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The Yosemite Project for
Healthcare Information Interoperability
David Booth, HRG and Rancho BioSciences
Conor Dowling, Ca...
2
Outline
• Mission of the Yosemite Project
• Foundation: RDF
• Roadmap for interoperability:
– Standardize the Standards
...
3
Imagine a world
4
Imagine a world
in which all healthcare systems
speak the same language
with the same meanings
covering all healthcare.
5
Semantic interoperability:
The ability of computer systems
to exchange data
with unambiguous, shared meaning.
– Wikipedia
6
Healthcare today
Tower of Babel, Abel Grimmer (1570-1619)
7
Yosemite Project
MISSION:
Semantic interoperability
of
all structured healthcare information
8
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Ince...
9
RDF as a Universal
Information
Representation
10
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
11
What is RDF?
• "Resource Description Framework"
– But think "Reusable Data Framework"
• Language for representing infor...
12
ex:patient319 foaf:name "John Doe" .
ex:patient319 v:systolicBP ex:obs_001 .
ex:obs_001 v:value 120 .
ex:obs_001 v:unit...
13
RDF captures information – not syntax
• RDF is format independent
• There are multiple RDF syntaxes: Turtle, N-Triples,...
14
Different source formats, same RDF
OBX|1|CE|3727-0^BPsystolic,
sitting||120||mmHg|
<Observation
xmlns="http://hl7.org/f...
Why does this matter?
• Emphasis is on the meaning (where it should be)
• RDF acts as a universal information representati...
16
Why RDF?
• Endorsed by over 100 thought leaders in healthcare and technology as the best
available candidate for a univ...
17
Standardize the Standards
18
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
19
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
20
Standard Vocabularies in UMLS
AIR ALT AOD AOT BI CCC CCPSS CCS CDT CHV COSTAR CPM CPT CPTSP
CSP CST DDB DMDICD10 DMDUMD...
ONC recommended standards
● Patchwork of ~30 standards +
clarifications
● Different data formats, data models
and vocabula...
22
How Standards Proliferate
http://xkcd.com/927/
23
Each standard is an island
• Each has its "sweet spot" of use
• Lots of duplication
24
RDF and OWL enable semantic bridges
between standards
• Goal: a cohesive mesh of standards that act as a single
compreh...
Standardize the standards
● Use RDF & family as a common, computable definition
language
● Semantically link standards
● C...
26
Needed: Collaborative Standards Hub
• Cross between BioPortal, GitHub, WikiData, Web Protege, CIMI repository, HL7
mode...
27
Collaborative Standards Hub
• Repository of healthcare
information standards
• Supports standards
groups and implemente...
28
SNOMED-CT
FHIR
ICD-11
HL7 v2.5
LOINC
Collaborative Standards Hub
• Suggests related concepts
• Checks and notifies of
i...
29
Collaborative Standards Hub
• Can scrape or reference
definitions held elsewhere
• Provides metrics:
– Objective (e.g.,...
30
iCat: Web Protege tool for ICD-11
31
iCat development of ICD-11
In three years:
• 270 domain experts
around the world
• 45,000+ classes
• 260,000+ changes
•...
32
Similar Effort in Financial Industry: FIBO
• Standards in RDF
• Similar concept but narrower scope than Yosemite Projec...
33
RDF helps avoid the bike shed effect
• Each group can use its favorite data format, syntax and names
• RDF can uniforml...
34
Bike shed effect
a/k/a Parkinson's Law of Triviality
Organizations spend disproportionate time
on trivial issues. -- C....
35
Standards committees
and the bike shed effect
• Committees spend hours deciding on data formats, syntax
and naming
– Ir...
36
Crowdsource
Translations
37
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
38
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
39
Two ways to achieve interoperability
• Standards:
– Make everyone speak the same language
– I.e., same data models and ...
40
Obviously we prefer
standards.
But . . . .
41
Standardization takes time
2016
DUE
COMING SOON!
COMPREHENSIVE
STANDARD
2036
2096
42
Standards trilemma: Pick any two
• Timely: Completed quickly
• Good: High quality
• Comprehensive: Handles all use cases
43
Modernization takes time
• Existing systems cannot be updated all at once
44
Diverse use cases
• Different use cases need different data, granularity and
representations
One standard does not fit ...
