The Future of Health Information Barry Smith Ontology Research Group Center of Excellence in Bioinformatics and Life Sciences University at Buffalo ontology.buffalo.edu/smith.

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Presentation transcript:

The Future of Health Information Barry Smith Ontology Research Group Center of Excellence in Bioinformatics and Life Sciences University at Buffalo ontology.buffalo.edu/smith

2 Collaborations National Center for Biomedical Ontology ( WHO Collaborating Center for Terminology Cleveland Clinic Semantic Database SNOMED CT – Disease Ontology German national Electronic Health Record initiative [Health Version 11]

3 Overview of this talk The role of ontology The role of HL7 The future of health information

4 The role of ontology The role of HL7 The future of health information Overview of this talk

5

we need to know where in the body, where in the cell we need to know what kind of disease process = we need ontologies we need semantic annotation of data

7

8

9 Ontologies are systems of terms for annotating data They are controlled vocabularies designating the types of entities in reality Data designate the instances of these types

10 cellular locations molecular functions biological processes used to annotate the entities represented in the major biochemical databases thereby creating integration across these databases The Gene Ontology: A set of standardized textual descriptions of

11 what cellular component? what molecular function? what biological process?

12 The process of data annotation yields a slowly growing computer-interpretable map of biological reality within which major databases are automatically integrated in semantically searchable form

13 But now need to extend the methodology to other domains, including clinical medicine  need disease, symptom (phenotype) ontologies

14 The Problem need for prospective standards to ensure mutual consistency and high quality of clinical counterparts of GO need to ensure consistency of the new clinical ontologies with the basic biomedical sciences if we do not start now, the problem will only get worse

15 The Solution establish common rules governing best practices for creating ontologies and for using these in annotations apply these rules to create a complete suite of orthogonal interoperable biomedical reference ontologies

16 a shared portal for (so far) 58 ontologies (low regimentation)  NCBO BioPortalhttp://obo.sourceforge.net First step (2003)

17

Second step (2004): reform efforts initiated, e.g. linking GO to other OBO ontologies to ensure interoperability id: CL: name: osteoblast def: "A bone-forming cell which secretes an extracellular matrix. Hydroxyapatite crystals are then deposited into the matrix to form bone." is_a: CL: relationship: develops_from CL: relationship: develops_from CL: GO Cell type New Definition + = Osteoblast differentiation: Processes whereby an osteoprogenitor cell or a cranial neural crest cell acquires the specialized features of an osteoblast, a bone-forming cell which secretes extracellular matrix.

19 The OBO Foundry Third step (2006)

20 a family of interoperable gold standard biomedical reference ontologies to serve the annotation of  scientific literature  model organism databases  clinical data  experimental results The OBO Foundry

21 Compare the UMLS Metathesaurus a system of post hoc mappings between independent source vocabularies built by trained experts massively useful for information retrieval and information integration creates out of literature a semantically searchable space

22 for UMLS local usage respected regimentation frowned upon cross-framework consistency not important no concern to establish consistency with basic science different grades of formal rigor, different degrees of completeness, different update policies no path towards improvement no path towards support for logical reasoning

23 The OBO Foundry is a prospective standard designed to guarantee interoperability of ontologies from the very start (contrast to: post hoc mapping) established March initial candidate OBO ontologies – focused primarily on basic science domains several being constructed ab initio now 16 ontologies

OntologyScopeURLCustodians Cell Ontology (CL) cell types from prokaryotes to mammals obo.sourceforge.net/cgi- bin/detail.cgi?cell Jonathan Bard, Michael Ashburner, Oliver Hofman Chemical Entities of Bio- logical Interest (ChEBI) molecular entitiesebi.ac.uk/chebi Paula Dematos, Rafael Alcantara Common Anatomy Refer- ence Ontology (CARO) anatomical structures in human and model organisms (under development) Melissa Haendel, Terry Hayamizu, Cornelius Rosse, David Sutherland, Foundational Model of Anatomy (FMA) structure of the human body fma.biostr.washington. edu JLV Mejino Jr., Cornelius Rosse Functional Genomics Investigation Ontology (FuGO) design, protocol, data instrumentation, and analysis fugo.sf.netFuGO Working Group Gene Ontology (GO) cellular components, molecular functions, biological processes Gene Ontology Consortium Phenotypic Quality Ontology (PaTO) qualities of anatomical structures obo.sourceforge.net/cgi -bin/ detail.cgi? attribute_and_value Michael Ashburner, Suzanna Lewis, Georgios Gkoutos Protein Ontology (PrO) protein types and modifications (under development)Protein Ontology Consortium Relation Ontology (RO) relationsobo.sf.net/relationshipBarry Smith, Chris Mungall RNA Ontology (RnaO) three-dimensional RNA structures (under development)RNA Ontology Consortium Sequence Ontology (SO) properties and features of nucleic sequences song.sf.netKaren Eilbeck

