The Yosemite Project A Roadmap for Healthcare Information Interoperability
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1 The Yosemite Project A Roadmap for Healthcare Information Interoperability David Booth, Hawaii Resource Group Conor Dowling, Caregraf Michel Dumontier, Stanford University Josh Mandel, Harvard University Claude Nanjo, Cognitive Medical Systems Rafael Richards, Veterans Affairs Semantic Technology and Business Conference 21-Aug-2014 SEE LATEST VERSION:
2 Outline Mission and strategy Semantic interoperability Standards Translations Roadmap for interoperability Cost 2
3 MISSION: Semantic interoperability of all structured healthcare information 3
4 MISSION: Semantic interoperability of all structured healthcare information 4
5 STRATEGY: RDF as a universal information representation 5
6 Universal information representation Q: What does instance data X mean? A: Determine its RDF information content Instance data RDF <Observation xmlns=" <system value=" <code value="3727 0"/> <display value="bpsystolic, sitting"/> <value value="120"/> <units value="mmhg"/> </Observation> 6
7 Why RDF? "Captures information content, not syntax" "Allows data models and vocabularies to evolve" "Multi-schema friendly" "Good for model transformation" "Allows diverse data to be connected and harmonized" "Supports inference" Endorsed by over 100 thought leaders in healthcare and technology as the best available candidate for a universal healthcare exchange language See 7
8 Semantic interoperability: The ability of computer systems to exchange data with unambiguous, shared meaning. Wikipedia 8
9 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 9
10 Obviously we prefer standards. But
11 Standardization takes time COMING SOON! COMPREHENSIVE STANDARD DUE
12 Standards trilemma: Pick any two Timely: Completed quickly Good: High quality Comprehensive: Handles all use cases 12
13 Modernization takes time Existing systems cannot be updated all at once 13
14 Diverse use cases Different use cases need different data, granularity and representations One standard does not fit all! 14
15 Standards evolve Version n+1 improves on version n 15
16 Healthcare terminologies rate of change Slide credit: Rafael Richards (VA) 16
17 Translation is unavoidable! Standardization takes time Modernization takes time Diverse use cases Standards evolve 17
18 A realistic strategy for semantic interoperability must address both standards and translations. 18
19 Interoperability achieved by standards vs. translations Translations Interop Standards Standards Convergence 19
20 How RDF Helps Standards 20
21 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
22 How Standards Proliferate Used by permission 22
23 Each standard is an island Each has its "sweet spot" of use Lots of duplication 23
24 RDF and OWL enable semantic bridges between standards Goal: a cohesive mesh of standards that act as a single comprehensive standard RDF also helps avoid the bike shed effect... 24
25 Bike shed effect a/k/a Parkinson's Law of Triviality Organizations spend disproportionate time on trivial issues. -- C.N. Parkinson, Nuclear Plant 2. Bike Shed Cost: $28,000,000 Discussion: 2.5 minutes Cost: $1,000 Discussion: 45 minutes 25
26 Standards committees and the bike shed effect Syntax! Committees spend hours deciding on data formats, syntax and naming Irrelevant to the computable information content 26
27 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 27
28 Needed: Collaborative Standards Hub SNOMED-CT LOINC FHIR HL7 v2.5 ICD-11 A cross between BioPortal, GitHub, WikiData, Web Protege, CIMI repository, HL7 model forge, UMLS Semantic Network and Metathesaurus Next generation BioPortal? 28
29 Collaborative Standards Hub Repository of healthcare information standards Supports standards groups and implementers Holds RDF/OWL definitions of data models, vocabularies and terms Encourages: SNOMED-CT FHIR LOINC HL7 v2.5 ICD-11 Semantic linkage Standards convergence 29
30 Collaborative Standards Hub SNOMED-CT Suggests related concepts Checks and notifies of inconsistencies within and across standards Can be accessed by browser or RESTful API LOINC FHIR HL7 v2.5 ICD-11 30
31 Collaborative Standards Hub Can scrape or reference definitions held elsewhere Provides metrics: SNOMED-CT LOINC FHIR HL7 v2.5 ICD-11 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 31
32 icat: Web Protege tool for ICD-11 32
33 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 33
34 FIBO development process Financial (FIBO) standards are developed in RDF/OWL 34
35 How RDF Helps Translation 35
36 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 36
37 Translating patient data 2. Translate Crowd-Sourced Translation Rules Hub Rules Source v2.5 Target 1. Lift to RDF 3. Drop from RDF 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 37
38 How should this translation be done? 2. Translate Crowd-Sourced Translation Rules Hub Rules Source v2.5 Target 1. Lift to RDF 3. Drop from RDF Translation is hard! Many different models and vocabularies Currently done in proprietary, black-box integration engines 38
39 Translation strategies Point-to-Point Hub-and-Spoke Point-to-point is easier/faster for each translation Hub-and-spoke requires fewer translations: O(n) instead of O(n^2) Hub-and-spoke requires a common data model Both strategies can be used! 39
40 Which common data model? Hub-and-Spoke Standardization may choose a common data model: Moving target Must be able to represent (but not require) the finest granularity needed by any use case Different use cases may use other data models, mapped to/from the common data model Speeds standardization of common data model Avoids bike shed effect 40
