an ogms-based model for clinical information

Unrestricted © Siemens AG 2013. All rights reserved

An OGMS-basedModel for Clinical Information

ICBO Early Career Symposium / July 2013

Heiner Oberkampf1,2, Sonja Zillner1, Bernhard Bauer2 and Matthias Hammon3

1 Siemens AG, Corporate Technology, Munich, Germany2 Software Methodologies for Distributed Systems, University of Augsburg, Germany3 Department of Radiology, University Hospital Erlangen, Germany

Unrestricted © Siemens AG 2013. All rights reserved July 2013 Corporate Technology

Agenda

Clinical Data and Problem Description

The Model for Clinical Information

Storage and Queries

Related Work


Clinical Data

Unstructured, heterogeneous and complex.

• Data is mostly unstructured

• Data is not integrated

• Different data needs to be combined for clinical decisions

• Raw data needs to be interpreted to fasten clinical decisions (e.g. normal, abnormal, pathological …)

• Clinicians do not use the full information contained in existing patient data

Problems

Structured• Diagnosis• Procedures• Lab values• Demographics• Medication• Provider

Unstructured• Reports• Images• Omics data

Data


Patient Data

The development of our model is based on two datasets.

Project: Data Intelligence for Clinical Solutions(6 manually selected melanoma patients)• Demographics• diagnoses (ICD-10 codes)• lab values (LOINC codes)• procedures (OPS codes)• drug administration (ATC codes)• radiology reports• pathology reports• all data timestamped

Project: Theseus MEDICO (382 patients)• 2700 Radiological Reports• Image Annotations


Semantic Data Integration

The Hospital in Erlangen integrates their data into an i2b2 data warehouse.

Clinical Information

Systems

Model for Clinical

Information

i2b2

Data-Warehouse

• Raw data• Vendor specific

• Administration centric• BI applications (e.g. Oracle Health Data Model)

• Structured data is mapped to standardized terminologies (ICD, LOINC, OPS…)• Identification of patient cohorts

• Patient centric and granular data representation• Annotation of unstructured data• Use of medical ontologies and reasoning mechanisms


Questions to Answer

In perspective we want to answer the following questions using Model of Clinical Information (MCI).

Normal and abnormal structures• What findings about abnormalities do we have from

the latest examination?

Longitudinal data access• How does this finding evolved from last

examination?

Disease centric data access• Are there any cancer findings?

Organ centric data access• What information do we have regarding the liver

functioning?

Decision support• What are likely diseases?• What examinations should be provided next?


Semantic Model for Clinical Information

Agenda



Storage and Queries

Related Work


Technical Perspective

Technical and Clinical Perspective

Clinical Perspective

• Provide a holistic view on the patient• Make the change of the patient‘s health

status transparent• Point to missing information about

symptoms and signs.• Allow efficient and integrated access to

patient data• Provide a basis for clinical decision support

systems

• MCI integrates and structures clinical data and provides…• core concepts of clinical information• meta-information• interpretations

• Clinical data is expressed using MCI in combination with established ontologies like SNOMED, RadLex, LOINC, ICD …

• MCI is based on established upper level ontologies: BFO, OGMS, IAO …

• Use of medical knowledge contained in ontologies through reasoning

• Use of Linked Open Data: LinkedCT, SIDER, DrugBank, …


Big Picture

Integrating different data and knowledge resources.

Integrated Data Access

Clinical Information Systems

PACS, reports, treatment plans,

lab values, administrative

data …

Data Repositories(factual knowledge)LinkedCT, DrugBank, SIDER, DBpedia, …

Medical Ontologies (formalized knowledge)

SNOMED CT, ICD, LOINC, ATC, RadLex, DOID, FMA,

OPS, SYMP, …

Model for Clinical Information (MCI)


Ontologies from the OBO Foundry

MCI is based on established upper ontologies

Basic Formal Ontology (BFO1.1)Completely domain independent

Ontology for General Medical Science (OGMS)basic clinical concepts like, e.g., diagnosis, clinical finding,pathological anatomical structure …

Ontology of Medically Related Social Entities (OMRSE)Patient role, healthcare provider role, gender role …

Information Artifact Ontology (IAO)document, report, figure ...

Relations Ontology (RO)has_part, has_participant, located_in …

Units Ontology (UO)Subset: units for length, mass and time.

Clinical Narrative Temporal Relation Ontology (CNTRO)(not from OBO Foundry)Subset: ObjectProperties before, after, overlap …

Total MCI

Classes 358 62

ObjectProperties 82 20

DatatypeProperties 19 14


Added Classes (I)

Extensions under ‘obo:data item‘.

mci:patientposition

mci:radiologicalexamination

_:re01 _:pp01

radlex:standingposition

mci:has examination modality

_:ce01

obo:clinicalencounter icd10:C79_8

obo:has specified output

mci:maindiagnosis

_:md01

Examination modality

Diagnosis

rdf:type


Added Classes (II)

Extensions under ‘obo:clinical finding‘ – interpretations of clinical findings.

mci:approximately

obo:length measurement

datum

0.8^^xsd:decimal

obo:has measurement unit label

obo:imagefinding radlex:lymph

node of thorax

obo:is about

mci:anatomical structure

obo:has measurement value

_:if01 _:as01

_:lmd01uo:centimeter

rdf:type…thoracic lymph node of ca. 0.8 cm.