RELATION TO TIME GRANULARITY CONTINUANTOCCURRENT INDEPENDENTDEPENDENT ORGAN AND ORGANISM Organism (NCBI Taxonomy) Anatomical Entity (FMA, CARO) Organ Function (FMP, CPRO) Phenotypic Quality (PaTO) Biological Process (GO) CELL AND CELLULAR COMPONENT Cell (CL) Cellular Component (FMA, GO) Cellular Function (GO) MOLECULE Molecule (ChEBI, SO, RnaO, PrO) Molecular Function (GO) Molecular Process (GO) Building out from the original GO

26 OBO low-regimentation ontology portal OBO Foundry high-regimentation collaborative initiative to create a gold standard suite of interoperable ontologies The vision

27  Common Anatomy Reference Ontology  Disease Ontology (DO) [SNOMED CT]  Biomedical Image Ontology (BIO)  Environment Ontology (EnvO)  Biobank Ontology (BrO)  Clinical Trial Ontology (CTO) [with WHO Global Trial Bank, Immune Tolerance Network, ACGT Advancing Genomics Clinical Trials in Cancer EU IP] Ontologies under construction

28 Clinical Trial Ontology part of a larger project called the Ontology for Biomedical Investigations (OBI)

29 controlled vocabulary for biomedical investigations including  protocols  instrumentation  material  data  types of analysis and statistical tools applied to the data OBI

30 Clinical Trial Ontology To serve merger of data schemas To serve flexibility of collaborative clinical trial research To serve design and management of clinical trials To serve data access and reuse – send me all trials which...

31 Ontology vs. Database Schema Separate development of data schemas and ‘information models’ (HL7) and terminologies such as SNOMED CT the two do not work together

32 Ontology vs. Database Schema diabetes => disease diabetes => string temperature => quality temperature => integer

33 CTO

34 CTO Continuant

35 CTO Occurrent

36 Clinical Trial Ontology Working Group Workshop on May 16-17, 2007

37 The role of ontology The role of HL7 The future of health information

38 HL7 V3 “the data standard for biomedical informatics ” HL7TheDataStandardForBiomedicalInformatics.ppt

39 HL7 V2 a workable messaging standard faced the problem of local dialects seeks to solve this problem by having all HL7 artifacts conform to a single ‘Reference Information Model’ (the RIM) HL7 V3

40 After 10 years? And many attempts? And gigantic investments of energy and funding? is there a single, successful RIM-implementation?

There are clear examples of failure of billion-dollar implementations resting on the RIM and of programmers involved in such failures who are tearing out their hair, and blaming HL7

42 Is it justified, in these circumstances, to promote HL7 V3 as an ISO Standard in the domain of patient care?

43 One indispensable foundation for a successful standard a correct and uniform interpretation of its basic terms Act Participation Entity Role ActRelationship RoleLink

44 Sometimes ‘Act’ means information about an act Sometimes ‘Act’ means real-world action Sometimes ‘Act’ means a mixture of the above Sometimes in the very same sentence Demonstrably, the HL7 community does not understand its own basic terms

45 Consequences of unclarity here Different user groups have interpreted the same classes in different ways Different message specifications used different interpretations This recreates interoperability problems Can we be sure that these problems will not lead to incidents relevant to patient safety?

46 Even with clarity – and clear documentation – the RIM would still be in bad shape

47 Where are diseases Acts ? Things, Persons, Organizations ? Participations ? Roles ? ActRelationships ? RoleLinks ?

48 The HL7 Clinical Genomic Standard defines an allele as the observation of an allele defines a phenotype as the observation of an observation

49 The $ 35 bn. NHS Program “Connecting for Health” has applied the RIM rigorously, using all the normative elements, and it discovered that it needed to create dialects of its own to make the V3-based system work for its purposes (it still does not work)

50 The RIM has no coherent answer Basic categories cannot be agreed upon even for common phenomena like snakebites. HL7 V3 dialects are formed – and the RIM does not do its job.

