Canada Health Infoway - Towards a National Interoperable Electronic Health Record (EHR) Solution.
Bibliographic record
Abstract
Canada Health Infoway Inc. (Infoway) is leading Canada's initiative to develop interoperable electronic health records (EHRs) and accelerate their adoption nationwide. Specifically, Infoway's core business is to invest with its partners-primarily provincial and territorial governments-in the development of robust, interoperable EHR solutions and in their deployment and replication across Canada. This partnership approach produces results faster, more cost-efficiently and more effectively than if any one partner acted alone.This chapter presents a high-level view of Infoway's seven-year plan to have the basic elements of interoperable EHRs in place across 50 percent of Canada by the end of 2009. In particular, the chapter discusses the business and technical approaches that have been developed to pursue Infoway's aggressive goal. These approaches allow individual jurisdictions to deliver local and regional solutions cost-effectively while contributing to a larger, interoperable national system.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.006 |
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".