Added Properties


mci:anatomicalstructure

Example Representationof a Radiological Image Finding

Spleen at hilum with diameter 10 x 4 cm

mci:precisely

4^^xsd:decimal


obo:imagefinding radlex:spleen

obo:is about



_:if01 _:as01

uo:centimeter

10^^xsd:decimal

_:lmd02obo:has measurement value


datum

_:lmd01

radlex:hilumof spleen

_:as02

PATO:diameter

_:q02

obo:is quality measurement of_:q01

mci:locationspecification



Agenda



Storage and Queries

Related Work


Jena Fuseki

Triple Store

Datasets and Named Graphs are used to separate triples.

/mci

/radlex

/patient23000PX1LH

/ops

/icd10

/atc

1) We transformed the the OPS hierarchy from in XML to RDF using XSLT.2) We transformed ATC from Excel to RDF

1

2

Named Graphs for clinical encountersNamed Graphs for clinical encounters…

/patient23000JJ43N

Named Graphs for clinical encountersNamed Graphs for clinical encounters…

……


Querying the Model

All findings about the gastrointestinal tract.

obo:imagefinding

obo:is about


_:if01 _:as01

radlex:wall of sigmoid colon

Radlex:sigmoidcolon

radlex:gastrointestinal tract

radlex:distal part of sigmoid colon

SELECT ?fWHERE {

SERVICE <http:localhost:3030/radlex/sparql>{ SELECT ?partOfGastroIntest

WHERE {# part of the gastroint. tract?partOfGastroIntest radlex:Part_Of+ radlex:RID94 .

}}

?f a obo:OGMS_0000014; # a obo:clinical findingobo:IAO_0000136 [ # which is about

# some part of the gastroint. tracta ?partOfGastroIntest].

}


SPARQL Update Queries

Normal and abnormal status of findings about lymph nodes.

INSERT {?f a ?findingType .

}WHERE {

SERVICE <http:localhost:3030/radlex/sparql>{ SELECT ?lymphNode

WHERE {?lymphNode rdfs:subClassOf radlex:RID13296 .

}}

?f a obo:OGMS_0000014; # a obo:clinical findingobo:IAO_0000136 [ a ?lympNode ]; # which is about some lymph node(mci:MCI_0000056 | mci:MCI_0000057) [ # approximately or preciselya obo:IAO_0000408 ; # a length measurement datumobo:IAO_0000039 uo:UO_0000015; # has measurement unit label uo:centimeterobo:IAO_0000004 ?v; # has measurement value ?v

] .BIND( IF(?v <= 1),

mci:MCI_0000034, # normal findingmci:MCI_0000035 ) # abnormal findingAS ?findingType)

}

mci:approximately


datum

0.8^^xsd:decimal


obo:imagefinding radlex:lymph

node of thorax

obo:is about



_:if01 _:as01

_:lmd01uo:centimeter

obo:normalfinding



Agenda



Storage and Queries

Related Work


Related Work (I)

Existing open data models.

Model Motivation Status Difference to MCI

HL7 Reference Information Model v3

• supplement to standards for messaging and clinical documents (CDA)

• 2010: first owl-version• inconsistent definitions of concepts

• MCI is based on established upper level ontologies

IHE • cross institutional EHRs • mainly for data exchange• based on standards likeHL7, XACML, SAML• granular access rights

OpenEHR

• interoperability and computability in e-health• formal representation of clinial data

• archetypes and templates• use of external terminologies

• not in RDF

i2b2 SMART Data Model • supplement to the i2b2 datawarehouse

• work in progress• should be the basis for i2b2 SMART applications

• MCI is based on established upper level ontologies

Translational Medicine Ontology (TMO)

• data integration for clinical studies

• actively worked on by the W3C HCLS interest group

• focus on studies, especially with relation to omics data

Computer based Patient Record (CPR)

• creation of a semantic patient model based on BFO and BioTop

• last modification in July 31th

• MCI builds upon OGMS• BioTop is not included

… … … …


Related Work (II)

Existing data models from horizontal IT providers.

Model Motivation Status Difference to MCI

Oracle Healthcare Data Model

• DWH• implement healthcare specific KPIs for reporting

• extended model for BI• many temp. concepts• reporting

• more concepts (many for adm.)• focus on hospital organization

Teradata HealthcareLogical Data Model

• DWH• framework for knowledge applications

• “single view of your enterprise”• strategic business and clinical information

• administration centric• focus on the hospitals organization

IBM Healthcare Provider Data Model

• DWH• health analytics• business insights• „innovate and improve the cost, quality and experience of healthcare”

• connection to IBM warehousing platforms and BI applications• application modules for “patient care and insights”

• administration centric• focus on hospital organization

… … … …


Heiner OberkampfPhD student

Corporate TechnologyCT RTC BAM KMR-DE

Otto-Hahn-Ring 681739 München, Deutschland

Tel: +49 89 636-37566Fax: +49 89 636-49438Mobile: +49 176 49839029

E-mail:[email protected]

Questions ?

an ogms-based model for clinical information

Technology

clinical encountersnamed graphs

sigmoid colon radlex

clinical information storage

image finding radlex

anatomical structure obo

clinical finding obo

clinical information

lymph node