Hoot72a key step for Linked Health Data

www.hoot72.org

Apple Pie

E Pluribus Unum!

Linked Health Data

Patient

Doctor

Manager

Researcher

Insurance

IT

Where Are We?

•Health Data in “islands”, “bunkers”

• Admissions/Pharmacy/Lab ... Systems

•But the Systems do chat (internally)

• “Patient Arrival ...”, “Observation made ...”

•A stew of HL7 v2.x messages

•Billing data does leave the premises!

They speak v2

Source: Neotool, V3 vs V2

“HL7 version 2 is a major breakthrough and market success. More than 93% hospitals in US are using this standard” - Health Level Horizon (HLH) Project

One “tweet” ...MSH|^~\&|REGADT|MCM|IFENG||199112311501||ADT^A04^ADT_A01|000001|P|2.4|||EVN|A04|199901101500|199901101400|01||199901101410PID|||191919^^GENHOS^MR~371-66-9256^^^USSSA^SS|253763|MASSIE^JAMES^A||19560129|M|||171 ZOBERLEIN^^ISHPEMING^MI^49849^""^||(900)485-5344|(900)485-5344||S^^HL70002|C^^HL70006|10199925^^^GENHOS^AN|371-66-9256||NK1|1|MASSIE^ELLEN|SPOUSE^^HL70063|171 ZOBERLEIN^^ISHPEMING^MI^49849^""^|(900)485-5344|(900)545-1234~(900)545-1200|EC1^FIRST EMERGENCY CONTACT^HL70131NK1|2|MASSIE^MARYLOU|MOTHER^^HL70063|300 ZOBERLEIN^^ISHPEMING^MI^49849^""^|(900)485-5344|(900)545-1234~(900)545-1200|EC2^SECOND EMERGENCY CONTACT^HL70131NK1|3NK1|4|||123 INDUSTRY WAY^^ISHPEMING^MI^49849^""^||(900)545-1200|EM^EMPLOYER^HL70131|19940605||PROGRAMMER|||ACME SOFTWARE COMPANYPV1||O|O/R||||0148^ADDISON,JAMES|0148^ADDISON,JAMES||AMB|||||||0148^ADDISON,JAMES|S|1400|A|||||||||||||||||||GENHOS|||||199501101410|PV2||||||||199901101400|||||||||||||||||||||||||199901101400ROL||AD|CP^^HL70443|0148^ADDISON,JAMESOBX||NM|3141-9^BODY WEIGHT^LN||62|kg|||||F

James was admitted ... his wife is his emergency contact ... here’s his weight ...

My Nurse, My Kin“The HL7 we receive from the various sources systems can be wildly different (some are not even near to being to spec).  Additional we can receive the same data (think heart rate) from multiple systems, each which represent this differently.” -- System Implementer

NK1|1|MASSIE^ELLEN|MTH^Mother^HL70063||||EC1^FIRST EMERGENCY CONTACT^HL70131

NK1|1|Jones^Jane^Lee^^RN|VAB^Vaccine administered by (Name)^HL70063|

Next of kin is a mother ...

Or a nurse!

HL7 v2 only “suggests” - too messy for integration!

System-wide^

Disintegrated!•Full integration costly

•custom models, brittle

•only stray outside when forced

•(Today’s) Web veneers

•for men, not machines

•Another Option? ...

HL7 v3 - the Fix?•HL7 v3 - Object-based

• End 2005, a do over, ten years in the making

• Object Model (RIM), not V2-compatible

• Bonus: XML goodness

•Beyond Interface - Common Model

• Modern systems to be “RIM-Inside”

• Remake all systems

But ...

• Government Mandate (UK), some green field

• Just another opportunity to gateway

• Just polite talk? Are we stuck?

“Frozen interface syndrome: existing HL7 message interfaces are pretty much stuck at 2.2. Meaning that application vendors don't like to change for change's sake -- there needs to be a business motivation.”

-- Wes Rishel, Gartner Group

Back Inside the Stew

MSH|^~\&||GA0000||VAERS PROCESSOR|20010331605||ORU^R01|20010422GA03|T|2.3.1|||AL|PID|||1234^^^^SR~1234-12^^^^LR~00725^^^^MR||Doe^John^Fitzgerald^JR^^^L||20001007|M||2106-3^White^HL70005|123 Peachtree St^APT 3B^Atlanta^GA^30210^^M^^GA067||(678) 555-1212^^PRN|ORC|CN|||||||||||1234567^Welby^Marcus^J^Jr^Dr.^MD^L|||||||||Peachtree Clinic|101 Main Street^^Atlanta^GA^38765^^O^^GA121|(404) 554-9097^^WPN|101 Main Street^^Atlanta^GA^38765^^O^^GA121|OBR|1|||^CDC VAERS-1 (FDA) Report|||20010316|OBX|1|CE|30955-9&30956-7^Vaccine type^LN|1|08^HepB-Adolescent/pediatric^CVX|OBX|2|CE|30955-9&30957-5^Manufacturer^LN|1|MSD^Merck^MVX|OBX|3|ST|30955-9&30959-1^Lot number^LN|1|MRK12345|OBX|4|CE|30955-9&30958-3^Route^LN|1|IM^Intramuscular^HL70162|OBX|5|CE|30955-9&31034-2^Site^LN|1|LA^Left arm^ HL70163|OBX|6|NM|30955-9&30960-9^Number of previous doses^LN|1|01I

•Stuff and Codes, Codes, CODES!

