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Limning the CTS Ontology Landscape Barry Smith http://ontology.buffalo.edu/smith 1 What exists HIPAA Non-public Hospital #1 data Hospital #2 data Clinic #1 data Lab#1 data Basic science (e.g. pharma data) translation Data Warehouse Basic science data Public 2 Components patient PAYER Secondary users portal Allied health other provider HILS Imaging lab PAS DSS UPDATE QUERY Enterprise Comprehensive Path lab notifications Msg gateway Basic Patient Record identity EHR Clinical ref data Clinical models Interactions DS Local modelling Online drug, Interactions DB With thanks to Tom Beale, Ocean Informatics Multimedia genetics LAB workflow realtime gateway demographics Online Demographic registries ECG etc billing terms guidelines protocols Online terminology Online archetypes telemedicine What every CTS institution would like to have HIPAA Non-public Hospital #1 data Hospital #2 data Clinic #1 data Lab#1 data Basic science (e.g. pharma data) translation translation Data Warehouse Basic science data Public 4 More (and better?) EHR data HIPAA Non-public Hospital #1 data Hospital #2 data Clinic #1 data Lab#1 data “Meaningful Use” Coding Systems Basic science (e.g. pharma data) translation translation Data Warehouse Basic science data Public 5 Strategies to overcome the complexity and incompatibility of coding schemes of EHRs HIPAA Non-public Hospital #1 data Hospital #2 data Clinic #1 data Lab#1 data “Meaningful Use” Coding Systems Basic science (e.g. pharma data) translation translation Data Warehouse i2b2 (with ontology cells) HOM (Health Ontology Mapper Basic science data Public 6 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 7 It is generally recognized that ontologies must play some part in the solution to these problems Non-public HIPAA Hospital #1 data Hospital #2 data Clinic #1 data Roswell data Data Warehouse i2b2 (with ontology cells) HOM (Health Ontology Mapper Basic science (e.g. pharma data) Gene Ontology Basic science data Public 8 Proposed solution: extend the Gene Ontology with a consistent set of small, agile, open ontology modules for clinical domains Non-public HIPAA Hospital #1 data Hospital #2 data Clinic #1 data Roswell data Basic science (e.g. pharma data) Data Warehouse Open Biomedical Ontologies Foundry Basic science data Public 9 RELATION TO TIME CONTINUANT INDEPENDENT OCCURRENT DEPENDENT GRANULARITY ORGAN AND ORGANISM Organism (NCBI Taxonomy) CELL AND CELLULAR COMPONENT Cell (CL) MOLECULE Anatomical Organ Entity Function (FMA, (FMP, CPRO) Phenotypic CARO) Quality (PaTO) Cellular Cellular Component Function (FMA, GO) (GO) Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Biological Process (GO) Molecular Process (GO) Open Biomedical Ontologies (OBO) Foundry (First Draft) 10 OBO Foundry approach extended into other domains NIF Standard Neuroscience Information Framework ISF Ontologies Integrated Semantic Framework OGMS and Extensions Ontology for General Medical Science IDO Consortium Infectious Disease Ontology cROP Common Reference Ontologies for Plants 11 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/ 12 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 13 HIPAA Hospital #1 data Hospital #2 data Clinic #1 data Roswell data Non-public Basic science (e.g. pharma data) Data Warehouse Alzheimer’s Disease Staph Aureus Bacteremia Sleep Disorders Using OGMS as basis, create small ontologies for specific clinical domains Open Biomedical Ontologies Foundry Basic science data Public 14 HIPAA Non-public Hospital #1 data Hospital #2 data Clinic #1 data Roswell data Basic science (e.g. pharma data) Data Warehouse Clinical Neurology Cancer Pathology Semi-public etc. Extend this approach to the workings of the CTS institution itself Resource data Publications, patents, equipment, samples, expertise, grants, lab activities, clinical research activities, clinical trials Basic science data 15 HIPAA Non-public Hospital #1 data Hospital #2 data Clinic #1 data Roswell data Basic science (e.g. pharma data) Data Warehouse Clinical Trial Ontology Consent Ontology etc. Extend this approach to the workings of the CTS institution itself OBI : Ontology for Biomedical Investigations Semi-public OGMS Resource data Publications, patents, equipment, samples, expertise, grants, lab activities, clinical research activities, clinical trials Open Biomedical Ontologies Foundry 16