51 The moral of this story Don’t claim to be “the data standard for biomedical informatics ” until you have a system that works HL7TheDataStandardForBiomedicalInformatics.ppt

52 The role of ontology The role of HL7 The future of health information

53 A New Paradigm for Health Information How achieve semantic interoperability amongst healthcare applications? Through referent tracking

54 The myth of ‘unambiguous’ understanding through biomedical terminologies /07/ closed fracture of shaft of femur /07/ Fracture, closed, spiral /07/ closed fracture of shaft of femur /07/ Accident in public building (supermarket) /07/ Essential hypertension /12/ benign polyp of biliary tract /03/ closed fracture of shaft of femur /03/ Accident in public building (supermarket) /04/ Other lesion on other specified region /05/ Essential hypertension 29822/08/ Closed fracture of radial head 29822/08/ Accident in public building (supermarket) /04/ closed fracture of shaft of femur /04/ Essential hypertension PtIDDateObsCodeNarrative /12/ malignant polyp of biliary tract * * * * cause, not disorder How many disorders have patients 5572, 2309 and 298 each had thus far in their lifetime ? How many numerically different disorders are listed here ? How many different types of disorders are listed here ?

55 Does seeing the labels help ? /07/ closed fracture of shaft of femur /07/ Fracture, closed, spiral /07/ closed fracture of shaft of femur /07/ Accident in public building (supermarket) /07/ Essential hypertension /12/ benign polyp of biliary tract /03/ closed fracture of shaft of femur /03/ Accident in public building (supermarket) /04/ Other lesion on other specified region /05/ Essential hypertension 29822/08/ Closed fracture of radial head 29822/08/ Accident in public building (supermarket) /04/ closed fracture of shaft of femur /04/ Essential hypertension PtIDDateObsCodeNarrative /12/ malignant polyp of biliary tract Same patient, same hypertension code: Same (numerically identical) hypertension ? Different patients, same fracture codes: Same (numerically identical) fracture ? Same patient, different dates, same fracture codes: same (numerically identical) fracture ? Same patient, same date, 2 different fracture codes: same (numerically identical) fracture ? Same patient, different dates, Different codes. Same (numerically identical) polyp ? Different patients. Same supermarket? Maybe the same freezer section ? Or different supermarkets, but always in the freezer sections ?

56 We have unique IDs for patients for healthcare deliverers for images for invoices

57 Let’s introduce unique IDs for everything that is mentioned in the record: –lesions –fractures –presentings –surgical procedures IUI = instance unique identifier

58 Better public health statistics /07/ closed fracture of shaft of femur /07/ Fracture, closed, spiral /07/ closed fracture of shaft of femur /07/ Accident in public building (supermarket) /07/ Essential hypertension /12/ benign polyp of biliary tract /03/ closed fracture of shaft of femur /03/ Accident in public building (supermarket) /04/ Other lesion on other specified region /05/ Essential hypertension 29822/08/ Closed fracture of radial head 29822/08/ Accident in public building (supermarket) /04/ closed fracture of shaft of femur /04/ Essential hypertension PtIDDateObsCodeNarrative /12/ malignant polyp of biliary tract IUI-001 IUI-003 IUI-004 IUI-005 IUI-007 IUI-002 IUI-012

59 ‘John Doe’s ‘John Smith’s liver tumor was treated with RPCI’s irradiation device’ ‘John Doe’s liver tumor was treated with RPCI’s irradiation device’ Better reasoning over health information #1 #3 #2 #4 #5 #6 treating person liver tumor clinic device instance-of at t 1 #10 #30 #20 #40 #5 #6 inst-of at t 2 inst-of at t 2 inst-of at t 2 inst-of at t 2 inst-of at t 2

60 Application principles #IUI-1 ‘affects’ #IUI-2 #IUI-3 ‘affects’ #IUI-2 #IUI-1 ‘causes’ #IUI-3 Referent Tracking Database EHR CAG repeat Juvenile HD person disorder continuant Ontology

61 Goal: A New Form of Evidence Based Medicine Now: –Decisions based on the outcomes of (reproducible) results of well-designed studies Guidelines and protocols –Evidence is hard to get, takes time to accumulate. Future: –Each discovered fact or expressed belief should instantly become available as contributing to the total body evidence, wherever its description is generated. –Data ‘eternally’ reusable independent of the purpose for which they have been generated.