212.3: Developing a modernized Canadian organ donation and transplantation (ODT) data and reporting system
Bibliographic record
Abstract
Despite significant advances in organ donation and transplantation (ODT), the need for lifesaving organ transplants in Canada continues to exceed the availability of donated organs. International comparisons show that Canada under-performs on ODT measures compared to peer countries, including rates of living and deceased organ donation, and significant variation exists across Canadian jurisdictions. Health system leaders across Canada identified the need for a modernized, pan-Canadian ODT system to support improvements in access, care and outcomes. The Canadian Institute Health Information (CIHI) and Canada Health Infoway (Infoway) are co-leading a multi-year project, funded by Health Canada, to achieve a world-leading ODT system through the deployment/integration of digital solutions to modernize workflow and improve data quality, as well as develop a pan-Canadian ODT data repository to enable system-level performance reporting. This initiative covers five work streams, outlined below. These are achieved through extensive engagement and collaboration with Canadian ministries of health, health organizations, clinicians, researchers, patients, families, donors and other stakeholders in the ODT community. 1.Data standards: Develop Canadian minimum data sets and interoperable data standards for deceased donation, living donation and transplantation. 2.Indicators and measures: Prioritize and develop Canadian ODT performance indicators and measures. 3.Digital solutions and integrations: Procure, implement, and integrate modern data management solutions to organ donation organizations (ODOs) and transplant centres in Canada. 4.Data repository and access: Design, build and deploy a pan-Canadian ODT data repository with longitudinal follow-up and data access capabilities to facilitate program and system planning, policy development, research and innovation. 5.Performance reporting: Develop and implement public and secure performance reporting tools for ODT. To date, work stream activities and key milestones include: deployment of a deceased donation management solution and integration projects resulted in the capacity for digital organ offers as well as new national Application Programming Interface (API) data submission standards for deceased donation. Progress towards improving interoperability of ODT data systems through the adoption of international standards, and a set of indicators were prioritized for public and secure reporting, following an extensive consultation process. This initiative offers the opportunity for knowledge exchange with ISODP attendees about the journey to create a national ODT data system that capitalizes on current technical system capabilities. Topics include: (1) the challenges of integrating existing data ecosystems from ODOs and transplant centres, (2) the importance of leveraging the strengths/expertise of partnering organizations; and (3) the value of collaboration and engagement with all relevant ODT stakeholders. CIHI and Infoway acknowledge and thank Health Canada as the funder for this project.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.008 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".