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Controlled vocabularies for medical and health research

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This document discusses controlled vocabularies in medicine and health. It defines controlled vocabularies as structured lists of terms used to describe and index medical resources that improve search, description, communication and research. Examples of health vocabularies include MeSH, SNOMED CT, and LOINC. Controlled vocabularies help increase precision in searching by describing relationships between concepts through hierarchies, equivalence and associations. Resources and browsers are provided to access and use standard health vocabularies.

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Kate LeMay Controlled vocabularies in medicine and health August 2016 Senior Research Data Specialist
Why use controlled vocabularies? ? Improved search & retrieval of digital health resources ? Improved description of digital health resources ? Bridge gaps in health communication ? Ask more specific or complex research questions ? Improve researcher interaction with health data
Vocabularies increase precision in searching
Cumulative Index of Nursing and Allied Health Literature (CINAHL) RxN orm Australian Doctor Command Language (DOCLE) Health Vocabulary examples
Discovery services that make use of health vocabularies
Central Nervous System Brain Meninges Spinal Cord Hierarchical EquivalenceAssociative Nursing Nursing Education is related to Parkinsons Disease Paralysis Agitans is the same as Relationships described by vocabularies
Acute Coronary Syndrome Myocardial Ischemia Angina Pectoris Coronary Disease Myocardial Infarction Myocardial Stunning Shock, Cardiogeni c Hierarchical Associative Equivalence Relationships described by vocabularies
Making use of alternate labels / equivalence relationships in searching Equivalence
Myocardial Infarction Myocardial Infarction is the same as Equivalence Relationships Crosswalks between vocabularies
Browsers that include health CVs along with non-health CVs Browsers that include only health CVs Browsers that include a single health CV MeSH Browser Browser Health vocabulary browsers
Resources Australian Digital Health Agency Clinical Terminology: https://www.digitalhealth.gov.au/get-started-with- digital-health/what-is-digital-health/clinical-terminology SHRIMP Browser: Database of SNOMED CT-AU concepts and information about those concepts https://aehrc.com/research/software/shrimp/ National Clinical Terminology and Information Service (NCTIS) Terminology Access: Download SNOMED CT-AU and Australian Medicines Terminology https://www.digitalhealth.gov.au/implementation-resources/terminology-access International Health Terminology Standards Development Organisation (IHTSDO) http://www.ihtsdo.org/ on Twitter @SnomedCT Australian Clinical Terminology User Group (AuCT-UG): http://auctug.com/ on Twitter @auctug
Resources Unified Medical language System (UMLS): Software apps that bring together health & biomedical vocabularies across computer systems http://www.nlm.nih.gov/research/umls/ UMLS Metathesaurus Browser: Database of concepts from selected health and biomedical vocabularies http://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/index.html UMLS SNOMED-CT Browser: Database of SNOMED-CT concepts and information about those concepts https://www.nlm.nih.gov/research/umls/Snomed/snomed_browsers.html MeSH Browser: Database of MeSH concepts and information about those concepts http://www.nlm.nih.gov/mesh/MBrowser.html MeSH on Demand: A tool for recognising MeSH concepts in text https://www.nlm.nih.gov/mesh/MeSHonDemand.html MetaMap: A tool for recognising UMLS concepts in text http://metamap.nlm.nih.gov/ RxNav: Database of drug vocabulary concepts http://mor.nlm.nih.gov/download/rxnav/index.html UMLS Source Vocabulary documentation: Alphabetical list of vocabularies that power the UMLS http://www.nlm.nih.gov/research/umls/sourcereleasedocs/index.html
