indexes that offset its poorer performance.

Database Management Systems↗
PubMed1986

Pyrolysis mass spectrometry of bacteria from infected human urine. I. Influence of culturing and antibiotics.

Curie-point pyrolysis mass spectrometry was performed on three bacterial isolates obtained from infected human urine using a novel, direct isolation method. Bacterial samples were analysed directly after isolation, as well as after free growth in broth and after exposure to solutions containing penicillin and gentamicin. The spectra of bacteria directly from urine showed no detectable contamination from urinary constituents. Discriminant analysis indicated genetic strain differences to be greater than the combined variances due to sample preparation or the growth phase. Characteristic biochemical changes related to growth or non-growth were detectable after only 2 h of incubation. The potential usefulness of pyrolysis mass spectrometry techniques for rapid susceptibility testing is discussed.

Anti-Bacterial Agents↗
PubMed1984

Pyrolysis mass spectrometry of complex organic materials.

Pyrolysis mass spectrometry in combination with computerized multivariate statistical analysis enables qualitative and quantitative analysis of nonvolatile organic materials containing molecular assemblies of a complexity and size far beyond the capabilities of direct mass spectrometry. The state of the art in pyrolysis mass spectrometry techniques is illustrated through specific applications, including structural determination and quality control of synthetic polymers, quantitative analysis of polymer mixtures, classification and structural characterization of fossil organic matter, and nonsupervised numerical extraction of component patterns from complex biological samples.

Biochemical Phenomena↗
PubMedDate not supplied

Toward a medical-concept representation language. The Canon Group.

The Canon Group is an informal organization of medical informatics researchers who are working on the problem of developing a "deeper" representation formalism for use in exchanging data and developing applications. Individuals in the group represent experts in such areas as knowledge representation and computational linguistics, as well as in a variety of medical subdisciplines. All share the view that current mechanisms for the characterization of medical phenomena are either inadequate (limited or rigid) or idiosyncratic (useful for a specific application but incapable of being generalized or extended). The Group proposes to focus on the design of a general schema for medical-language representation including the specification of the resources and associated procedures required to map language (including standard terminologies) into representations that make all implicit relations "visible," reveal "hidden attributes," and generally resolve ambiguous or vague references. The Group is proceeding by examining large numbers of texts (records) in medical sub-domains to identify candidate "concepts" and by attempting to develop general rules and representations for elements such as attributes and values so that all concepts may be expressed uniformly.

Computer Simulation↗
PubMedDate not supplied

The Canon Group's effort: working toward a merged model.

OBJECTIVE: To develop a representational schema for clinical data for use in exchanging data and applications, using a collaborative approach. DESIGN: Representational models for clinical radiology were independently developed manually by several Canon Group members who had diverse application interests, using sample reports. These models were merged into one common model through an iterative process by means of workshops, meetings, and electronic mail. RESULTS: A core merged model for radiologic findings present in a set of reports that subsumed the models that were developed independently. CONCLUSIONS: The Canon Group's modeling effort focused on a collaborative approach to developing a representational schema for clinical concepts, using chest radiography reports as the initial experiment. This effort resulted in a core model that represents a consensus. Further efforts in modeling will extend the representational coverage and will also address issues such as scalability, automation, evaluation, and support of the collaborative effort.

Artificial Intelligence↗
PubMedDate not supplied

An event model of medical information representation.

OBJECTIVE: Develop a model for structured and encoded representation of medical information that supports human review, decision support applications, ad hoc queries, statistical analysis, and natural-language processing. DESIGN: A medical information representation model was developed from manual and semiautomated analysis of patient data. The key assumption of the model is that medical information can be represented as a series of linked events. The event representation has two main components. The first component is a frame or template definition that specifies the attributes of the event. The second component is a structured vocabulary, the terms of which are taken as the values of the slots in the event template structure. Individual event instances are linked by specific named relationships. RESULTS: The proposed model was used to represent a chest-radiograph report. CONCLUSIONS: The event model of medical information representation provides a mechanism for formal definition of the logical structure of medical data and allows explicit time-oriented and associative relationships between event instances.

Computer Simulation↗
PubMedDate not supplied

Evaluation of a "lexically assign, logically refine" strategy for semi-automated integration of overlapping terminologies.

OBJECTIVE: To evaluate a "lexically assign, logically refine" (LALR) strategy for merging overlapping healthcare terminologies. This strategy combines description logic classification with lexical techniques that propose initial term definitions. The lexically suggested initial definitions are manually refined by domain experts to yield description logic definitions for each term in the overlapping terminologies of interest. Logic-based techniques are then used to merge defined terms. METHODS: A LALR strategy was applied to 7,763 LOINC and 2,050 SNOMED procedure terms using a common set of defining relationships taken from the LOINC data model. Candidate value restrictions were derived by lexically comparing the procedure's name with other terms contained in the reference SNOMED topography, living organism, function, and chemical axes. These candidate restrictions were reviewed by a domain expert, transformed into terminologic definitions for each of the terms, and then algorithmically classified. RESULTS: The authors successfully defined 5,724 (73%) LOINC and 1,151 (56%) SNOMED procedure terms using a LALR strategy. Algorithmic classification of the defined concepts resulted in an organization mirroring that of the reference hierarchies. The classification techniques appropriately placed more detailed LOINC terms underneath the corresponding SNOMED terms, thus forming a complementary relationship between the LOINC and SNOMED terms. DISCUSSION: LALR is a successful strategy for merging overlapping terminologies in a test case where both terminologies can be defined using the same defining relationships, and where value restrictions can be drawn from a single reference hierarchy. Those concepts not having lexically suggested value restrictions frequently indicate gaps in the reference hierarchy.

