Clinical Observations Interoperability (COI):How can Semantic Web Technologies Help?

Vipul Kashyapvipul.kashyap@cigna.com

http://esw.w3.org/topic/HCLS/ClinicalObservationsInteroperability

CSHALS 2008February 25, 2009Cambridge, MA

Acknowledgments: Helen Chen, Eric P and Holger Stenzhorn for COI Demo!Parsa Mirhaji for providing the real world clinical data!

Outline

• W3C Task Force on Clinical Observations Interoperability

• Healthcare and Life Sciences (HCLS): A Taxonomy

• HCLS Ecosystem: Current and Goal State

• Use Cases and Functional Requirements

• Use Case Demo Step Through

• Advantages of Semantic Web Technologies

• Next Steps

W3C Task Force on Clinical Observations Interoperability

• Goals and Objectives— Establish a collaboration between Providers, Pharma and other HCLS

stakeholders for re-use of EMR data in Clinical Research

— Establish the key stakeholders and respective value proposition

— Create consensus on a common use case, needs statements and functional requirements

— Develop Proofs of Concept by implementing key use cases

• Participants— Healthcare Providers

• Partners, Cleveland Clinic, Intermountain Healthcare, Mayo Clinic, VA/Regenstrief

— Pharmaceutical Companies• Eli Lilly, Astra Zeneca, Novartis, Pfizer, Bristol Myers Squibb

— Consortia• W3C, CDISC, HL7

What is Translational Medicine (TM)?

Research Practice

Clinical

Biological

Biomedical Research

ClinicalPractice

ClinicalResearch

PersonalizedMedicine

TranslationalResearch

Outcomes and UtilizationResearch

Risk and Cost Assessment

HCLS Ecosystem: Current State

PharmaceuticalCompanies

Clinical ResearchOrganizations (CROs)

FDANational InstitutesOf Health

Hospitals

Universities,Academic MedicalCenters (AMCs)

Characterized by silos with uncoordinated supply chains leading to inefficiencies in the system

Center forDiseaseControl

Hospitals Doctors

Payors

Patients

Patients,Public

Patients

Patients

Biomedical ResearchClinical Practice

Clinical Trials/Research Clinical Practice

Some interesting developments …

• Payors are performing analyses to enable— Employers to better identify health issues and optimize offerings

— Employees/members to make better medical decisions

— For cost/utilization optimization and claim adjudication.

• Providers are performing clinical studies and reviews:— To evaluate the quality and consistency of clinical care

— To perform clinical research and evaluate clinical protocols

• Pharmaceuticals are performing:— Clinical Trials

— Evaluating secondary uses of healthcare data, e.g., use of EMRs for clinical research

HCLS Ecosystem: Goal State

Patients, Public

Hospitals Doctors

Payors

CDC

CROs

PharmaceuticalCompanies

FDA NIH(Research)

Universities, AMCs

From FDA, CDC

Clinical Observations Interoperability will be a Critical Enabler to realize this Vision!

Functional Requirements

• X identifies the Use Cases, Systems and Functional Requirement under consideration of the COI Task Force• Based on the Functional Requirements Specification developed by EHRVA/HIMSS

Need for a bi-directional EMR – CTMS Link:Shareable Open Source Models of Clinical Data

Healthcare Provider 1

Healthcare Provider 2

…

Healthcare Provider N

OpenSourceClinicalModels- DCM- SDTM- BRIDG- Snomed- MedDRA- NCIT

…..

Clinical Trial 1

Clinical Trial 2

…

Clinical Trial M

Clinical

Observations

Clinical

Observations

Use Case: Patient Screening

Clinical Research ProtocolEligibility Criteria:

- Inclusion- Exclusion

EMR DATA

Meds Procedures

Diagnoses Demographics

…FailPassPass5/8 criteria met

Yes0033333

…………………

Pass

Pass

Criteria #3

(Pass/Fail/ Researcher Needs to Evaluate)

…

…

…

FailPass3/8 criteria met

No 0022222

Pass

No Criteria #2

(Pass/Fail/ Researcher Needs to Evaluate)

Pass 6/8 criteria met

Yes0011111

Criteria #1

(Pass/Fail/ Researcher Needs to Evaluate)

# Criteria Met / Total Criteria in Protocol

Potentially Eligible for Protocol

Patient MR #

Research Coordinator selects protocol for patient screening:

Research Coordinator views list of patients and selects which ones to approach in person for evaluation and recruitment.

