1. Building chronic disease registries from EMR and administrative data
Elodie Portales-Casamar
Clinical Assistant Professor, Dept of pediatrics, UBC
Clinical Research Informatics Lead, CFRI

2. Outline Background Proof-of-concept Cross-Canada Opportunities
Context/Challenges/Needs for Registries
Solution: i2b2 & SHRINE
Proof-of-concept
Pediatric Diabetes Registry
Two partner sites: Vancouver, BC & Edmonton, AB
Cross-Canada Opportunities

3. Context
Disease registries are a fundamental tool for surveillance, monitoring and outcome measurement along with many other research applications from epidemiology to biomarker discovery.

4. Challenges Quantity and quality of data from multiple sources
No standard platforms
Inconsistent vocabulary
Provincial, national and international boundaries
Limited integration with the clinical systems

5. Needs Data integration technology
Interoperability and data sharing technology
Consistent vocabularies
Address privacy regulation across jurisdictions

6. Solution
Informatics Integrating Biology & the Bedside (i2b2) data warehousing framework
NIH-funded initiative
scalable open-source software
enables secondary usage and sharing of clinical data for discovery research
SHRINE Data Sharing Network

7. Build on Successes e.g. ImproveCareNow
US Pediatric IBD Network
Modular pediatric chronic disease registry for Quality Improvement and Clinical Effectiveness research

8. Build on Successes e.g. Childhood Arthritis & Rheumatology Research Alliance (CARRA) Registry
North American Network of pediatric rheumatology research centers
Observational registry to assess therapeutics used to treat pediatric rheumatic diseases

9. Enable high performance collection of medical record data for querying and distribution
Enterprise web client
Create patient cohorts for further investigation
Enable discovery within data on enterprise wide scale

11. Data remains in local Clinical Data Warehouse (e.g. i2b2 repository)
Broadcast queries and aggregate responses
No central database
Hospital Autonomy: each site remains in control over all disclosures
Patient privacy: no attempts to re-identify patients

12. Proof-of-Concept Time-frame: 1 year Focus on one disease: Diabetes
Two partner sites:
CFRI, BC: BC Children’s Hospital and UBC
WCHRI, AB: Stollery Children’s Hospital and U of A
Use mock-up data modeled from the real clinical data
Deliverable: Assessment of technical implementation feasibility

13. Collaborators Informatics Clinical Partners Lawrence Richer, WCHRI
Elodie Portales-Casamar, CFRI
Clinical
Elizabeth Rosolowsky, U of A
Shazhan Amed, UBC
Partners
Anne Junker, MICYRN
Wyeth Wasserman, CFRI

14. Model EMR EMR i2b2 i2b2 SHRINE Authorized User
I2b2 User Query Interface
Webserver
EMR
Clinical Data Warehouse
EMR
Clinical Data Warehouse
i2b2
Research Data Warehouse
i2b2
Research Data Warehouse
SHRINE
Federated Queries
Data Aggregation
Administrative
Health Data
Administrative
Health Data
BC Children’s Hospital
Stollery Children’s Hospital

15. EMR Data Demographic Data Clinical Data* DOB Personal health number
Contact information
Geographic location
Diagnosis
Anthropometric data
Vital signs (Blood pressure,…)
Lab results (A1C, TSH,…)
Medication (Insulin regimen,…)
*for every patient visit

16. Administrative Data
BC Ministry of Health (via PopData BC) or Alberta Health Services
Physician Billing (Medical Benefits)
Hospitalizations (DAD)
Rx dispensations
Demographic data
Vital Statistics

17. PoC Objectives
Demonstrate the utility and feasibility of a Canadian translational research informatics infrastructure that can:
Address key questions, such as:
epidemiology within and across provinces
prevalence of co-morbidities
adherence to recommended course of treatment
Facilitate research study development through easier and consolidated data access

18. PoC Technical Considerations
EMRs are poorly standardized
Vocabularies/terminologies are different and need to be mapped to one another
Disease definition varies across jurisdiction
Different algorithms have been developed to define diabetes cases
To be able to compare cases across province, the same case definition needs to be used

19. Broader Challenges Privacy/Legal framework Risk Aversion
Unconnected data stewardship and governance
Cross-jurisdiction
Risk Aversion
Multi-step data access processes
Highly qualified personnel

20. Opportunities in BC Clinical & Systems Transformation
Population Data BC
SPOR Support Unit
Provincial Data Platform

21. Fractal Model for BC Health Data
Data is organized, managed and accessed locally
To share, we need standardization and coordination across the pieces
Coming together is a real opportunity but we can each assemble and manage the infrastructure we need

22. Fractal Model for BC Health Data
How to make it work:
Individual infrastructure
Qualifying security, privacy, analytic characteristics
Central location(s) for linking data
Minimal essential data standards

23. Opportunities across Canada
SPOR SUPPPORT Units
Emerging Informatics Efforts
MICYRN Clinical Research Informatics working group

24. Thank You.