Theodoros. N. Arvanitis, RT, DPhil, CEng, MIET, MIEEE, AMIA, FRSM

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TRANSFoRm Theodoros. N. Arvanitis, RT, DPhil, CEng, MIET, MIEEE, AMIA, FRSM Biomedical Informatics, Signals & Systems Research Laboratory School of Electronic, Electrical & Computer Engineering College of Engineering and Physical Sciences University of Birmingham Birmingham Children s Hospital NHS Foundation Trust TRANSFoRm is partially funded by the European Commission - DG INFSO (FP7 247787) 1

Knowledge in healthcare Specific research knowledge Clinical trials Controlled populations Well-defined questions EHR systems Wide coverage Vast quantity May lack in detail and quality Routinely collected knowledge Actionable knowledge Distilled scientific findings Usable in clinical practice Decision support 2

The challenge of representing knowledge in an interoperable computable form Developing a user understandable, computable and extensible knowledge representation scheme for capturing clinical trials concepts and information (knowledge) with a multilingual support The foundation of interoperability lies with a shared understanding of concepts and data representation between systems: it is necessary to establish both syntactic (model-based) and semantic interoperability to represent knowledge in a computable form 3

Cohort identification as part Clinical trials life-cycle Adapted from Source: Douglas Fridsma, MD, PhD The University of Pittsburgh Cancer Institute Centre for Pathology and Oncology Informatics Clinical Trials Research Core 4

Query Formulation Workbench Provides tools necessary to author, store and deploy queries of clinical data to identify subjects for clinical studies: query authoring for the identification of research subjects based on existing ehr data use of semantic mediator services Semantically aware Enables easy authoring of distributed searches to EHR and other clinical data sources Uses a controlled vocabulary service and appropriate standards-based technological solutions Automatically identifies prevalent cases for research Count eligible subjects, flag the subjects for recruitment and consent by the local clinical care team Full compliance with data protection legislation and best practice 5

Overall Design Approach The development of the system adopts a model-based approach, where the TRANSFoRm Clinical Research Information Model (CRIM) provides a computable information model for eligibility criteria. Criteria concepts, especially clinical concepts, can be browsed and selected through the TRANSFoRm Integrated Vocabulary Service. The vocabulary service provides mappings from standard UMLS concepts to standard EHR or clinical data sources coding schemes. The eligibility criteria are captured in a computable representation, based on the Clinical Data Integration Model (CDIM) ontology CDIM captures an extensible common representation of clinical care data 6

Conceptual Architecture CDIM Ontology (1) Clinical Codes Vocabulary Service CDIM-DSM mapping TRANSFoRm Query Formulation Workbench (2) Search Criteria Distributed Infrastructure (3) Local Query EHR for Data Extraction and DS (5) Query Result Linkage (4) Query Result Clinical Researcher Provenance Service 7

Vocabulary Service: RCD v2/icpc2 Read Codes (RCDv2) and International Classification of Primary Care (ICPC2) corpus of terms and their associated mappings created to cater for the initial need of the existence of specific primary care oriented terminologies. The UK NHS Connecting for Health Terminology Centre - mappings from Read Codes version 2 to SNOMED CT. The Read Codes v2 database in Transform VS is set up based on this mapping so that Read Codes 2 concepts can be linked to a UMLS search. Similar approach for ICPC2. ICPC2-ICD10 Thesaurus and mappings - Transition Project @ University of Amsterdam The TRANSFoRm team is updating the ICPC-ICD 10 mapping and Thesaurus UMLS Metathesaurus Read Codes v2 Codes UMLS Metathesaurus ICPC2 Codes SNOMED CT Codes ICD-10 Thesaurus/Codes 8

Demo of the Vocabulary Service 9

Demo of Eligibility Criteria Creation 10

Submitting Queries 11

Identifying prevalent cases through eligible counts 12

TRANSFoRm Dr Theodoros N. Arvanitis University of Birmingham Birmingham Children s Hospital NHS Trust University of Birmingham Clinical Informatics Research Team: Sarah Lim Choi Keung, James Rossiter, Lei Zhao