pre-printMedical Informatics needs a specific terminology that reflects the multi-disciplinary nature of the field and can rapidly change as the discipline evolves. Using the four primary methods of thesaurus construction, a group at the University of Missouri- Columbia is developing a thesaurus that meets these criteria and includes both user and literary warrant. The steps in construction include using existing thesauri, medical informatics literature, and the terminology of experts to produce a thesaurus arranged within a hierarchical structure

Mitchell, Joyce A.

Ogg, Nancy J.

English

The University of Utah: J. Willard Marriott Digital Library

Construction of a Medical Informatics ThesaurusNancy J. Ogg*+, MaryEllen Sievert, Zong Rong LiA, Joyce A. Mitchell+*Dept. of Information Science, University of Missouri-Columbia'Medical Informatics Group, University of Missouri-ColumbiaAMedical Informatics Institute, Hubei Medical University, ChinaABSTRACTMedical Informatics needs a specific terminologythat reflects the multi-disciplinary nature of the fieldand can rapidly change as the discipline evolves.Using the four primary methods of thesaurusconstruction, a group at the University of Missouri-Columbia is developing a thesaurus that meets thesecriteria and includes both user and literarywarrant. The steps in construction include usingexisting thesauri, medical informatics literature, andthe terminology of experts to produce a thesaurusarranged within a hierarchical structure.INTRODUCTIONMedical Informatics is a constantly evolving, multi-disciplinary field which draws terminology from avariety of disciplines. When we tried to dooriginal abstracting and indexing of medicalinformatics literature for the Medical InformaticsInformation Center at the University of Missouri-Columbia we realized a specific informaticsthesaurus was needed. Several steps were taken toconfirm that this need did exist and to identify itsrange.First, we reviewed the history of the L Tree ofMeSH[l] because it was the first vocabulary toinclude medical informatics terminology and is stillused as a source of medical informaticsterminology. We found that the current L Treeterms were not sufficient to cover the disciplinebecause there were numerous major concepts notcovered. An examination of the thesauri used inthe contributing disciplines and of the medicalinformatics literature both confirmed our view andallowed us to develop a raw vocabulary of medicalinformatics terminology now in use. The resultingthesaurus will contain a manageable number ofterms with an accompanying classification.We believe that the medical informatics thesauruswe are developing more adequately covers theexisting medical informatics discipline thananything currently does. It can also bequickly revised to include the rapidly evolvingterminology of the discipline. The purpose of thispaper is to present the steps we used to create thisnew thesaurus and to discuss our plans for furthertesting, refinement, and publication of thatthesaurus.METHODSOur purpose in developing the thesaurus was toaddress both user and literary warrant in selectingterms for inclusion. User warrant means that theterms chosen for inclusion must be those whichusers in the field would use, while literary warrantmeans that the terms would be found in keydocuments in the literature of that discipline.In order to achieve this goal, we looked at the fourprimary methods of thesaurus construction and usedparts of each of them for our project. The fourmain methods of thesaurus construction, asidentified by Lancaster[2], are to:1. Generate the vocabulary empirically on the basisof indexing a representative set of documents;2. Convert an existing vocabulary;3. Extract the vocabulary from an existing, moregeneral thesaurus or develop a specializedthesaurus within the framework of a general one;4. Collect terms from diverse sources includingglossaries, other publications, and from subjectspecialists.The following discussion shows how we includedfacets of each of these approaches into ourthesaurus construction.0195-4210/94/$5.00 ( 1994 AMIA, Inc. 900Work on this project began in September 1992. Ahistorical review of the MeSH L Tree wasperformed to ascertain the degree and nature of thechanges made in the terminology in this source overthe last thirty-three years.