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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

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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:

http://tinyurl.com/YosemiteRoadmap20150709slides

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Outline

  • Mission and strategy
  • Semantic interoperability

– Standards – Translations

  • Roadmap for interoperability
  • Cost
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MISSION:

Semantic interoperability

  • f

all structured healthcare information

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MISSION:

Semantic interoperability

  • f

all structured healthcare information

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STRATEGY:

RDF as a universal information representation

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Universal information representation

  • Q: What does instance data X mean?
  • A: Determine its RDF information content

<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>

Instance data RDF

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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/

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Semantic interoperability:

The ability of computer systems to exchange data with unambiguous, shared meaning. – Wikipedia

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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

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Obviously we prefer

standards.

But . . . .

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Standardization takes time

2016

2036

2096

DUE COMING SOON! COMPREHENSIVE STANDARD

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Standards trilemma: Pick any two

  • Timely: Completed quickly
  • Good: High quality
  • Comprehensive: Handles all use cases
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Modernization takes time

  • Existing systems cannot be updated all at once
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Diverse use cases

  • Different use cases need different data,

granularity and representations

One standard does not fit all!

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Standards evolve

  • Version n+1 improves on version n
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Healthcare terminologies rate of change

Slide credit: Rafael Richards (VA)

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Translation is unavoidable!

  • Standardization takes time
  • Modernization takes time
  • Diverse use cases
  • Standards evolve
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A realistic strategy for semantic interoperability must address both

standards and translations.

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Interoperability achieved by standards vs. translations

Standards Translations Interop Standards Convergence

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How RDF Helps Standards

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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!

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How Standards Proliferate

http://xkcd.com/927/ Used by permission

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Each standard is an island

  • Each has its "sweet spot" of use
  • Lots of duplication
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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 . . .
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Bike shed effect

a/k/a Parkinson's Law of Triviality

Organizations spend disproportionate time

  • n 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

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Standards committees and the bike shed effect

  • Committees spend hours deciding on data

formats, syntax and naming

– Irrelevant to the computable information content

Syntax!

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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
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Needed: Collaborative Standards Hub

  • A 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

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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
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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

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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
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iCat: Web Protege tool for ICD-11

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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
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FIBO development process

  • Financial @@@ (FIBO) standards are

developed in RDF/OWL

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How RDF Helps Translation

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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

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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

Crowd-Sourced Translation Rules Hub Rules Source Target v2.5

2. Translate

  • 3. Drop

from RDF

  • 1. Lift

to RDF

Source Target v2.5

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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

Crowd-Sourced Translation Rules Hub Rules Source Target v2.5

2. Translate

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Translation strategies

  • 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!

Hub-and-Spoke Point-to-Point

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Which common data model?

  • 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

Hub-and-Spoke

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Where are these translation rules?

  • By manipulating RDF data, rules can be

mixed, matched and shared

2. Translate

  • 3. Drop

from RDF

  • 1. Lift

to RDF

Crowd-Sourced Translation Rules Hub Rules Source Target v2.5 Crowd-Sourced Translation Rules Hub Rules

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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)

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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?

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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

Crowd-Sourced Translation Rules Hub Rules Source Target v2.5

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Roadmap for Interoperability

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Roadmap

Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

  • 1. RDF as a Universal

Information Representation

Roadmap - 1

Use RDF as a common semantic foundation

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 2

For common healthcare information representations*, define an RDF mapping to/from each format, data model and vocabulary – "lift" and "drop".

  • 2. RDF

Mappings

*Both standard and proprietary

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 3

Define translation rules for instance data that is expressed in RDF representations

  • 3. Translations

between models & vocabularies

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 4

Create a hub for crowd-sourcing translation rules

  • 4. Crowd-Sourced

Translation Rules

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 5

Create RDF / OWL definitions of the data models and vocabularies defined by healthcare standards

  • 5. RDF/OWL

Standards Definitions

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 6

Create a collaborative standards hub for RDF/OWL standards definitions, to facilitate standards convergence

  • 6. Collaborative

Standards Convergence

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 7

Adopt policy incentives for healthcare providers to achieve semantic interoperability.

  • 7. Interoperability

Policies

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 7

(a) Adopt free and open interoperability standards. Why? Eliminate IP barriers to interoperability.

  • 7. Interoperability

Policies

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Roadmap - 7

(b) Adopt policy incentives for healthcare providers to achieve semantic interoperability. Why? A healthcare provider has no natural business incentive to make its data interoperable with competitors.

  • 7. Interoperability

Policies

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Roadmap

Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

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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 guesses . . . What are yours?

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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

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Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

Biggest payoff opportunities

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Questions?

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BACKUP SLIDES

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Related Activities

  • New HL7 group 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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http://YosemiteProject.org/ A Roadmap for Healthcare Information Interoperability

Semantic Interoperability

  • 4. Crowd-Sourced

Translation Rules

  • 6. Collaborative

Standards Convergence

  • 2. RDF

Mappings

  • 3. Translations

between models & vocabularies

  • 5. RDF/OWL

Standards Definitions

  • 7. Interoperability

Policies

  • 1. RDF as a Universal

Information Representation

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64 Standardize the Standards Translate When Necessary

http://YosemiteProject.org/ A Roadmap for Healthcare Information Interoperability

Semantic Interoperability

Crowd-sourced translation rules Collaborate standards convergence Lift to RDF Translations between models & vocabularies Standards in RDF Interoperability incentives

  • 1. RDF as a Universal

Information Representation 4 6 5 3 2 7

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Steps 2 and 5

<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>

XML Instance Data RDF Instance Data Lift/Drop Mapping Text Existing Standard Definition

+

RDF / OWL Standard Definition XML Schema Describes Text

+

RDF / OWL Ontology Describes 2 5 Corresponds to

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Roadmap

Semantic Interoperability

  • 1. RDF as a Universal

Information Representation