Remote Monitoring Programs for Cardiac Conditions in Canada: An Environmental Scan
Bibliographic record
Abstract
This Environmental Scan aimed to provide an overview of the current remote monitoring landscape for chronic cardiac conditions in Canada and was informed through a limited literature search and a survey completed by key stakeholders across Canada. Based on the results from the limited literature search and survey responses, remote monitoring programs are currently offered in British Columbia, Ontario, New Brunswick, Prince Edward Island, and Newfoundland and Labrador for patients with chronic cardiac conditions such as heart failure and hypertension, and for patients eligible for cardiac rehabilitation. These remote monitoring programs share common components and are intended to allow for greater patient autonomy and engagement, improved quality of life, and fewer hospital visits and admissions. There are many operational considerations that inform the implementation of remote monitoring programs in Canada. These operational considerations can act as barriers or facilitators to establishing and developing new remote monitoring programs. The most common identified barriers to program implementation are resourcing and funding limitations, whereas the most common facilitators to program implementation are patient engagement and a recent uptake in remote care in the wake of COVID-19. There are also many operational considerations that impact the maintenance of established remote monitoring programs in Canada. Similar to the barriers that affect program implementation, resourcing and funding limitations are the most commonly identified barriers to the maintenance of established remote monitoring programs. Positive patient experiences and the application of a teams-based approach to care are common facilitators to program maintenance. There is a gap in the jurisdictional representation from some provinces and territories in remote monitoring programs for patients with chronic cardiac conditions in Canada. Evidence-based guidelines for Canadian remote monitoring programs for chronic cardiac conditions or cardiac rehabilitation in Canada were sought but did not yield any results.
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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 | 0.007 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.014 | 0.045 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.000 |
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".