[3] A search of fiftytitles from papers in the 1992 Symposium onComputer Applications in Medical Care (SCAMC)identified terms used in these titles that alsoappeared in the 1992 L Tree. Major concepts in the1992 SCAMC for which no terms appeared in the LTree were also identified. Examples of suchconcepts include Bayesian networks, knowledgebases and knowledge representation, heuristicapproaches, electronic patient records, physicianorder entry, nursing systems and nursinginformatics. These findings indicate that the L Treewould not suffice as a thesaurus for the medicalinformatics literature.Because of the multi-disciplinary nature of themedical informatics field and the lack of acomprehensive thesaurus, seven thesauri from otherfields were examined for relevant terminology forindexing medical informatics articles. The first stepin the thesaurus construction was to compare theterminology in each of these thesauri to see whichterms were used by all, some or only one of them.The thesauri used and the fields represented include:Engineering field:Engineering Information Thesaurus (EI)[4]INSPEC Thesaurus[5]Education/psychology field:Thesaurus of ERIC Descriptors[6]Thesaurus of Psychological Index Terms[7]Medical field:Medical Subiect Headings (MeSH)[8]Computer field:Computer Select® Glossary of Terms[9]Informatics field:In-house list of indexing terms used at theMedical Informatics Information Center at theUniversity of Missouri-Columbia.Terms from each thesaurus were assigned a weightaccording to their importance in the informaticsfield. These weights were assigned to allow us todetermine which terms were most significant to theliterature. A term appearing in both the medicaland the engineering terminology should beconsidered more important than a term carried onlyin the psychology terminology. Thesauri from thefields of engineering (EI and INSPEC) andmedicine (MeSH) received a weight of two. Therest were assigned weights of one. The total weightfor a particular term was determined by how manyand which thesauri included the term.The second step was to study the medicalinformatics literature to determine what terminologythose who work in the field use. The literatureexamined came from journals and proceedings. Thefollowing journals were considered key medicalinformatics journals:1. "Computer Applications in the Biosciences"2. "Computers and Biomedical Research"3. "Computers in Nursing"4. "MD-Computing"5. "Medical Informatics"."JAMIA" was not in existence when this work wasdone, having published its first issue in January1994. Also included were two major conferenceproceedings for the medical informatics field,SCAMC and MEDINFO.From a total population of 1676 articles, 271randomly selected abstracts were reviewed, a 30percent sample. The entire sample was reviewed bytwo members of the project team to determine thekey words used in the abstracts. As a furthercheck, two senior members of the project teamreviewed 30 percent of the sample again. A weightof one was given to each term selected by the firstteam and a weight of two to each term selected bythe second team because the members of the secondteam have more expertise in determining whichterms are significant. These weights were assignedso that, once the entire raw vocabulary had beenassembled, decisions could be made on what termsto eliminate based on the number of occurrences ofthe term and the number of times it was selected byeach reviewer.901The key terms from each abstract were thencollected and entered into a database and the editingprocess began. The initial editing consisted ofeliminating singular vs plural, lexical variants, anduseless terms. The decision was made to prefer theplural over the singular form of terms with someexceptions for singular words that are considered apreferred over their plural form; for example,classification was preferred over classifications andterminology over terminologies. In determining thepreferred term for lexical variants the noun waspreferred over the verb form and either of these waspreferred over the adjective form again with someexceptions for preferred usage. The literature andthe weights that had been assigned throughout thedevelopment of the raw vocabulary assisted us indetermining the preferred variant of a term. Anumber of terms were eliminated because they wereuseless terms; for example, megabytes or houseofficer care or interactive nature. These termscarried weights of one or two which meant they hadonly been chosen from one article by one or both ofthe members of team one and upon examination bythe senior team members were determined to bemeaningless terms for the vocabulary. Also, theterm for an action was preferred to the term for theperson performing the action; for example,education was preferred over educators anddevelopment over developers. We also eliminatedany hyphenated terms in favor of the non-hyphenated terms as in computer-assisted instructionor CD-ROM. Phrases with extra unnecessary termswere eliminated in favor of the shortest versionapplicable. Examples of this include the exclusionof automatic indexing method and automaticindexing program in preference to automaticindexing and the exclusion of diagnostic decisionsupport system and diagnostic decision supportprogram in preference to diagnostic decisionsupport. From an original 5759 terms these editsreduced the terms to 5462. Weights were addedtogether when a term was combined with another toproduce a total reviewer weight.The third step consisted of a review of glossariesfrom experts in the field to see what