CENTRE FOR COMPARATIVE GENOMICS
Western Australia
RVA Rare Disease Summit 2015 Melbourne 27-28 March
A rare disease knowledge framework: addressing key informatics challenges to support the patient journey
Matt Bellgard Director, CCG Research Affiliate, Western Australian Neuroscience Research Institute Research Fellow, NCGR, Santa Fe, NM
Overview
• Registries in Context
• Second Generation Registry Framework
• RD Registry Roadmap
Diagnosis/Treatment Challenge
• “If diagnosis begins with standardized data collection, doctors bring clinical judgment to bear at the final stage of diagnosis”
Lawrence and Lincoln Weed, 2011 • Health care reform
– Patient-centred care is defined as care that is “respectful of and responsive to individual patient preferences, needs, and values, and ensuring that patient values guide all clinical decisions”
Reuben et. al, Goal-oriented patient care — an alternative health outcomes paradigm. N Engl J Med 2012; 366: 777-9.
– To what extent is patient-centred care part of routine care to influence clinical decision making?
Webb et al. Treatment Goals – health care improvement through setting and measuring patient-centred outcomes. Critical Care and Res. 15: 2, 2013.
.
http://www.infogineering.net/data-information-knowledge.htm
• Data can directly inform knowledge • Data can be collected and become information, which
in turn facilitates knowledge
Rare Disease Registries
Data vs Information vs Knowledge => Clinical decisions
Items to consider for registry creation
http://www.treat-nmd.eu/dmd/patient-registries/toolkit/
Purpose: • Recruitment • Contact registry • Clinical Trials • Post market and Surveillance • Clinical registry
What system to use?
Registry Challenges
• Registries (typically): – Stand alone
• Unnecessarily duplicated • Limited scope and accessibility • Requirements change over time
– Developed on different platforms • Vendor-specific • Differing skill base • Different system designs
– Varying levels of security
– Not interoperable – Sustainability – Implement their own Data elements
• Physiological measurements – E.g. DOB, BMI, Fatigue, Surgeries, genotype
• cannot be shared
Bellgard et al. Dispelling myths about rare disease registry system development, SCFBM 2013
Registry System Evolution
Standalone Registry Design
Paradigm 1: Software developers do most of the Registry development effort
Software Developers
Users
Paradigm 1
Registry System Evolution
Standalone Registry Design
Global Registry Efforts
RDRF First Generation • Static Creation
Paradigm 1
Rare Disease Registry Framework Modular design
Bellgard et al, 2012
Rare Disease Registry Development
• The CCG has developed a number of Rare Disease Registries for the Health Department of Western Australia, and the Office of Population Health Genetics.
• Currently we have the following registries : – Australian/NZ Duchenne Muscular Dystrophy Registry
https://nmdregistry.com.au/dmd/), online since 2010
– Australian Myotonic Dystrophy Registry (https://nmdregistry.com.au/dm1/), online since 2011
• Deployed (not Live) – Australian Spinal Muscular Atrophy Registry (https://nmdregistry.com.au/sma/), online since 2010
Paradigm 2: Users create registries
Software Developers
Users
Software Developers
Users Curators Clinicians
Clinical Researchers
Paradigm 2 Second Generation RDRF
Paradigm 1
Focus on Tools
Registry Frameworks An essential new dimension
Overview
• Registries in Context
• Second Generation Registry Framework
• RD Registry Roadmap
Registry System Evolution
Standalone Registry Design
Global Registry Efforts
RDRF First Generation • Static Creation
RDRF Second Generation • Dynamic Registry Creation
Paradigm 1
Paradigm 2
RDRF: Second Generation
A highly dynamic web framework for the creation of disease registries with no extra software development
• RDRF Completely dynamic • Users can create
– Complete registries – Define all the DEs that define a given registry – All from within the system without the need of software developers
• Patients can be in more than one registry • A registry can be either contact, clinical, surveillance, disease-
specific – Framework needs to cater for changing needs
Bellgard et al. Second Generation Registry Framework, SCFBM, 2014
Registry structure
Registry
Forms …
Sections
…
Form 1 Forms Form 2
Section 1 Sections Section 2
Sections Section 3 …
DEs DE2 DE3 DE1 DE4 DE5 DE6 DE7 DE8
… PVGs PVG1 PVG2 PVG3 PVG4 PVG5 PVG6 PVG7
RDRF – Second Generation
The first version of the registry is defined on: https://rdrf.ccgapps.com.au/gaucher/registry/GR
Log in with username: grcurator and password: grcurator
Gaucher Registry – log in details
Different levels of access permissions of data are available, and are typically modified by the admin user. Current roles include curator,
clinician, and genetic staff
RDRF – Construction of registry
RDRF – Data Elements
Gaucher Registry – Patient-centric
Patients are able to fill in and submit the
questionnaire, which is then stored as a
‘questionnaire response’ and validated by a curator.
This creates the patient record in the registry
Patient Questionnaires are exposed on a public URL:https://rdrf.ccgapps.com.au/gaucher/GR/questionnaire/
Gaucher Registry Questionnaire validation
Once logged in, the curator can validate questionnaire responses and view patients
RDRF – Multiple registries
Current application of RDRF
Patient advocate driven (through WA Health) • DMD (live), DM1 (live), SMA Clinical, patient advocate, industry driven (in preparation for deployment) • FH • Gaucher (Wellcome Trust/Shire/RVA) In development/discussion • FKRP – Newcastle (UK) • TreatNMD - Newcastle (UK) • Angelman • HAE • FSHD (UK, Australia) • Microangiopathic Thrombocytopenia • Mitochondrial disease • Bronchiectasis • DMD Surveillance (living with DMD) • Dystrophies in India (India-wide)
Overview
• Registries in Context
• Second Generation Registry Framework
• RD Registry Roadmap
Drag and drop DEs into Registries
Bellgard et al. Dispelling myths about rare disease registry system development, SCFBM 2013
Registry Aggregation
RDRF: Knowledge Management
Standalone Registry Design
Global Registry Efforts
RDRF First Generation • Static Creation
RDRF Second Generation • Dynamic Registry Creation
RDRF Third Generation • Decision support
Paradigm 1
Paradigm 2
Evidence-based decision support e.g. Digital Referral
http://www.healthnetworks.health.wa.gov.au/modelsofcare/
Matchmaker/RDRF interaction
Summary
• It is possible to currently share rare disease data – Significant advances are required to share data in a
sophisticated way • Data elements specifications and registry definitions, structured data (ontologies) • Enable EHR interoperability • Clinical decision support, analytics, training and economics
• Registry requirements evolve over time – Dynamic creation of registries at runtime
• No requirement of software developer • Reusable components (DEs and DDEs)
– For a new registry, survey, clinical study, and so forth
• Support the patient journey – Capture knowledge – Associate patients seamlessly across registries
Acknowledgements
CCG • Adam Hunter • Lee Render • Maciej Radochonski • Kathryn Napier • Steve Wilton • Sue Fletcher • Alan Bittles
Dept. Health, WA OPHG • Hugh Dawkins • Leanne Lamont • Caroline Graham Public Health • Tarun Weeramanthri Genetic Services • Jack Goldblatt • Gareth Baynam
ORDR, NIH • Stephen Groft • Yaffa Rubinstein
EU Collaborators Especially • Hanns Lochmüller • Christophe Béroud • Ivo Gut • David Salgado • Oksana Pogoryelova • Libby Wood
Rare Voices Australia • Megan Fookes • Lesley Murphy • Rebecca Novacek Shire Australia • Cameron Milliner