41 Where are these translation rules? 2. Translate Crowd-Sourced Translation Rules Hub Rules Source v2.5 Target 1. Lift to RDF 3. Drop from RDF By manipulating RDF data, rules can be mixed, matched and shared 41
42 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) 42
43 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? 43
44 Patient data privacy 2. Translate Crowd-Sourced Translation Rules Hub Rules Source v2.5 Target 1. Lift to RDF 3. Drop from RDF Download translation rules as needed plug-and-play Run rules locally Patient data is not sent to the rules hub 44
45 Roadmap for Interoperability 45
46 Roadmap Semantic Interoperability 6. Collaborative Standards Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 46
47 Roadmap - 1 Semantic Interoperability Use 6. Collaborative Standards RDFConvergence as a common 5. RDF/OWL Standards Definitions foundation 2. RDF Mappings 1. RDF as a Universal Information Representation 7. Interoperability Policies semantic 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 47
48 Roadmap - 2 Semantic information Interoperability For common healthcare representations*, define an RDF 6. Collaborative mappingstandards to/from each format,7.data Interoperability Convergence model and vocabulary "lift" and Policies "drop". 5. RDF/OWL Standards Definitions *Both standard 2. RDF Mappings 1. RDF as a Universal Information Representation 4. Crowd-Sourced Translation and proprietary Rules 3. Translations between models & vocabularies 48
49 Roadmap - 3 Semantic Interoperability Define translation rules for 6. Collaborative instance data thatstandards is expressed in Convergence RDF representations 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 49
50 Roadmap - 4 Create a hub for crowd-sourcing 6. Collaborative translation rules Standards Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation Semantic Interoperability 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 50
51 Roadmap - 5 Semantic Interoperability definitions of Create RDF / OWL the data models and vocabularies 6. Collaborative Standards defined by healthcare standards 7. Interoperability Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 51
52 Roadmap - 6 Semantic Interoperability 6. Collaborative Standards Convergence 5. RDF/OWL Standards collaborative Definitions 7. Interoperability Policies 4. Crowd-Sourced Translation Rules Create a standards hub for RDF/OWL standards 2. RDF definitions, to facilitate standards Mappings convergence 3. Translations 1. RDF as a Universal Information Representation between models & vocabularies 52
53 Roadmap - 7 Adopt policy incentives for 6. Collaborative healthcare providers to achieve semantic interoperability.standards Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation Semantic Interoperability 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 53
54 Roadmap - 7 (a) Adopt free and open 6. Collaborative interoperability standards. Standards Convergence 5. RDF/OWL Standards Why? Definitions Eliminate IP barriers to 2.interoperability. RDF Mappings 1. RDF as a Universal Information Representation Semantic Interoperability 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 54
55 Roadmap - 7 (b) Adopt policy incentives for 6. Collaborative healthcare providers to achieve semantic interoperability.standards Convergence 5. RDF/OWL Why? Standards Definitions healthcare provider Semantic Interoperability 7. Interoperability Policies 4. Crowd-Sourced Translation Rules A has no natural business incentive to 2. RDF make its data interoperable with Mappings 3. Translations competitors. between models 1. RDF as a Universal Information Representation & vocabularies 55
56 Roadmap Semantic Interoperability 6. Collaborative Standards Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 56
57 What will semantic interoperability cost? My guesses... Initial Ongoing Standards $40-500M + $30-400M / year Translations $30-400M + $20-300M / year Total $60-900M + $50-700M / year What are yours? 57
58 Opportunity cost Non-interoperability $30000 Million per year* Interoperability *Source: $700 Million per year? 58
59 Biggest payoff opportunities Semantic Interoperability 6. Collaborative Standards Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 59
60 Questions? 60
61 BACKUP SLIDES 61
62 Related Activities New HL7 group on "RDF for Semantic Interoperability": ONC's "Interoperability Roadmap" (draft): 62
63 A Roadmap for Healthcare Information Interoperability Semantic Interoperability 6. Collaborative Standards Convergence 5. RDF/OWL Standards Definitions 2. RDF Mappings 1. RDF as a Universal Information Representation 7. Interoperability Policies 4. Crowd-Sourced Translation Rules 3. Translations between models & vocabularies 63
64 A Roadmap for Healthcare Information Interoperability Semantic Interoperability Collaborate standards convergence 7 ss ary 4 ds r da n ta S the 1. RDF as a Universal Information Representation Wh en sla te Tra n i ze d 2 dar an St Ne ce Standards in RDF 3 Lift to RDF Interoperability incentives 5 6 Crowd-sourced translation rules Translations between models & vocabularies 64
65 Steps 2 and 5 Existing Standard Definition XML Schema + Text RDF / OWL 5 Standard Definition Corresponds to + Text Describes Describes XML Instance Data <Observation xmlns=" <system value=" <code value="3727 0"/> <display value="bpsystolic, sitting"/> <value value="120"/> <units value="mmhg"/> </Observation> RDF / OWL Ontology RDF Instance Data 2 Lift/Drop Mapping 65
66 Roadmap Semantic Interoperability 1. RDF as a Universal Information Representation 66
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