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Standards for the electronic transfer of clinical data: progress and promises.

Data exchange standards have two components: the message format or syntax and the dictionary of codes (semantics). For many applications, message standards already have been developed. For a few kinds of clinical entities, such as drugs, these code systems (e.g., the National Drug Code) are virtually complete, but a few gaps must be filled and an agreement must be reached about the level of granularity needed. The available codes for clinical descriptors are inadequate but the National Library of Medicine's Universal Medical Language (UML) project will do much to redress this deficiency. Codes for clinical variables such as blood pressure and blood glucose which have methods, units, normal ranges, and physiologic correlates are very inadequate. CPT4 provides some of the needed codes but has huge gaps. An early effort to extend CPT4 is included in ASTM 1238. Work being done by ASTM E31.12 and the Euclides project will offer robust codes for clinical laboratory measurements. If we want to pool data from different institutions for clinical and policy research, universal codes for observations are prerequisite. And agreement of an international coding system for observation-bearing variables should be a major agenda item for standards groups in the next year. Our goal has been to standardize the communication of clinical data between clinical systems, not the systems themselves or their internal operation. In fact, standardizing the internals of clinical application could be counterproductive at the present. It would deflect energy from, and delay the spread of, CDI standards. Moreover, it gives undue attention to computer systems, rather than the data they contain. The data are the most expensive part of any data system. They are the raison d'être for such systems. Computer systems come and go. The data last forever. Yet we have been mesmerized by the computer system while ignoring its contents. As a result, most computer-stored clinical data must live like the tragic boy in the bubble. They cannot "live" outside of the computer system in which they were born. So, we find at every hospital the bizarre rituals of humans reading computer-generated reports so they can type this information in another computer. Electronic (e.g., stored clinical) data should not depend upon the internals of a particular program, language, or machine for its interpretation. The clinical data entered into one computer system should be directly available to any other computer system that now receives them through manual transcription. Data interchange standards give life to our data--independent of the source system.

Abstracting and Indexing↗

Contemporary issues in HIM. The Internet. Part II.

The services and resources available on the Internet are immense and growing daily. In this and last month's article I have only scratched the surface of what is available. I have given two references that I have found very useful while learning about the Internet. I highly recommend both. However, if you would rather look for other books or articles, they are plentiful. In a recent newspaper, I saw seven books that had "Internet" in the title advertised by one book store. There were books for PC users, Mac users, and UNIX users. Lack of information is definitely not an excuse for not checking out the Internet!

Computer Communication Networks↗

Adapting a commercially available software program to improve ADR reporting.

To facilitate the long-term storage, retrieval, and analysis of adverse drug reaction (ADR) data, the drug information service at the University of Texas Health Science Center at San Antonio selected a computer software program with the capability to compile sets of relational databases. Five subsets were created to form the ADR database--patient demographics, medications, American Hospital Formulary Service classifications, adverse reactions, and case reports. This computerized system allows for quick information retrieval as well as the generation of monthly ADR reports. With such information, trends in ADRs can be identified and targeted for intervention programs to improve patient care and to comply with JCAHO requirements.

Adverse Drug Reaction Reporting Systems↗

Using a journal availability study to improve access.

PURPOSE: Identify journal collection access and use factors. SETTING AND SUBJECTS: University of North Carolina at Chapel Hill's Health Sciences Library patrons. METHODOLOGY: Survey forms and user interactions were monitored once a week for twelve weeks during the fall 1997 semester. The project was based on a 1989 New Mexico State University study and used Kantor's Branching Analysis to measure responses. RESULT: 80% of reported sought journal articles were found successfully. Along with journal usage data, the library obtained demographic and behavioral information. DISCUSSION AND CONCLUSIONS: Journals are the library's most used resource and, even as more electronic journals are offered, print journals continue to make up the majority of the collection. Several factors highlighted the need to study journal availability. User groups indicated that finding journals was problematic, and internal statistics showed people requesting interlibrary loans for owned items. The study looked at success rates, time, and ease of finding journals. A variety of reasons contributed to not finding journals. While overall user reports indicated relatively high success rate and satisfaction, there were problems to be addressed. As the library proceeds in redesigning both the physical space and electronic presence, the collected data have provided valuable direction.