45
Standards evolve
• Version n+1 improves on version n
46
Healthcare terminologies rate of change
Slide credit: Rafael Richards (VA)
47
Translation is unavoidable!
Translation allows:
• Newer systems to interoperate with older systems
• Different use case...
48
A realistic strategy for semantic interoperability
must address both
standards and translations.
49
Interoperability achieved
by standards vs. translations
Standards
Translations
Interop
Standards Convergence
50
How RDF helps translation
• RDF supports inference
– Can be used for translation
• RDF acts as a universal information
...
51
Translating patient data
• Steps 1 & 3 map between source/target syntax and RDF
• Step 2 translates instance data betwe...
52
How should this translation be done?
• Translation is hard!
• Many different models and vocabularies
• Currently done i...
2.
Translate
3. Drop
from
RDF
1. Lift
to
RDF
Source Target
v2.5
53
Where are these translation rules?
• By manipulating RD...
54
Needed: Crowd-Sourced Translation Rules
Hub
● Based on GitHub, WikiData, BioPortal, Web Protege or other
● Hosts transl...
55
Translation rules metadata
• Source and target language / class
• Rules language
– E.g. SPARQL/SPIN, N3, JenaRules, Jav...
56
Patient data privacy
• Download translation rules as needed – plug-and-play
• Run rules locally
– Patient data is not s...
57
Incentivize
58
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
59
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
Incentivize
● There is no natural business incentive for a
healthcare provider to make its data
interoperable with its com...
61
Interoperability Roadmap
Healthcare
Information
Interoperability
Standardize
the Standards
Crowdsource
Translations
Inc...
62
What will semantic interoperability cost?
Initial Ongoing
Standards $40-500M + $30-400M / year
Translations $30-400M + ...
63
What will semantic interoperability cost?
Initial Ongoing
Standards $40-500M + $30-400M / year
Translations $30-400M + ...
64
Opportunity cost
Interoperability
$700 Million
per year?
*Source: http://www.calgaryscientific.com/blog/bid/284224/Inte...
65
Questions?
Upcoming Webinars
● July 23, 2015 - Why RDF for Healthcare - David Booth, HRG
● Aug 6, 2015 - drugdocs: Using RDF to produ...
Weekly Yosemite Project
Teleconference
Fridays 1pm Eastern US
See http://YosemiteProject.org/
68
BACKUP SLIDES
69
Related Activities
• Joint HL7/W3C subgroup on "RDF for Semantic
Interoperability":
http://wiki.hl7.org/index.php?
titl...
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SmartData Webinar Slides: The Yosemite Project for Healthcare Information interoperability

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Healthcare data originates in a wide variety of data formats, data models and vocabularies, making information interoperability a major challenge. Although many standards exist, and each one strives for a level of interoperability within its scope, in the aggregate these standards form an uncoordinated patchwork that thwarts interoperability. Furthermore, even when standards are used, translation between data formats, data models and vocabularies is still needed, for a variety of reasons.

The Yosemite Project describes an ambitious roadmap for achieving semantic interoperability of all structured healthcare information. Based on RDF as the best available candidate for a universal information representation, this roadmap addresses both the need to 'standardize the standards' and the opportunity to crowdsource data translations that are still required for information interoperability.

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SmartData Webinar Slides: The Yosemite Project for Healthcare Information interoperability

  1. 1. The Yosemite Project for Healthcare Information Interoperability David Booth, HRG and Rancho BioSciences Conor Dowling, Caregraf Michel Dumontier, Stanford University Josh Mandel, Harvard University Claude Nanjo, Cognitive Medical Systems Rafael Richards, Veterans Affairs 9-Jul-2015 These slides: http://tinyurl.com/YosemiteRoadmap20150709slides http://YosemiteProject.org/
  2. 2. 2 Outline • Mission of the Yosemite Project • Foundation: RDF • Roadmap for interoperability: – Standardize the Standards – Crowdsource Translations – Incentivize
  3. 3. 3 Imagine a world
  4. 4. 4 Imagine a world in which all healthcare systems speak the same language with the same meanings covering all healthcare.