•Messages (v2 or v3) just “trucks”

•If Codes a mess then ...

State of the Codes

•For substances, procedures, diseases ...

• Local, National, International; Care vs Billing vs ...

• SNOMED CT, MeSH, ICPC, ICD-9-CM, DRG, MDC, LOINC, CPT-4, HCPCS Level II, ICD-10, HL7 Vocabulary Domains ...

•Too many, unwieldy, overlapping ...

•Extend, (re)structure, link

“In” SchemesScope Size Grain C/E*

SNOMED All 350K Varies C

LOINC Labs 50K? High C

NDC Drugs 11 Digits High E

ICD9-CM Diseases 10K? Low*** E

UMLS All** Combined Varies Varies* Composed or

Enumerated** Assumes diversity. UMLS is 143 others: “not an attempt to build a single standard biomedical vocabulary.” RxNORM is its drugs.

*** “Other” is a catch-all, mandated for medicare billing

Focus: Coverage• Problem List to SNOMED: “SNOMED CT ...

can exactly represent a large portion (92.3%) of the terms” -- Mayo Clinic

• Local Lab Codes to LOINC: “Almost 19% of LOINC codes are ‘other’” -- CDC

• LOINC to SNOMED: “Automatic mapping of laboratory procedures from LOINC to SNOMED CT remains incomplete and unsatisfactory” -- Mapping Issues, Olivier Bodenreider, MD, PhD

Elephant: Equivalence

• Finding vs Observable

• [serum_potassium_elevated_code] vs [Code: serum_potassium_code Value: elevated]

• Many and one• “head injury” and “no intracranial bleed” vs “head injury without intracranial

bleed”

• Little/No Lexical match

• “colon cancer” vs “malignant neoplasm” plus “primary site: colon”

• Beyond Equivalence - kind-of

• BrCA Breast Cancer, Cystic Fibrosis ... are Diseases-linked-to-Genes

there may be several different ways to express the same concept. Human users may be able to recognise that these are essentially the same, but the rules for doing so must be made explicit to be usable by computer. -- Why is Terminology hard?, Alan Rector

Where’s the Ontology?• Ontology: “an implementable model of

the entities that need to be understood in common in order for some group of software systems and their users to function and communicate at the level required for a set of tasks” -- Alan Rector

• Code schemes slight/none: “deficiencies in the knowledge representation languages used”

• Enter w3c’s OWL == Web Ontology Language

• Focus on meaning referenced by codes

Joining their fellows

Joining the “Semantic Web”

•Web of documents to Web of data

•Reuse: HTTP, URIs

•Add: Query (SPARQL), Represent (RDF), Meaning (OWL)

•Silo’ed to Meaningful Linked Data

W3c HCLS - Power of linkage

•Gap: Trial Criteria, Patients

• Patients taking “Weight Loss Drugs”

• Patient NDC codes: DESOXYN TABLETS (00074337701) ...

•Linked by Ontologies

•"may_treat" “Obese” to RxNORM

•RxNORM links in NDC codes

•Trial meets Patients in two steps

What about the Patient?

Concepts linking

OR|20010331605||ORU^R01|20010422GA03|T|2.3.1|||AL|725^^^^MR||Doe^John^Fitzgerald^JR^^^L||20001007|M||2106-3^White^HL70005|123 Peachtree St^APT 3B^Atlanta^GA^30210^^M^^GA067||(678) 555-1212^^PRN||||||||||Peachtree Clinic|101 Main Street^^Atlanta^GA^38765^^O^^GA121|(404) 554-9097^^WPN|101 Main Street^^Atlanta^GA^38765^^O^^GA121|

Shouldn’t patients join in?

E Pluribus Unum ...

Codes

Patients

Linked Health Data

Patient

Doctor

Insurance

Researcher

“Link-Maker”

Manager

Avoid Temptation!

•V2’s Yuck Factor - “Legacy”, “Messy”

•Formalism likes its fellows

•wait until V2 disappears?

•mate its successors to this Web

•Hold your noses. Go where the data is!

Enter Hoot72

• Hoot (from OWL), 72 (HL7 v2)

• Mapping: message to graph assertions

• pre-defined ontology small

• Automatic: drive off message definitions

• Presumes little so generally applicable

• Creative Commons License

Observation (OBX)PID|||1234^^^^SR~1234-12^^^^LR~00725^^^^MR||Doe^John^Fitzgerald^JR^^^L|...OBX|4|CE|30949-2^Vaccination adverse event outcome^LN|1|H^required hospitalization^NIP005|

LN 30949-2

CodingSystem Code

H NIP005

CodingSystemCode

observation observationValue

Doe

John Fitzgerald

personName

familyName

givenName

middleName

contextPatient

type

Identifiers and Time not shown

A first step: Expose

•A Site graph == Here’s your Hospital/Clinic

•Linking to do (to code ontologies ...)

•“Predicates” to interpret

•Reports/views to generate

•Inaccuracies to find

From Many, One ...

•Health Care unlinked today

•Linked Health Care = site graphs + interacting ontologies, linked

•Hoot72, a key step. www.hoot72.org.