Clinical Evaluation and Recruitment

- -

* Thanks to Rachel Richesson

COI Demo – Clinical Trial Eligibility Criteria

Use Case Step-Through

1. (Textual) specification of the eligibility criteria for a given clinical trial

2. Ontology-based translation of the eligibility criteria into SPARQL queries

3. Translation of the SPARQL queries into database-specific queries

4. Execution of the queries at the databases –results contain all eligible patients

5. Return of a list of eligible patients to clinical trial administrator

COI Demo – Selecting Inclusion Criteria

Inclusion in SDTM based ontology

SDTM based clinical trial

ontology

COI Demo – Drug Ontology Inference

Exclusion in Drug ontology

Drug ontologySubcla

sses o

f “an

ticoag

ulant”

COI Demo – Selecting Mapping Rules

#check all drugs that "may_treat obese" {?A rdfs:subClassOf ?B; rdfs:label ?D. ?B a owl:Restriction; owl:onProperty :may_treat; owl:someValuesFrom :C0028754} => {?D a :WeightLoseDrug}.

Medication:M0271 a sdtm:Medication;

spl:classCode 6809 ; #metformin sdtm:subject :P0006; sdtm:dosePerAdministration [ sdtm:hasValue 500; sdtm:hasUnit "mg„ ]; sdtm:startDateTime "20070101T00:00:00"^^xsd:dateTime ; sdtm:endDateTime "2008-0101T00:00:00"^^xsd:dateTime .

Criteria in SPARQL

?medication1 sdtm:subject ?patient ;spl:activeIngredient ?ingredient1 .

?ingredient1 spl:classCode 6809 . OPTIONAL { ?medication2 sdtm:subject ?patient ;

spl:activeIngredient ?ingredient2 .?ingredient2 spl:classCode 11289 .

} FILTER (!BOUND(?medication2))

metformin

anticoagulant

Exclusion Criteria

SDTM to HL7 Transformation

hl7hl7:Substance- :Substance- Administration Administration

hl7hl7:doseQuantity:doseQuantity

{ { ?x a ?x a sdtmsdtm:Medication ;:Medication ; sdtmsdtm:dosePer- :dosePer- Administration ?y Administration ?y} => {} => { ?x ?x hl7hl7:Substance-:Substance- Administration ; Administration ; hl7hl7:doseQuantity ?y:doseQuantity ?y}}

sdtmsdtm:Medication:Medication

sdtmsdtm:dosePer-:dosePer- Administration Administration

Clinical Trial Ontology

Clinical Practice Ontology

HL7 to EMR Database Transformation

hl7hl7:Substance- :Substance- Administration Administration

hl7hl7:doseQuantity:doseQuantity

{ { hl7:substanceAdministration hl7:substanceAdministration [[

aa hl7:SubstanceAdministration ;hl7:SubstanceAdministration ; hl7:consumable [hl7:consumable [

hl7:displayNamehl7:displayName ?takes ; ?takes ; spl:activeIngredient [spl:activeIngredient [

spl:classCode ?ingredspl:classCode ?ingred ]]] ;} => {] ;} => {

{{?indicItem Item_Medication:PatientID ?person;?indicItem Item_Medication:PatientID ?person; Item_Medication:PerformedDTTM Item_Medication:PerformedDTTM

?indicDate ;?indicDate ; Item_Medication:EntryNameItem_Medication:EntryName ? ?takes .takes .

..}}

SPARQL in Clinical Practice Ontology

SQL to EMR Database

Item_MedicationItem_Medication:EntryName:EntryName ?takes . ?takes .

