Feasibility of Using Clinical Element Models (CEM) to Standardize Phenotype Variables in the Database of Genotypes and Phenotypes (dbGaP)

PLoS ONE

Volumn 8, Issue 9, 2013, Pages

  Lin, Ko Wei ^a   Tharp, Melissa ^a   Conway, Mike ^a   Hsieh, Alexander ^a   Ross, Mindy ^a   Kim, Jihoon ^a   Kim, Hyeon Eui ^a  

^a UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; CLINICAL ELEMENT MODEL; DATABASE OF GENOTYPES AND PHENOTYPES; GENETIC DATABASE; MATHEMATICAL MODEL; NATURAL LANGUAGE PROCESSING; PHENOTYPE;

DATABASES, GENETIC; FEMALE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; MALE; MODELS, GENETIC; PHENOTYPE;

EID: 84884217961     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0076384     Document Type: Article

References (39)

1. Mailman MD, Feolo M, Jin Y, Kimura M, Tryka K, et al. (2007) The NCBI dbGaP database of genotypes and phenotypes. Nat Genet 39: 1181-1186. PubMed: 17898773.
2. National Center for Biotechnology Information, U.S National Library of Medicine.The database of Genotypes and phenotypes (dbGaP). Available: http://www.ncbi.nlm.nih.gov/gap. Accessed 15 July 2013.
3. Hripcsak G, Friedman C, Alderson PO, DuMouchel W, Johnson SB, et al. (1995) Unlocking clinical data from narrative reports: a study of natural language processing. Ann Intern Med 122: 681-688. doi:10.7326/0003-4819-122-9-199505010-00007. PubMed: 7702231.
4. Intermountain Healthcare and GE Healthcare/Caradigm. The Clinical Element Model Browser. Available: http://www.clinicalelement.com/. Accessed 15 April 2013.
5. Lin KW, Ross MK, Ohno-Machado L, Finn PW, Kim HE, (2012) Testing the adequacy of a public GWAS database as a cohort discovery tool. Am J Respir Crit Care Med 185: A5778.
6. Pan H, Tryka KA, Vreeman DJ, Huggins W, Phillips MJ, et al. (2012) Using PhenX measures to identify opportunities for cross-study analysis. Hum Mutat 33: 849-857. doi:10.1002/humu.22074. PubMed: 22415805.
7. National Human Genome Research Institute The eMERGE Network: Electronic Medical Records and Genomics. Available: http://emerge.mc.vanderbilt.edu/. Accessed 20 December 2012.
8. Pathak J, Wang J, Kashyap S, Basford M, Li R, et al. (2011) Mapping clinical phenotype data elements to standardized metadata repositories and controlled terminologies: the eMERGE Network experience. J Am Med Inform Assoc 18: 376-386. doi:10.1136/amiajnl-2010-000061. PubMed: 21597104.
9. Pathak J, Pan H, Wang J, Kashyap S, Schad PA, et al. (2011) Evaluating Phenotypic Data Elements for Genetics and Epidemiological Research: Experiences from the eMERGE and PhenX Network Projects. AMIA Summits on Translational Science proceedings AMIA Summit on Translational. Science:(2011): pp. 41-45.
10. National Cancer Institute NCI thesaurus. Available: http://ncit.nci.nih.gov/. Accessed 20 December 2012.
11. National Cancer Institute Cancer Data Standards Registry and Repository (caDSR). Available: https://cabig.nci.nih.gov/community/concepts/caDSR/. Accessed 20 December 2012.
12. Clinical Data Interchange Standards Consortium. Study Data Tabulation Model. Available: http://www.cdisc.org/sdtm/. Accessed 20 December 2012.
13. The International Health Terminology Standards Development Organization. SNOMED Clinical Terms® (SNOMED CT®). Available: http://www.nlm.nih.gov/research/umls/Snomed/snomed_main.html. Accessed 20 December 2012.
14. The Office of the National Coordinator for Health Information Technology. Strategic Health IT Advanced Research Projects (SHARP) Research Focus. Area 4- Secondary Use of EHR Data. Available: http://informatics.mayo.edu/sharp/. Accessed 23 March 2013.
15. Chute CG, Pathak J, Savova GK, Bailey KR, Schor MI, et al. (2011) The SHARPn project on secondary use of Electronic Medical Record data: progress, plans, and possibilities. AMIA Annual Symposium Proceedings/ AMIA Symposium: 2011: 248-256 PubMed: 22195076.
16. Rea S, Pathak J, Savova G, Oniki TA, Westberg L, et al. (2012) Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: the SHARPn project. J Biomed Inform 45: 763-771. doi:10.1016/j.jbi.2012.01.009. PubMed: 22326800.
17. Friedman C, Kra P, Yu H, Krauthammer M, Rzhetsky A, (2001) GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles. Bioinformatics 17 (Suppl 1):: S74-S82. doi:10.1093/bioinformatics/17.suppl_1.S74. PubMed: 11472995.
18. Navigli R, Velardi P, (2008) Glossaries to Ontologies: Extracting Semantic Structure from Textual Definitions. In: Buitelaar P, Cimiano P, eds. Ontology Learning and Population: Bridging the Gap between Text and Knowledge. Washington DC: IOS Press. pp. pp. 71-87.