terms theyused in their texts. Blois[10], Covvey[1 1],Shortliffe[12] and Barnett[13] were used asexperts for this section. The glossaries werereviewed to ascertain which terms were alreadyincluded in the raw vocabulary. Terms not alreadyincluded were added to the raw vocabulary. Aweight of two was assigned to terms in the Barnettand Shortliffe glossaries because they are morerecent publications. A weight of one was assignedto the Blois and Covvey terms. Therefore, a newterm appearing in all four glossaries would carry aweight of six.Finally, the terms identified in each of the firstthree steps were compared to one another to seewhich ones were present in which sources. Forthose terms that existed in both the literature andthe thesauri, the weights for each source wereincluded in the database. There were some termsfound only in the thesauri. If the thesauri weight ofthese terms was four or above, they were includedin the raw vocabulary list. The terms found only inthe expert glossaries were added to the rawvocabulary as bolded entries so that they wouldstand out when terms were reviewed. They werereviewed for what sources they belonged to as wellas their weight. This insured that they would notbe eliminated simply because they had a lowweight.RESULTSWhen all the terms had been identified, the processof refining the raw vocabulary began. The aim wasto reduce the original 5462 terms to a manageablesize which Batty defines as "as small as possiblebut includes everything with a good size beingapproximately 2000 terms."[14] First, weclosely examined the terms with a literature weightof 1 or 2 because that weight meant the term wasselected by only one or two reviewers and fromonly one article. There were 3368 terms in thiscategory. We eliminated 1738 terms, or 52%, ofthem in this step which left 3724 terms in thevocabulary.The next step in the refinement process was tocreate a group of categories and begin to create thehierarchical structure for the classification. Themain concepts then were:1.2.3.4.5.6.7.8.9.10.BusinessComputer and Data ProcessingEducationEngineeringLanguage/LibraryLegalMathematicsNursingDentistryVeterinary Medicine902All terms were sorted into one of these categories.Terms that did not fit were placed in a separatecategory for further review. Many of the latterterms were eliminated from the vocabulary asunimportant. Examples of terms eliminated includecrime, shared data, and system environment. Themajor categories were refined in the second step ofthis process to include:1. Business2. Computer and Data Processing withmathematics and engineering as sub-categories3. Education4. Health Care Informatics which includes thehealth category5. LanguageALibraryThe categories of legal, nursing, dentistry andveterinary medicine were absorbed into the othercategories.Once the terms were divided into categories, webegan to establish a hierarchy of terms within eachcategory. At this point, preferred terms werechosen for concepts which had several synonyms.Part of this final refinement was to decide howacronyms and geographic terms were to be handled.Not all acronyms were retained in the vocabulary.For those we did retain, it was decided to put theacronym in parentheses behind its spelled outversion wherever it appeared in the thesaurus.Examples of this would be Computer AssistedInstruction (CAI) or Integrated AdvancedInformation Management Systems (IAIMS). Forgeographic names users of the thesaurus will bereferred to the Z Tree of MeSH which contains acomprehensive listing of geographical placenames.[15] Users will also be referred to theMeSH Subject Headings for specific medical termsas the purpose of this project was not to recreatethe entire medical vocabulary but only to includeterms that specifically addressed informatics and itsrelated fields. The decision to handle acronyms,geographic names, and specific medical terms inthis manner eliminated 1378 terms which gave us atotal of 2315 terms remaining in the vocabulary.When completed, our medical informatics thesauruswill contain a manageable number of terms,arranged within a hierarchical structure within thefinal five categories. The thesaurus will then betested against the 1994 SCAMC titles to see if itcontains the necessary terms to cover the conceptsin the document. We also plan to test the documentby sending it to experts in the field for their review,use and comments. Finally, we will publish thethesaurus in both a print and an electronic version.DISCUSSIONThe first formal work in the terminology of medicalinformatics was at NLM. They began to covermedical informatics terminology in a minimal wayin their first L Tree developed in 1960. Majorrevisions to this L Tree in 1963, 1965, 1966, 1975,and 1987 have added new terms, eliminated termsand changed the hierarchical relationship of terms.Rada and others[16] helped in this revisionprocess in 1986 when they developed a medicalinformatics thesaurus. "It consisted of termsdeveloped by an automatic merging of the thesaurusused by the "Association of Computing Machinery"and the Information Sciences component of the"Medical Subject Headings" from the NationalLibrary of Medicine (NLM). The terminology wasthen pruned by eliminating terms not related tothose in the MEDINFO keyword list or not in themedical informatics literature." The terminologyfrom this thesaurus was incorporated into NLM's1987 version of the L Tree.Currently Rada is working with the Committee forEuropean Normalization (CEN) under theInternational Medical Informatics Association(IMIA). This work parallels our project.