1. Achieving Semantic Interoperability of Cancer Registries
NAACCR 2007 Annual Meeting
June 7, 2007
Peter Winkelstein, MD
Chief, Division of General Pediatrics
CMIO, UPA and UBA
University at Buffalo, New York

2. Informatics Goals for Cancer Registries
Improve efficiency and accuracy of data entry
Automated data extraction from EHRs and other systems
Automated data checking
Improve data extraction
Facilitate reporting (querying)
Facilitate secondary use of registry data
Translational research
Data mining

3. Computable Health Information
Registry data must be:
Stored in such a way as to be amenable to computational processes (e.g. database elements)
Have carefully defined meaning (e.g. ontologies)
Required for interoperability
Required for robust querying

4. What is Ontology (philosophically)?
A representation of some pre-existing domain of reality which:
reflects the properties of the objects within its domain in such a way that there is a systematic correlation between reality and the representation itself
is intelligible to a domain expert
is formalized in a way that allows it to support automatic information processing
(Source: Werner Ceusters, 12/23/2005)

5. What is an ontology (practically)?
A formal model of a domain which consists of:
Classes (aka concepts)
Instances (particular members of classes)
Instances are not generally part of published ontologies
Relationships between classes (aka roles)
In contrast to controlled vocabularies, which are word lists with no (or limited) relationships

6. Example

7. Syntactic vs. Semantic Interoperability
The ability to exchange information among systems and software, especially EHRs, is called interoperability
The ability to exchange data is called syntactic interoperability
Interfaces/Messaging
The ability to exchange data and meaning is called semantic interoperability
Interfaces/Messaging plus Ontologies

8. Syntactic Interoperability

9. Semantic Interoperability

10. Syntactic Interoperability Alone Is Not Enough
Free text data has little (if any) machine-interpretable meaning
Data elements are not guaranteed interoperable
Multiple encodings
Inflexible encoding
Incompatible lists/Granularity
Data abstraction
Impression vs. criteria
Qualitative qualifiers
Lack of standards

11. Semantic Interoperability
Semantic interoperability allows the exchange of both structure and meaning among systems
Requires data in structured form (database elements) plus encoding data with machine-interpretable meaning
Ontologies are the tools for this encoding

12. State-of-the-art in Ontology
There are few, if any, well-formed medical ontologies (or even controlled vocabularies)
Notably for cancer informatics, the current state of the NCI Thesaurus is suboptimal

13. Some Existing Vocabularies and Ontologies
Controlled Vocabularies
DICOM
LOINC
HCPCS
ICD-9
CPT
ICD-O
MedDRA
“Ontologies”
HL7 RIM
UMLS
NCIT
FMA GO
SNOMED-CT

14. Examples NAACCR Standards for Cancer Registries Volume II
Data Standards and Data Dictionary
Eleventh Edition
Record Layout Version 11.1

26. Keys to Achieving Semantic Interoperability
Structured data collection (no free text)
Highest granularity possible
Careful definition of meaning for each data element
Consistent use of each data element
Assignment of standard code to each data element if possible
Vocabulary creation and maintenance for meanings not available among current standards
Publication and versioning of all definitions

27. Recommendations
Cancer registries should move towards semantic interoperability
This would facilitate improvements in both data collection and extraction
A strong link to EHR data is particularly desirable
Registry organizations should actively work with vendors towards semantic interoperability with oncology EHRs