MedicationMedication:ItemID:ItemID ?indicItem; ?indicItem;

Pushing Query to Database

• SPARQL in SDTM ontology to SPARQL in HL7 ontology

• SPARQL in HL7 ontology to SQL in EMR database

CT

Eligibility

HL

7 DC

M/R

IM

EM

R

SPARQL SQLSPARQL

List of eligible patients

SPARQL in SDTM

PREFIX sdtm: <http://www.sdtm.org/vocabulary#>PREFIX spl: <http://www.hl7.org/v3ballot/xml/infrastructure/vocabulary/vocabulary#>

SELECT ?patient ?dob ?sex ?takes ?indicDate?contra WHERE { ?patient a sdtm:Patient ; sdtm:middleName ?middleName ; sdtm:dateTimeOfBirth ?dob ; sdtm:sex ?sex . [ sdtm:subject ?patient ;

sdtm:standardizedMedicationName ?takes ; spl:activeIngredient [ spl:classCode ?code ] ;

sdtm:startDateTimeOfMedication ?indicDate ] . OPTIONAL { [ sdtm:subject ?patient ;

sdtm:standardizedMedicationName ?contra ; spl:activeIngredient [ spl:classCode 11289 ] ;

sdtm:effectiveTime [ sdtm:startDateTimeOfMedication ?contraDate ] . } FILTER (!BOUND(?contra) && ?code = 6809)}

SDTM-HL7 Mapping Rules

CONSTRUCT {?patient a sdtm:Patient ; sdtm:middleName ?middleName ; sdtm:dateTimeOfBirth ?dob ; sdtm:sex ?sex .

[ a sdtm:ConcomitantMedication ;sdtm:subject ?patient ;sdtm:standardizedMedicationName ?takes ;spl:activeIngredient [ spl:classCode ?ingred ] ;sdtm:startDateTimeOfMedication ?start

] .} WHERE {?patient a hl7:Person ;

hl7:entityName ?middleName ; hl7:livingSubjectBirthTime ?dob ; hl7:administrativeGenderCodePrintName ?sex ; hl7:substanceAdministration [

a hl7:SubstanceAdministration ; hl7:consumable [

hl7:displayName ?takes ; spl:activeIngredient [ spl:classCode ?ingred ]

] ;hl7:effectiveTime [ hl7:start ?start ]

] .}

SPARQL in HL7 Via SWtranformer

PREFIX hl7: <http://www.hl7.org/v3ballot/xml/infrastructure/vocabulary/vocabulary#>

SELECT ?patient ?dob ?sex ?takes ?indicDate WHERE{ ?patient hl7:entityName ?middleName . ?patient hl7:livingSubjectBirthTime ?dob . ?patient hl7:administrativeGenderCodePrintName ?sex . ?patient a hl7:Person . ?patient hl7:substanceAdministration ?b0035D918_gen0 . ?b0035D918_gen0 hl7:consumable ?b0035C798_gen1 . ?b0035D918_gen0 a hl7:SubstanceAdministration> . ?b0035D918_gen0 hl7:effectiveTime ?b0035C5E8_gen3 . ?b0035C798_gen1 hl7:displayName ?takes . ?b0035C798_gen1 hl7:activeIngredient ?b0035C848_gen2 . ?b0035C848_gen2 hl7:classCode ?code . ?b0035C5E8_gen3 hl7:start ?indicDate . FILTER ( ?code = 6809 )}

HL – Database Mapping Rules: Tables

PREFIX xsd: <http://www.w3.org/2001/XMLSchema#>PREFIX Person: <http://hospital.example/DB/Person#>PREFIX Sex_DE: <http://hospital.example/DB/Sex_DE#>PREFIX Item_Medication: <http://hospital.example/DB/Item_Medication#>PREFIX Medication: <http://hospital.example/DB/Medication#>PREFIX Medication_DE: <http://hospital.example/DB/Medication_DE#>PREFIX NDCcodes: <http://hospital.example/DB/NDCcodes#>

HL – Database Mapping Rules: Schema

CONSTRUCT { ?person a hl7:Person ; hl7:entityName ?middleName ; hl7:livingSubjectBirthTime ?dob ; hl7:administrativeGenderCodePrintName ?sex ; hl7:substanceAdministration [ a hl7:SubstanceAdministration ; hl7:consumable [

hl7:displayName ?takes ; spl:activeIngredient [ spl:classCode ?ingred]

] ; hl7:effectiveTime [ hl7:start ?indicDate ]

] . } WHERE {

?person Person:MiddleName ?middleName ; Person:DateOfBirth ?dob ; Person:SexDE ?sexEntry .