Algorithms↗
PubMedDate not supplied

Development of the Logical Observation Identifier Names and Codes (LOINC) vocabulary.

The LOINC (Logical Observation Identifier Names and Codes) vocabulary is a set of more than 10,000 names and codes developed for use as observation identifiers in standardized messages exchanged between clinical computer systems. The goal of the study was to create universal names and codes for clinical observations that could be used by all clinical information systems. The LOINC names are structured to facilitate rapid matching, either automated or manual, between local vocabularies and the universal LOINC codes. If LOINC codes are used in clinical messages, each system participating in data exchange needs to match its local vocabulary to the standard vocabulary only once. This will reduce both the time and cost of implementing standardized interfaces. The history of the development of the LOINC vocabulary and the methodology used in its creation are described.

Classification↗
PubMedDate not supplied

The decline and fall of Esperanto: lessons for standards committees.

In 1887, Polish physician Ludovic Zamenhof introduced Esperanto, a simple, easy-to-learn planned language. His goal was to erase communication barriers between ethnic groups by providing them with a politically neutral, culturally free standard language. His ideas received both praise and condemnation from the leaders of his time. Interest in Esperanto peaked in the 1970s but has since faded somewhat. Despite the logical concept and intellectual appeal of a standard language, Esperanto has not evolved into a dominant worldwide language. Instead, English, with all its idiosyncrasies, is closest to an international lingua franca. Like Zamenhof, standards committees in medical informatics have recognized communication chaos and have tried to establish working models, with mixed results. In some cases, previously shunned proprietary systems have become the standard. A proposed standard, no matter how simple, logical, and well designed, may have difficulty displacing an imperfect but functional "real life" system.

History, 19th Century↗
PubMedDate not supplied

Toward vocabulary domain specifications for health level 7-coded data elements.

The "vocabulary problem" has long plagued the developers, implementers, and users of computer-based systems. The authors review selected activities of the Health Level 7 (HL7) Vocabulary Technical Committee that are related to vocabulary domain specification for HL7 coded data elements. These activities include: 1) the development of two sets of principles to provide guidance to terminology stakeholders, including organizations seeking to deploy HL7-compliant systems, terminology developers, and terminology integrators; 2) the completion of a survey of terminology developers; 3) the development of a process for HL7 registration of terminologies; and 4) the maintenance of vocabulary domain specification tables. As background, vocabulary domain specification is defined and the relationship between the HL7 Reference Information Model and vocabulary domain specification is described. The activities of the Vocabulary Technical Committee complement the efforts of terminology developers and other stakeholders. These activities are aimed at realizing semantic interoperability in the context of the HL7 Message Development Framework, so that information exchange and use among disparate systems can occur for the delivery and management of direct clinical care as well as for purposes such as clinical research, outcome research, and population health management.

Computer Communication Networks↗
PubMedDate not supplied

Evaluation of the clinical LOINC (Logical Observation Identifiers, Names, and Codes) semantic structure as a terminology model for standardized assessment measures.

OBJECTIVE: The purpose of this study was to test the adequacy of the Clinical LOINC (Logical Observation Identifiers, Names, and Codes) semantic structure as a terminology model for standardized assessment measures. METHODS: After extension of the definitions, 1, 096 items from 35 standardized assessment instruments were dissected into the elements of the Clinical LOINC semantic structure. An additional coder dissected at least one randomly selected item from each instrument. When multiple scale types occurred in a single instrument, a second coder dissected one randomly selected item representative of each scale type. RESULTS: The results support the adequacy of the Clinical LOINC semantic structure as a terminology model for standardized assessments. Using the revised definitions, the coders were able to dissect into the elements of Clinical LOINC all the standardized assessment items in the sample instruments. Percentage agreement for each element was as follows: component, 100 percent; property, 87.8 percent; timing, 82.9 percent; system/sample, 100 percent; scale, 92.6 percent; and method, 97.6 percent. DISCUSSION: This evaluation was an initial step toward the representation of standardized assessment items in a manner that facilitates data sharing and re-use. Further clarification of the definitions, especially those related to time and property, is required to improve inter-rater reliability and to harmonize the representations with similar items already in LOINC.

Databases, Factual↗
PubMedDate not supplied

Automated mapping of observation codes using extensional definitions.

OBJECTIVE: To create "extensional definitions" of laboratory codes from derived characteristics of coded values in a clinical database and then use these definitions in the automated mapping of codes between disparate facilities. DESIGN: Repository data for two laboratory facilities in the Intermountain Health Care system were analyzed to create extensional definitions for the local codes of each facility. These definitions were then matched using automated matching software to create mappings between the shared local codes. The results were compared with the mappings of the vocabulary developers. MEASUREMENTS: The number of correct matches and the size of the match group were recorded. A match was considered correct if the corresponding codes from each facility were included in the group. The group size was defined as the total number of codes in the match group (e.g., a one-to-one mapping is a group size of two). RESULTS: Of the matches generated by the automated matching software, 81 percent were correct. The average group size was 2.4. There were a total of 328 possible matches in the data set, and 75 percent of these were correctly identified. CONCLUSIONS: Extensional definitions for local codes created from repository data can be utilized to automatically map codes from disparate systems. This approach, if generalized to other systems, can reduce the effort required to map one system to another while increasing mapping consistency.

Algorithms↗