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Limning the CTS Ontology Landscape

Limning the CTS Ontology Landscape. Barry Smith http://ontology.buffalo.edu/smith. What exists. HIPAA. Non-public. Basic science (e.g. pharma data). Lab#1 data. Hospital #1 data. Hospital#2 data. Clinic #1 data. translation. Data Warehouse. Basic science data. Public. Allied

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Limning the CTS Ontology Landscape

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  1. Limning the CTS Ontology Landscape Barry Smith http://ontology.buffalo.edu/smith

  2. What exists HIPAA Non-public Basic science (e.g. pharma data) Lab#1 data Hospital #1 data Hospital#2 data Clinic #1 data translation Data Warehouse Basic science data Public

  3. Allied health patient other provider PAYER Secondary users portal HILS Imaging lab PAS ECG etc billing Security / access control Path lab DSS UPDATE QUERY Enterprise notifications Msg gateway Comprehensive Basic LAB Multimedia genetics identity realtime gateway workflow demographics guidelines protocols telemedicine Clinical ref data terms Online Demographic registries Clinical models Interactions DS Online drug, Interactions DB Local modelling Online archetypes Online terminology Components EHR Patient Record

  4. What every CTS institution would like to have HIPAA Non-public Basic science (e.g. pharma data) Lab#1 data Hospital #1 data Hospital#2 data Clinic #1 data translation translation Data Warehouse Basic science data Public

  5. More (and better?) EHR data HIPAA Non-public Basic science (e.g. pharma data) Lab#1 data Hospital #1 data Hospital#2 data Clinic #1 data “Meaningful Use” Coding Systems translation translation Data Warehouse Basic science data Public

  6. Strategies to overcome the complexity and incompatibility of coding schemes of EHRs HIPAA Non-public Basic science (e.g. pharma data) Lab#1 data Hospital #1 data Hospital#2 data Clinic #1 data “Meaningful Use” Coding Systems translation translation Data Warehouse Basic science data i2b2 (with ontology cells) HOM (Health Ontology Mapper Public

  7. Coding schemes and terminologies ICD, SNOMED, … • are slow to change • do not interoperate well with structured basic biology data • are not fully open source • are tied to multiple competing EHR systems • are not optimized for research And therefore • do not support translation

  8. It is generally recognized that ontologies must play some part in the solution to these problems Non-public HIPAA Basic science (e.g. pharma data) Roswell data Hospital #1 data Hospital#2 data Clinic #1 data Gene Ontology Data Warehouse HOM (Health Ontology Mapper i2b2 (with ontology cells) Basic science data Public

  9. Proposed solution: extend the Gene Ontology with a consistent set of small, agile, open ontology modules for clinical domains Non-public HIPAA Basic science (e.g. pharma data) Roswell data Hospital #1 data Hospital#2 data Clinic #1 data Open Biomedical Ontologies Foundry Data Warehouse Basic science data Public

  10. Open Biomedical Ontologies (OBO) Foundry (First Draft)

  11. OBO Foundry approach extended into other domains

  12. OGMS and Its Extensions Ontology of Medically Relevant Social Entities (OMRSE) Vital Sign Ontology (VSO) Mental Diseases Examples of OGMS applied to specific diseases. Oral Health and Disease ontology Infectious Disease Ontology (IDO) http://code.google.com/p/ogms/

  13. IDO and Its Extensions IDO – Brucellosis IDO – Dengue Fever IDO – Influenza IDO – Malaria IDO – Staphylococcus Aureus Bacteremia IDO - Vector Surveillance and Management VO – Vaccine Ontology

  14. HIPAA Roswell data Hospital #1 data Hospital#2 data Clinic #1 data Non-public Basic science (e.g. pharma data) Data Warehouse Open Biomedical Ontologies Foundry Alzheimer’s Disease Staph Aureus Bacteremia Sleep Dis-orders Using OGMS as basis, create small ontologies for specific clinical domains Basic science data Public

  15. HIPAA Non-public Roswell data Hospital #1 data Hospital#2 data Basic science (e.g. pharma data) Clinic #1 data Data Warehouse Semi-public Resource data Publications, patents, equipment, samples, expertise, grants, lab activities, clinical research activities, clinical trials Clinical Neurology Cancer Pathology etc. Extend this approach to the workings of the CTS institution itself Basic science data

  16. HIPAA Non-public Roswell data Hospital #1 data Hospital#2 data Basic science (e.g. pharma data) Clinic #1 data Data Warehouse Semi-public Resource data Publications, patents, equipment, samples, expertise, grants, lab activities, clinical research activities, clinical trials Clinical Trial Ontology Consent Ontology etc. Extend this approach to the workings of the CTS institution itself Open Biomedical Ontologies Foundry OGMS OBI : Ontology for Biomedical Investigations

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