OPTIONAL { ?indicItem Item_Medication:PatientID ?person ; Item_Medication:PerformedDTTM ?indicDate ; Item_Medication:EntryName ?takes . ?indicMed Medication:ItemID ?indicItem ; Medication:DaysToTake ?indicDuration ; Medication:MedDictDE ?indicDE . ?indicDE Medication_DE:NDC ?indicNDC . } }

Drug Class Information in CT #8

• monotherapy with metformin, insulin secretagogue, or alpha-glucosidase inhibitors and a low dose combination of all

• Long term insulin therapy

• Therapy with rosiglitazone (Avandia) or pioglitazone (Actos), or extendin-4 (Byetta), alone or in combination

• corticosteroids

• weightloss drugs e.g., Xenical (orlistat), Meridia (sibutramine), Acutrim (phenylpropanol-amine), or similar medications

• nonsteroidal anti-inflammatory drugs

• Use of warfarin (Coumadin), clopidogrel (Plavix) or other anticoagulants

• Use of probenecid (Benemid, Probalan), sulfinpyrazone (Anturane) or other uricosuric agents

Prescription Information in Patient Database

• "132139","131933","98630 ","GlipiZIDE-Metformin HCl 2.5-250 MG Tablet","54868079500 ",98630,"2.5-250 ","TABS","","MG "," ","15","GlipiZIDE-Metformin HCl ","","GlipiZIDE-Metformin HCl 2.5-250 MG Tablet“

• "132152","131946","98629 ","GlipiZIDE-Metformin HCl 2.5-500 MG Tablet","54868518802 ",98629,"2.5-500 ","TABS","","MG "," ","15","GlipiZIDE-Metformin HCl ","","GlipiZIDE-Metformin HCl 2.5-500 MG Tablet“

• "132407","132201","98628 ","GlipiZIDE-Metformin HCl 5-500 MG Tablet","54868546702 ",98628,"5-500 ","TABS","","MG "," ","15","GlipiZIDE-Metformin HCl ","","GlipiZIDE-Metformin HCl 5-500 MG Tablet“

• "132642","132436","C98630 ","GlipiZIDE-Metformin HCl TABS","54868079500 ",98630,"","TABS",""," "," ","15","GlipiZIDE-Metformin HCl ","","GlipiZIDE-Metformin HCl TABS"

NDC Code

Drug Ontology By Stanford

from drug ontology documentation

NDC:54868079500: GlipiZIDE-Metformin HCl 2.5-250 MG Tablet

NDC: 54868518802: GlipiZIDE-Metformin HCl 5-500 MG Tablet

NDC:54868079500:GlipiZIDE-Metformin HCl TABS

CTmetformin,

insulin secretagogue

alpha-glucosidase inhibitors

anticoagulants

uricosuric agents

nonsteroidal anti-inflammatorydrugBank: DB00331RxNORM: 6809C0025598

Mapping Between CT and Patient Record

Drug Ontology

MechanismOfAction

GeneralDrugType

C1299007

C0066535

C0050393

Advantages of Semantic Web Technologies

• Plug and play use of multiple ontologies and information models based on industry standards (e.g., CDISC, HL7).

• Ability to access multiple points of view through declarative specification of mappings.

— Mappings across CDISC/SDTM and HL7 based information models— Mappings across terminologies such as NDC, RxNorm and Stanford’s Drug

Ontology

• Ability to map across terminologies via compositional definition of concepts, e.g., Obesity drugs

• Late binding of coding systems and database schema

• Transform SPARQL to SQL in real time, reflecting real time discovery and integration needs

Next Steps

• Solicit Feedback and Participation from the broader Biomedical Informatics communities

http://esw.w3.org/topic/HCLS/ClinicalObservationsInteroperability

http://hcls.deri.org/coi/demo

• Develop proof of concepts for a wider variety of use cases in collaboration with various participants in the HCLS Ecosystem

— Adverse Drug Event Reporting and Resolution

— Clinical Trials Data Collection

— Pharmaco-vigilance