Resources Healthbase AMT Browser: http://australia.healthbase.info/amt/ IHTSDO SNOMED CT Browser: http://browser.ihtsdotools.org/ LOINC Browser: https://search.loinc.org/ MedDRA Desktop Browser: http://www.meddra.org/browsers NCBI MeSH Browser: http://www.ncbi.nlm.nih.gov/mesh OBO Foundry: http://www.obofoundry.org/ Biomedical Ontology BioPortal: http://bioportal.bioontology.org/ BioPortal Source Vocabs: http://bioportal.bioontology.org/resource_index
Resources Hadlow, Jan and Pitts, Marian. ＾The understanding of common health terms by doctors, nurses and patients.￣ Social Science & medicine 32.2 (1991): 193-196. Web. <http://www.sciencedirect.com/science/article/pii/027795369190059L>. Hammond, W. Edward. ＾Electronic medical records - Getting it right and going to scale.￣ Commonwealth Fund (2004). Web. <http://www.commonwealthfund.org/~/media/files/publications/fund-report/2004/jan/electronic-medical-records-- getting-it-right-and-going-to-scale/hammond_elecmedrecords_695-pdf.pdf>. Harland, Lee et. al. "Empowering Industrial Research with Shared Biomedical Vocabularies." Drug Discovery Today 16.21/22 (2011): 940-947. Web. <http://www.ncbi.nlm.nih.gov/pubmed/21963522>. Lerner, E. Brooke et. al. ＾Medical communication: Do our patients understand?￣ American Journal of Emergency Medicine 18.7 (2000): 764-766. Web. <http://www.ncbi.nlm.nih.gov/pubmed/11103725>. Murray, Tom and Berberian, Laura. ＾The importance of structured data elements in EHRs.￣ Computerworld Healthcare IT Spotlight (2011). Web. <http://www.computerworld.com/article/2470987/healthcare-it/the-importance-of-structured-data- elements-in-ehrs.html>. Sorani, Marco D. et. al. ＾Clinical and biological data integration for biomarker discovery.￣ Drug Discovery Today 15.17/18 (2010): 741-748. Web. <http://www.ncbi.nlm.nih.gov/pubmed/20558318>. Truran, Donna, et. al. ＾Using SNOMED CT-enabled data collections in a national clinical research program: primary care data can be used in secondary studies.￣ HIC 2009: frontiers in health informatics, Health Informatics Society of Australia, Canberra, Australia (2009) 1-18. Web. <http://ro.uow.edu.au/ahsri/327/>. Zielstorff, Rita D. ＾Controlled vocabularies for consumer health.￣ Journal of Biomedical Informatics 36 (2003): 326-333. Web. <http://www.ncbi.nlm.nih.gov/pubmed/14643728>.
Senior Research Data Specialist kate.lemay@ands.org.au With thanks to Jane Frazier for the original slides from which these were developed Kate LeMay

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Controlled vocabularies for medical and health research

  • 1. Kate LeMay Controlled vocabularies in medicine and health August 2016 Senior Research Data Specialist
  • 2. Why use controlled vocabularies? ? Improved search & retrieval of digital health resources ? Improved description of digital health resources ? Bridge gaps in health communication ? Ask more specific or complex research questions ? Improve researcher interaction with health data
  • 4. Cumulative Index of Nursing and Allied Health Literature (CINAHL) RxN orm Australian Doctor Command Language (DOCLE) Health Vocabulary examples
  • 5. Discovery services that make use of health vocabularies
  • 6. Central Nervous System Brain Meninges Spinal Cord Hierarchical EquivalenceAssociative Nursing Nursing Education is related to Parkinsons Disease Paralysis Agitans is the same as Relationships described by vocabularies
  • 8. Making use of alternate labels / equivalence relationships in searching Equivalence
  • 10. Browsers that include health CVs along with non-health CVs Browsers that include only health CVs Browsers that include a single health CV MeSH Browser Browser Health vocabulary browsers