[17],[18] They have produced a new 200word thesaurus.Rada's terminology still leaves a wide area ofinformatics unrepresented since it is focused on thecreation of a framework for standards development.The Rada et. al. work and this project also differ inmethodology of thesaurus construction and size ofthe vocabulary.Rada uses a computerized technique to extractpossible terms. This method achieves literarywarrant but makes little formal effort to ensure userwarrant. He has published the list and requestedcomments from members of the informaticscommunity. Our methods of construction weremore extensive and varied and achieve both userand literary warrant. As shown, our approach usesliterature review, thesauri review, review of expertglossaries, and comparisons of all sources forsimilarity to achieve both literary and user warrant903for our terminology.The small size of Rada's vocabulary (200)necessarily would force users to use broad terms forsome concepts. With a larger thesaurus of 2000 ormore terms the user is more likely to be able toachieve an acceptable level of specificity.CONCLUSIONOur research first identified a need for a newmedical informatics thesaurus. Then, using existingthesauri, medical informatics literature, and theterminology of experts in the field to identifyappropriate concepts and terms, we are creating anew thesaurus to cover the discipline. Continuedrefinement will be accomplished by testing thethesaurus against the 1994 SCAMC titles and byasking experts in the field to use and review thethesaurus and give us feedback. The thesaurus willbe published in both a print and an electronicformat so that it is readily available for use byeveryone in the field. We plan to supportcontinuous revision of the thesaurus to keep itcurrent with the ever expanding field of medicalinformatics.References1. Li Z, Ogg N, Sievert M, and Mitchell J. "On theGrowth and Trimming of the L Trees ofMeSH." Symposium on Computer Applicationsin Medical Care. 1993: 892.2. Lancaster FW. Vocabulary Control forInformation Retrieval. 1st ed. Arlington, VA:Information Resources Press, 1972: 27.3. Li Z, et al, 892.4. Milstead JL. ed. Engineering InformationThesaurus. 1st ed. Hoboken, NJ: EngineeringInformation Inc, 1992.5. Institution of Electrical Engineers. INSPECThesaurus. Old Woking, Surrey, Eng: UnwinBrothers Limited, 1991.6. Houston JE. ed. Thesaurus of ERIC Descriptors.12th ed. Phoenix, AZ: ORYX Press, 1990.7. Walker A. Jr. ed. Thesaurus of Ps cholo icalIndex Terms. 6th ed. Arlington, VA: AmericanPsychological Association, 1991.8. National Library of Medicine. Medical SubjectHeadings. Annotated Alphabetic List. Bethesda,MD: Medical Subject Headings Section, LibraryOperations, National Library of Medicine, 1992.9. Lotus Development Corporation and ZiffCommunications Company. Computer Select®Glossary of Terms. 5th ed. New York, NY: ZiffCommunications Company, 1992.10. Blois MS. Information and Medicine: TheNature of Medical Descriptions. Berkeley:University of California Press, 1984: 298 p.11. Covvey HD, McAllister NH. Computers in thePractice of Medicine. Vol. I-Introduction toComputing Concepts. Reading, MA: Addison-Wesley, 1980: 266 p.12. Shortliffe EH, Perreault LE, eds. MedicalInformatics: Computer Applications in HealthCare. Reading, MA: Addison-Wesley, 1990:715 p.13. Barnett GO. "Core Topics in MedicalInformatics." Personal Correspondence, 1992.14. Batty CD. Thesaurus ConstructionWorkshop. 55th Annual Meeting of theAmerican Society for Information Science(ASIS). Oct. 22, 1992; Pittsburgh, PA.15. National Library of Medicine. Medical SubiectHeadings. Tree Structures. Bethesda, MD:Medical Subject Headings Section, LibraryOperations, National Library of Medicine,1960-1992.16. Rada R, Calhoun F, Mili E, Singer SJ, Blum B,and Orthnerr H. "A medical informaticsthesaurus." MEDINFO '86. Washington, DC.Amsterdam: North-Holland, 1986: 1164-1172.17. Rada R, Ghaoui C, Russell J, and Taylor M."Approaches to the construction of a medicalinformatics glossary and thesaurus." MedicalInformatics. 18(1). 1993: 69-78.18. Rada R. "Vocabulary." SigBio. 14(1). Jan.1994: 5-16.904

Construction of a medical informatics thesaurus

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Construction of a medical informatics thesaurus

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