  5. 5. 5 Semantic interoperability: The ability of computer systems to exchange data with unambiguous, shared meaning. – Wikipedia
  6. 6. 6 Healthcare today Tower of Babel, Abel Grimmer (1570-1619)
  7. 7. 7 Yosemite Project MISSION: Semantic interoperability of all structured healthcare information
  8. 8. 8 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  9. 9. 9 RDF as a Universal Information Representation
  10. 10. 10 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  11. 11. 11 What is RDF? • "Resource Description Framework" – But think "Reusable Data Framework" • Language for representing information • International standard by W3C • Mature – 10+ years • Used in many domains, including biomedical and pharma
  12. 12. 12 ex:patient319 foaf:name "John Doe" . ex:patient319 v:systolicBP ex:obs_001 . ex:obs_001 v:value 120 . ex:obs_001 v:units v:mmHg . RDF graph Patient319 has name "John Doe". Patient319 has systolic blood pressure observation Obs_001. Obs_001 value was 120. Obs_001 units was mmHg. English assertions: RDF* assertions ("triples"): RDF graph: *Namespace definitions omitted
  13. 13. 13 RDF captures information – not syntax • RDF is format independent • There are multiple RDF syntaxes: Turtle, N-Triples, JSON- LD, RDF/XML, etc. • The same information can be written in different formats • Any data format can be mapped to RDF
  14. 14. 14 Different source formats, same RDF OBX|1|CE|3727-0^BPsystolic, sitting||120||mmHg| <Observation xmlns="http://hl7.org/fhir"> <system value="http://loinc.org"/> <code value="3727-0"/> <display value="BPsystolic, sitting"/> <value value="120"/> <units value="mmHg"/> </Observation> HL7 v2.x FHIR RDF graph Maps to Maps to
  15. 15. Why does this matter? • Emphasis is on the meaning (where it should be) • RDF acts as a universal information representation • Existing data formats can be used – Each one has an implicit RDF equivalent – No need for explicitly exchange RDF format
  16. 16. 16 Why RDF? • Endorsed by over 100 thought leaders in healthcare and technology as the best available candidate for a universal healthcare exchange language – See http://YosemiteManifesto.org/ "Captures information content, not syntax" "Multi-schema friendly" "Supports inference" "Good for model transformation" "Allows diverse data to be connected and harmonized" "Allows data models and vocabularies to evolve" http://dbooth.org/2014/why-rdf/
  17. 17. 17 Standardize the Standards
  18. 18. 18 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  19. 19. 19 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  20. 20. 20 Standard Vocabularies in UMLS AIR ALT AOD AOT BI CCC CCPSS CCS CDT CHV COSTAR CPM CPT CPTSP CSP CST DDB DMDICD10 DMDUMD DSM3R DSM4 DXP FMA HCDT HCPCS HCPT HL7V2.5 HL7V3.0 HLREL ICD10 ICD10AE ICD10AM ICD10AMAE ICD10CM ICD10DUT ICD10PCS ICD9CM ICF ICF-CY ICPC ICPC2EDUT ICPC2EENG ICPC2ICD10DUT ICPC2ICD10ENG ICPC2P ICPCBAQ ICPCDAN ICPCDUT ICPCFIN ICPCFRE ICPCGER ICPCHEB ICPCHUN ICPCITA ICPCNOR ICPCPOR ICPCSPA ICPCSWE JABL KCD5 LCH LNC_AD8 LNC_MDS30 MCM MEDLINEPLUS MSHCZE MSHDUT MSHFIN MSHFRE MSHGER MSHITA MSHJPN MSHLAV MSHNOR MSHPOL MSHPOR MSHRUS MSHSCR MSHSPA MSHSWE MTH MTHCH MTHHH MTHICD9 MTHICPC2EAE MTHICPC2ICD10AE MTHMST MTHMSTFRE MTHMSTITA NAN NCISEER NIC NOC OMS PCDS PDQ PNDS PPAC PSY QMR RAM RCD RCDAE RCDSA RCDSY SNM SNMI SOP SPN SRC TKMT ULT UMD USPMG UWDA WHO WHOFRE WHOGER WHOPOR WHOSPA Over 100!