Academic Medical Centers↗

Evaluation of the DEFINDER system for fully automatic glossary construction.

In this paper we present a quantitative and qualitative evaluation of DEFINDER, a rule-based system that mines consumer-oriented full text articles in order to extract definitions and the terms they define. The quantitative evaluation shows that in terms of precision and recall as measured against human performance, DEFINDER obtained 87% and 75% respectively, thereby revealing the incompleteness of existing resources and the ability of DEFINDER to address these gaps. Our basis for comparison is definitions from on-line dictionaries, including the UMLS Metathesaurus. Qualitative evaluation shows that the definitions extracted by our system are ranked higher in terms of user-centered criteria of usability and readability than are definitions from on-line specialized dictionaries. The output of DEFINDER can be used to enhance these dictionaries. DEFINDER output is being incorporated in a system to clarify technical terms for non-specialist users in understandable non-technical language.

Dictionaries, Medical as Topic↗

Cross-language MeSH indexing using morpho-semantic normalization.

We consider three alternative procedures for the automatic indexing of medical documents using MeSH thesaurus identifiers as target units (document descriptors). Rather than considering complete words as the starting point of the indexing procedure, we here propose morphologically plausible subwords as basic units from which MeSH terms are derived. We describe the morphological segmentation and normalization procedures, as well as the mappings from subwords to MeSH terms, and discuss results from an evaluation carried out on a German-language corpus.

Abstracting and Indexing↗

The integration of similar clinical research data collection instruments.

We devised an algorithm for integrating similar clinical research data collection instruments to create a common measurement instrument. We tested this algorithm using questions from several similar surveys. We encountered differing levels of granularity among questions and responses across surveys resulting in either the loss of granularity or data. This algorithm may make survey integration more systematic and efficient.

Algorithms↗

Assessment of a three-year experience with a Belgian Primary Care data Network.

The paper describes the experiences with a Belgian Primary Care data Network from 1999 till 2002. Three cycles of data collection have been performed. The network involves about 300 general practitioners (GPs) and up to 8 different software packages. This network is semi-anonymous, semi-automatic and mixed (paper and electronic with various software's). For the coming next years, efforts should be focused on solving some frequently occurring problems with the data collection through the EPR, such as a considerable number of data lacking and the fact that GPs do not always use the problem oriented structure of the EPR (Electronic Patient Record). Afterwards, more promising usage could be considered and developed such as repeated data collection using a same GPs' sample, long-term recording studies, usage of larger GPs' samples, etc.

Belgium↗

Generic computer-based questionnaires: an extension to OpenSDE.

Development of computer-based questionnaires (CQs) has been an ongoing challenge since the 1960s. The added value of such CQs for data collection and the acceptance by patients have been well documented. Many questionnaire projects, however, were temporary due to dedicated software, limited funding, and lack of integration with medical information systems. Also, the use of a fixed dedicated database makes integration cumbersome, as change in content requires change to the data model. Since much of the functional requirement of CQs is not dependent on content, the challenge is to both separate functionality and database structure from content. Following these principles, we extended OpenSDE, a generic application for structured data entry, with a tool to construct and run CQs as an alternative way of data input. We propose the combination of a generic building tool and a content-independent data model as an effective strategy to tackle the above-mentioned problems in CQ development.

Data Collection↗

[Automated classification of celestial spectra based on support vector machines].

The main objective of an automatic recognition system of celestial objects via their spectra is to classify celestial spectra and estimate physical parameters automatically. This paper proposes a new automatic classification method based on support vector machines to separate non-active objects from active objects via their spectra. With low SNR and unknown red-shift value, it is difficult to extract true spectral lines, and as a result, active objects can not be determined by finding strong spectral lines and the spectral classification between non-active and active objects becomes difficult. The proposed method in this paper combines the principal component analysis with support vector machines, and can automatically recognize the spectra of active objects with unknown red-shift values from non-active objects. It finds its applicability in the automatic processing of voluminous observed data from large sky surveys in astronomy.

Algorithms↗

Accelerating approximate subsequence search on large protein sequence databases.

