The technology strategy will outline the framework to ensure technological interoperability and adherence to all DHDP standards relating to governance, security, privacy and confidentiality principles.
This strategy will detail the DHDP Standards Certification Services and the Auditability and Regulatory Services that allow for simultaneous collaborative research. This includes defining and supervising the continuous delivery of technology-related digital maturity models through domain transformation.
Frequently Asked Questions about our Technology
It is well documented that well-informed patients readily give their consent to data sharing for research purposes. What is not well understood is the willingness of hospitals to share data. Any comment on this?
As custodians of patient information, healthcare institutions have the responsibility to ensure patient privacy and data security is protected. In the context of research projects, Institutional Ethics Review Boards are involved in ensuring that the data used for research has appropriate consent, and that the use of this data is reasonable. Complexities arise when data consented for research leads to IP generation then managed outside the scope of ERB, by offices of technology transfer. The DHDP’s approach to address this challenge is to design and implement a federated data governance framework. This framework will ensure the security and traceability of all of the data within the ecosystem, and is built on three key principles: Autonomy, Diversity and Privacy by Design. Custodians will always retain control, and autonomy over their own data, which will never leave their local servers. For instance, custodians can decide which data to use for which projects. Through the platform, clinicians and researchers will have access to easy to use, analytic tools that have been developed by data scientists and AI experts, allowing them to generate robust clinical evidence by leveraging diverse datasets from across multiple sites, going beyond what is available to them locally. By taking a privacy by design approach, patient data and other sensitive data will be respected through all aspects of the initiative: The DHDP federated data governance framework allows experts to build robust sophisticated machine learning models, and learn collectively from the data without ever sharing any sensitive private information.
How are you planning on accessing the data at the sites? Are you expecting challenges in deploying DHDP across the sites as they will be using different recording systems and languages?
A DHDP Appliance will be installed in participating sites across Canada. This appliance is a digital infrastructure and will contain common DHDP tools including the certification service that will protect patient privacy and data security. Through this local appliance, data consumption networks - Imagia’s EVIDENS Platform and CanDIG - will access and process the sites’ local data. The DHDP has committed to providing an open-source data lake technology (OSDL) that can facilitate local data aggregation (static data or live clinical data). Independently, Imagia’s EVIDENS Platform provides the capabilities to ingest, index and structure static and live clinical data. As we work through the integration of the foundational sites, the DHDP will build an integration playbook that future sites can refer to in preparation for integration of the DHDP. Interoperability mechanisms will be put in place between the two data consumption networks to leverage their respective capabilities.
A DHDP Integration Working Group was formed in late 2020. It includes key individuals at the foundational sites who can socialize the concept of the DHDP and facilitate its integration. The researchers in the Marathon of Hope Cancer Centre Network have already identified multiple cancer cohorts in each of the foundational sites that can be contributed to the DHDP. Similarly, EVIDENS members are already engaging into collaborative multi-institutional research projects through Imagia’s EVIDENS Platform. The DHDP submission to ISED also had the support of researchers in the field of neurodegenerative diseases. Success stories from the federation of these early cohorts will help build additional interest and willingness to contribute data in additional healthcare domains.
Do researchers and clinicians want to see which feature(s) of the image was the most important for the AI algorithm to make a decision?
Yes. Explainability and understanding of what is activated in the model is imperative. This feature is not currently available on the EVIDENS Platform. In healthcare, understanding what the features mean, what the model is looking at, and breaking open this blackbox is a key necessity both during research and clinical practice.
Is there a longer-term plan for interoperability with international datasets (e.g., via GA4GH principles and tools)? Is there a plan to introduce a data access application system using GA4GH Passport or a similar approach?
The DHDP Technology Committee will strongly recommend the use of standards developed by GA4GH, as they are state of the art in genomics and data sharing. CanDIG, one of the two identified DHDP data consumption networks, is a GA4GH driver project. This will help us ensure efficient and secure collaboration both across Canada and internationally. Other initiatives to create data interoperability standards in other domains will be taken into consideration by the DHDP Data and Technology committees.
How far along is this DHDP technology at the moment - when will clinical researchers be able to utilize this developing network?
Both data consumption networks EVIDENS Platform and CanDIG, are established. We are currently building out the DHDP certification service and defining the standards that will enable the operationalization of open innovation across DHDP Member institutions. Timelines will be communicated once development plans have matured further.