  21. 21. ONC recommended standards ● Patchwork of ~30 standards + clarifications ● Different data formats, data models and vocabularies ● Defined in different ways - not in a uniform, computable form
  22. 22. 22 How Standards Proliferate http://xkcd.com/927/
  23. 23. 23 Each standard is an island • Each has its "sweet spot" of use • Lots of duplication
  24. 24. 24 RDF and OWL enable semantic bridges between standards • Goal: a cohesive mesh of standards that act as a single comprehensive standard
  25. 25. Standardize the standards ● Use RDF & family as a common, computable definition language ● Semantically link standards ● Converge on common definitions
  26. 26. 26 Needed: Collaborative Standards Hub • Cross between BioPortal, GitHub, WikiData, Web Protege, CIMI repository, HL7 model forge, UMLS Semantic Network and Metathesaurus – Next generation BioPortal? SNOMED-CT FHIR ICD-11 HL7 v2.5 LOINC
  27. 27. 27 Collaborative Standards Hub • Repository of healthcare information standards • Supports standards groups and implementers • Holds RDF/OWL definitions of data models, vocabularies and terms • Encourages: – Semantic linkage – Standards convergence SNOMED-CT FHIR ICD-11 HL7 v2.5 LOINC
  28. 28. 28 SNOMED-CT FHIR ICD-11 HL7 v2.5 LOINC Collaborative Standards Hub • Suggests related concepts • Checks and notifies of inconsistencies – within and across standards • Can be accessed by browser or RESTful API
  29. 29. 29 Collaborative Standards Hub • Can scrape or reference definitions held elsewhere • Provides metrics: – Objective (e.g., size, number of views, linkage degree) – Subjective (ratings) • Uses RDF and OWL under the hood – Users should not need to know RDF or OWL SNOMED-CT FHIR ICD-11 HL7 v2.5 LOINC
  30. 30. 30 iCat: Web Protege tool for ICD-11
  31. 31. 31 iCat development of ICD-11 In three years: • 270 domain experts around the world • 45,000+ classes • 260,000+ changes • 17,000 links to external terminologies
  32. 32. 32 Similar Effort in Financial Industry: FIBO • Standards in RDF • Similar concept but narrower scope than Yosemite Project • For financial reporting and policy enforcement • Using github and other tools to help collaboration
  33. 33. 33 RDF helps avoid the bike shed effect • Each group can use its favorite data format, syntax and names • RDF can uniformly capture the information content
  34. 34. 34 Bike shed effect a/k/a Parkinson's Law of Triviality Organizations spend disproportionate time on trivial issues. -- C.N. Parkinson, 1957 2. Bike Shed Cost: $1,000 Discussion: 45 minutes 1. Nuclear Plant Cost: $28,000,000 Discussion: 2.5 minutes
  35. 35. 35 Standards committees and the bike shed effect • Committees spend hours deciding on data formats, syntax and naming – Irrelevant to the computable information content Syntax!
  36. 36. 36 Crowdsource Translations
  37. 37. 37 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  38. 38. 38 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  39. 39. 39 Two ways to achieve interoperability • Standards: – Make everyone speak the same language – I.e., same data models and vocabularies • Translations: – Translate between languages – I.e., translate between data models and vocabularies
  40. 40. 40 Obviously we prefer standards. But . . . .
  41. 41. 41 Standardization takes time 2016 DUE COMING SOON! COMPREHENSIVE STANDARD 2036 2096
  42. 42. 42 Standards trilemma: Pick any two • Timely: Completed quickly • Good: High quality • Comprehensive: Handles all use cases
  43. 43. 43 Modernization takes time • Existing systems cannot be updated all at once
  44. 44. 44 Diverse use cases • Different use cases need different data, granularity and representations One standard does not fit all!
  45. 45. 45 Standards evolve • Version n+1 improves on version n
  46. 46. 46 Healthcare terminologies rate of change Slide credit: Rafael Richards (VA)
  47. 47. 47 Translation is unavoidable! Translation allows: • Newer systems to interoperate with older systems • Different use cases to use different data models • Standards to evolve
  48. 48. 48 A realistic strategy for semantic interoperability must address both standards and translations.