Bioinformatics has become an active research area in recent years. The amount of mapped sequences doubles every fourteen months. BLAST has been widely employed for retrieving sequences which has similar portion(s) to a given sequence. However, BLAST has to scan the entire database every time when a query is issued. This can be very time consuming especially when the database is large. In this paper, we study the problem on how to build a persistent index structure for protein sequences to support approximate match. The suffix tree has been proposed as a solution to index sequence database and has been deployed on organizing DNA sequences (Hunt et al. 2001). Unfortunately, it suffers from the problem of "memory bottleneck" that prevents it from being applied efficiently to a large database. The performance even degrades further for protein database due to a larger fanout at each node. Here, we employ an indexing structure, called BASS-tree, to support approximate match in sublinear time on a large protein database. We call this indexing method as sequence approximate match (SAM) index method. The search of approximate matches can be properly directed to the portion in the database with a high potential of matching quickly. It has been demonstrated in our experiments that the potential performance improvement is in an order of magnitude over alternative methods such as the BLAST algorithm and the suffix tree.

Algorithms↗

Towards index-based similarity search for protein structure databases.

We propose two methods for finding similarities in protein structure databases. Our techniques extract feature vectors on triplets of SSEs (Secondary Structure Elements) of proteins. These feature vectors are then indexed using a multidimensional index structure. Our first technique considers the problem of finding proteins similar to a given query protein in a protein dataset. This technique quickly finds promising proteins using the index structure. These proteins are then aligned to the query protein using a popular pairwise alignment tool such as VAST. We also develop a novel statistical model to estimate the goodness of a match using the SSEs. Our second technique considers the problem of joining two protein datasets to find an all-to-all similarity. Experimental results show that our techniques improve the pruning time of VAST 3 to 3.5 times while keeping the sensitivity similar.

Algorithms↗

A new approach for gene annotation using unambiguous sequence joining.

The problem addressed by this paper is accurate and automatic gene annotation following precise identification/ annotation of exon and intron boundaries of biologically verified nucleotide sequences using the alignment of human genomic DNA to curated mRNA transcripts. We provide a detailed description of a new cDNA/DNA homology gene annotation algorithm that combines the results of BLASTN searches and spliced alignments. Compared to other programs currently in use, annotation quality is significantly increased through the unambiguous junction of genomic DNA sequences. We also address gene annotation with both non-canonic splice sites and short exons. The approach has been tested on the Genie learning subset as well as full-scale human RefSeq, and has demonstrated performance as high as 97%.

Algorithms↗

Determining prominent subdomains in medicine.

We discuss an automated method for identifying prominent subdomains in medicine. The motivation is to enhance the results of natural language processing by focusing on sublanguages associated with medical specialties concerned with prevalent disorders. At the core of our approach is a statistical system for topical categorization of medical text. A method based on epidemiological evidence is compared to another that considers frequency of occurrence of Medline citations. We suggest the isolation of UMLS terminology peculiar to individual medical specialties as a way of enhancing natural language processing systems in the biomedical domain.

Abstracting and Indexing↗

The benefits of the application of geographical information systems in public and environmental health.

One of the most important issues in public and environmental health today concerns the type of instruments that can be used to devise quick, reliable and scientifically valid methods of rapid assessment which, in turn, can be utilized in health research and in the planning, monitoring and evaluation of health programmes. As the applications of geographical information systems (GIS) relate to the collection, storage, integration, management, retrieval, analysis and display of spatial data, it is not surprising that the potential usefulness of this new technology in the fields of health research and policy is beginning to be realized. This article seeks to demonstrate the opportunities which the use of geographical information systems can offer to research and policy on health issues. The article first describes the principles and objectives of GIS before going on to discuss hardware and software developments as well as the variety of application fields, organizations and users. Some examples of current applications are provided to illustrate the type of work being undertaken. The final sections address issues specifically related to the application of GIS in health research and policies in the European context.

Computers↗

Automated and computer-assisted pathology support for a large chronic study.

Pathology support for the 24,192 mouse toxicological ED01 study at the National Center for Toxicological Research was provided by the University of Arkansas Pathology Services Project through a contract between NCTR and the University of Arkansas. To aid in the collection, storage, retrieval, and analysis of this large amount of data an automated computer-assisted pathology system was developed. Use of this system has resulted in accurate data, the ability to handle large amounts of data, and low-cost analysis of the data.

Animals↗