  • 11. Resources Australian Digital Health Agency Clinical Terminology: https://www.digitalhealth.gov.au/get-started-with- digital-health/what-is-digital-health/clinical-terminology SHRIMP Browser: Database of SNOMED CT-AU concepts and information about those concepts https://aehrc.com/research/software/shrimp/ National Clinical Terminology and Information Service (NCTIS) Terminology Access: Download SNOMED CT-AU and Australian Medicines Terminology https://www.digitalhealth.gov.au/implementation-resources/terminology-access International Health Terminology Standards Development Organisation (IHTSDO) http://www.ihtsdo.org/ on Twitter @SnomedCT Australian Clinical Terminology User Group (AuCT-UG): http://auctug.com/ on Twitter @auctug
  • 12. Resources Unified Medical language System (UMLS): Software apps that bring together health & biomedical vocabularies across computer systems http://www.nlm.nih.gov/research/umls/ UMLS Metathesaurus Browser: Database of concepts from selected health and biomedical vocabularies http://www.nlm.nih.gov/research/umls/knowledge_sources/metathesaurus/index.html UMLS SNOMED-CT Browser: Database of SNOMED-CT concepts and information about those concepts https://www.nlm.nih.gov/research/umls/Snomed/snomed_browsers.html MeSH Browser: Database of MeSH concepts and information about those concepts http://www.nlm.nih.gov/mesh/MBrowser.html MeSH on Demand: A tool for recognising MeSH concepts in text https://www.nlm.nih.gov/mesh/MeSHonDemand.html MetaMap: A tool for recognising UMLS concepts in text http://metamap.nlm.nih.gov/ RxNav: Database of drug vocabulary concepts http://mor.nlm.nih.gov/download/rxnav/index.html UMLS Source Vocabulary documentation: Alphabetical list of vocabularies that power the UMLS http://www.nlm.nih.gov/research/umls/sourcereleasedocs/index.html
  • 13. Resources Healthbase AMT Browser: http://australia.healthbase.info/amt/ IHTSDO SNOMED CT Browser: http://browser.ihtsdotools.org/ LOINC Browser: https://search.loinc.org/ MedDRA Desktop Browser: http://www.meddra.org/browsers NCBI MeSH Browser: http://www.ncbi.nlm.nih.gov/mesh OBO Foundry: http://www.obofoundry.org/ Biomedical Ontology BioPortal: http://bioportal.bioontology.org/ BioPortal Source Vocabs: http://bioportal.bioontology.org/resource_index
  • 14. Resources Hadlow, Jan and Pitts, Marian. ＾The understanding of common health terms by doctors, nurses and patients.￣ Social Science & medicine 32.2 (1991): 193-196. Web. <http://www.sciencedirect.com/science/article/pii/027795369190059L>. Hammond, W. Edward. ＾Electronic medical records - Getting it right and going to scale.￣ Commonwealth Fund (2004). Web. <http://www.commonwealthfund.org/~/media/files/publications/fund-report/2004/jan/electronic-medical-records-- getting-it-right-and-going-to-scale/hammond_elecmedrecords_695-pdf.pdf>. Harland, Lee et. al. "Empowering Industrial Research with Shared Biomedical Vocabularies." Drug Discovery Today 16.21/22 (2011): 940-947. Web. <http://www.ncbi.nlm.nih.gov/pubmed/21963522>. Lerner, E. Brooke et. al. ＾Medical communication: Do our patients understand?￣ American Journal of Emergency Medicine 18.7 (2000): 764-766. Web. <http://www.ncbi.nlm.nih.gov/pubmed/11103725>. Murray, Tom and Berberian, Laura. ＾The importance of structured data elements in EHRs.￣ Computerworld Healthcare IT Spotlight (2011). Web. <http://www.computerworld.com/article/2470987/healthcare-it/the-importance-of-structured-data- elements-in-ehrs.html>. Sorani, Marco D. et. al. ＾Clinical and biological data integration for biomarker discovery.￣ Drug Discovery Today 15.17/18 (2010): 741-748. Web. <http://www.ncbi.nlm.nih.gov/pubmed/20558318>. Truran, Donna, et. al. ＾Using SNOMED CT-enabled data collections in a national clinical research program: primary care data can be used in secondary studies.￣ HIC 2009: frontiers in health informatics, Health Informatics Society of Australia, Canberra, Australia (2009) 1-18. Web. <http://ro.uow.edu.au/ahsri/327/>. Zielstorff, Rita D. ＾Controlled vocabularies for consumer health.￣ Journal of Biomedical Informatics 36 (2003): 326-333. Web. <http://www.ncbi.nlm.nih.gov/pubmed/14643728>.
  • 15. Senior Research Data Specialist kate.lemay@ands.org.au With thanks to Jane Frazier for the original slides from which these were developed Kate LeMay