  49. 49. 49 Interoperability achieved by standards vs. translations Standards Translations Interop Standards Convergence
  50. 50. 50 How RDF helps translation • RDF supports inference – Can be used for translation • RDF acts as a universal information representation • Enables data model and vocabulary translations to be shared
  51. 51. 51 Translating patient data • Steps 1 & 3 map between source/target syntax and RDF • Step 2 translates instance data between data models and vocabularies (RDF-to-RDF) – A/k/a semantic alignment, model alignment 2. Translate 3. Drop from RDF 1. Lift to RDF Source Target v2.5
  52. 52. 52 How should this translation be done? • Translation is hard! • Many different models and vocabularies • Currently done in proprietary, black-box integration engines 2. Translate 3. Drop from RDF 1. Lift to RDF Source Target v2.5
  53. 53. 2. Translate 3. Drop from RDF 1. Lift to RDF Source Target v2.5 53 Where are these translation rules? • By manipulating RDF data, rules can be mixed, matched and shared Crowd-Sourced Translation Rules Hub Rules
  54. 54. 54 Needed: Crowd-Sourced Translation Rules Hub ● Based on GitHub, WikiData, BioPortal, Web Protege or other ● Hosts translation rules ● Agnostic about "rules" language: ● Any executable language that translates RDF-to-RDF (or between RDF and source/target syntax)
  55. 55. 55 Translation rules metadata • Source and target language / class • Rules language – E.g. SPARQL/SPIN, N3, JenaRules, Java, Shell, etc. • Dependencies • Test data / validation • License (free and open source) • Maintainer • Usage metrics/ratings – Objective: Number of downloads, Author, Date, etc. – Subjective: Who/how many like it, reviews, etc. – Digital signatures of endorsers?
  56. 56. 56 Patient data privacy • Download translation rules as needed – plug-and-play • Run rules locally – Patient data is not sent to the rules hub 2. Translate 3. Drop from RDF 1. Lift to RDF Source Target v2.5 Crowd-Sourced Translation Rules Hub Rules
  57. 57. 57 Incentivize
  58. 58. 58 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  59. 59. 59 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation http://YosemiteProject.org/
  60. 60. Incentivize ● There is no natural business incentive for a healthcare provider to make its data interoperable with its competitors ● Carrot / stick policies are needed ● Not the focus of the Yosemite Project, but essential for policy makers to address
  61. 61. 61 Interoperability Roadmap Healthcare Information Interoperability Standardize the Standards Crowdsource Translations Incentivize RDF as a Universal Information Representation
  62. 62. 62 What will semantic interoperability cost? Initial Ongoing Standards $40-500M + $30-400M / year Translations $30-400M + $20-300M / year Total $60-900M + $50-700M / year My SWAG . . . What is yours?
  63. 63. 63 What will semantic interoperability cost? Initial Ongoing Standards $40-500M + $30-400M / year Translations $30-400M + $20-300M / year Total $60-900M + $50-700M / year My SWAG . . . What is yours? ??
  64. 64. 64 Opportunity cost Interoperability $700 Million per year? *Source: http://www.calgaryscientific.com/blog/bid/284224/Interoperability-Could- Reduce-U-S-Healthcare-Costs-by-Thirty-Billion $30000 Million per year* Non-interoperability
  65. 65. 65 Questions?
  66. 66. Upcoming Webinars ● July 23, 2015 - Why RDF for Healthcare - David Booth, HRG ● Aug 6, 2015 - drugdocs: Using RDF to produce one coherent, definitive dataset about drugs, Conor Dowling, Caregraf ● Sept 3, 2015 - Linked VistA: VA Linked Data Approach to Semantic Interoperability, Rafael Richards, Veterans Affairs ● Sept 17, 2015 - Clinical data in FHIR RDF: Intro and Representation, Josh Mandel, Children's Hospital Informatics Program at Harvard-MIT, and David Booth, HRG ● Others to be announced http://YosemiteProject.org/
  67. 67. Weekly Yosemite Project Teleconference Fridays 1pm Eastern US See http://YosemiteProject.org/
  68. 68. 68 BACKUP SLIDES
  69. 69. 69 Related Activities • Joint HL7/W3C subgroup on "RDF for Semantic Interoperability": http://wiki.hl7.org/index.php? title=ITS_RDF_ConCall_Agenda • ONC's "Interoperability Roadmap" (draft): http://tinyurl.com/mgtwwr8

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