19. Rindflesch TC, Fiszman M, (2003) The interaction of domain knowledge and linguistic structure in natural language processing: interpreting hypernymic propositions in biomedical text. J Biomed Inform 36: 462-477. doi:10.1016/j.jbi.2003.11.003. PubMed: 14759819.
20. Tobias J, Chilukuri R, Komatsoulis GA, Mohanty S, Sioutos N, et al. (2006) The CAP cancer protocols--a case study of caCORE based data standards implementation to integrate with the Cancer Biomedical Informatics Grid. BMC Med Inform Decis Mak 6: 25. doi:10.1186/1472-6947-6-25. PubMed: 16787533.
21. International Health Terminology Standards Development Organisation. SNOMED CT® User Guide. Available: http://www.snomed.org/ug. Accessed 15 April 2013.
22. Health Level Seven International (HL7). Health Level Seven (HL7) Reference Information Model (RIM). Available: http://www.hl7.org/implement/standards/rim.cfm. Accessed 15 April 2013.
23. Navas H, Lopez Osornio A, Gambarte L, Elías Leguizamón G, Wasserman S, et al. (2010) Implementing rules to improve the quality of concept post-coordination with SNOMED CT. Stud Health Technol Inform 160: 1045-1049. PubMed: 20841843.
24. Green JM, Wilcke JR, Abbott J, Rees LP, (2006) Development and evaluation of methods for structured recording of heart murmur findings using SNOMED-CT post-coordination. J Am Med Inform Assoc 13: 321-333. doi:10.1197/jamia.M1973. PubMed: 16501179.
25. Rector A, Iannone L, (2012) Lexically suggest, logically define: quality assurance of the use of qualifiers and expected results of post-coordination in SNOMED CT. J Biomed Inform 45: 199-209. doi:10.1016/j.jbi.2011.10.002. PubMed: 22024315.
26. Schulz S, Schober D, Daniel C, Jaulent MC, (2010) Bridging the semantics gap between terminologies, ontologies, and information models. Stud Health Technol Inform 160: 1000-1004. PubMed: 20841834.
27. Carlson D, Farkash A, Timm JT, (2010) A model-driven approach for biomedical data integration. Stud Health Technol Inform 160: 1164-1168. PubMed: 20841867.
28. Heymans S, McKennirey M, Phillips J, (2011) Semantic validation of the use of SNOMED CT in HL7 clinical documents. Journal of biomedical semantics 2: 2. PubMed: 21762489.
29. Coyle J, Heras Y, Oniki T, Huff S, (2008) Clinical Element Model. Available: http://informatics.mayo.edu/sharp/images/9/91/CEReference20081114.pdf. Accessed 20 December 2012.
30. Wu ST, Kaggal VC, Dligach D, Masanz JJ, Chen P, et al. (2013) A common type system for clinical natural language processing. Journal of biomedical semantics 4: 1.
31. Johnson AD, O'Donnell CJ, (2009) An open access database of genome-wide association results. BMC Med Genet 10: 6. doi:10.1186/1471-2350-10-6. PubMed: 19161620.
32. Chute CG, Cohn SP, Campbell KE, Oliver DE, Campbell JR, (1996) The content coverage of clinical classifications. For The Computer-Based Patient Record Institute's Work Group on Codes & Structures. J Am Med Inform Assoc 3: 224-233. doi:10.1136/jamia.1996.96310636. PubMed: 8723613.
33. Humphreys BL, McCray AT, Cheh ML, (1997) Evaluating the coverage of controlled health data terminologies: report on the results of the NLM/AHCPR large scale vocabulary test. J Am Med Inform Assoc 4: 484-500. doi:10.1136/jamia.1997.0040484. PubMed: 9391936.
34. Lin KW, Tharp M, Conway M, Ross M, Hsieh A, et al. (2012) Feasibility of Using Clinical Element Models (CEM) to Standardize Phenotype Variables in the Database of Genotypes and Phenotypes (dbGaP). 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology, La Jolla, CA, USA. pp. 123.
35. the Regenstrief Institute, Inc and the LOINC Committee Logical Observation Identifiers Names and Codes (LOINC®). Available: http://loinc.org/. Accessed 20 December 2012.
36. Tao C, Jiang G, Oniki TA, Freimuth RR, Zhu Q, et al. (2012) A semantic-web oriented representation of the clinical element model for secondary use of electronic health records data. J Am Med Inform Assoc.
37. Hsieh A, Doan SC, Michael, Lin, Ko-Wei Kim, Hyeoneui, (2012) Demographics Identification: Variable Extraction Resource (DIVER). 2012 IEEE Second International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB). La Jolla, CA, USA. pp. 40-49.
38. Percha B, Nassif H, Lipson J, Burnside E, Rubin D, (2012) Automatic classification of mammography reports by BI-RADS breast tissue composition class. J Am Med Inform Assoc 19: 913-916. doi:10.1136/amiajnl-2011-000607. PubMed: 22291166.
39. Harkema H, Chapman WW, Saul M, Dellon ES, Schoen RE, et al. (2011) Developing a natural language processing application for measuring the quality of colonoscopy procedures. J Am Med Inform Assoc 18 (Suppl 1):: i150-i156. doi:10.1136/jamia.2010.005520. PubMed: 21946240.