Home health monitoring during the COVID pandemic: Results from a feasibility study in Alberta primary care
Bibliographic record
Abstract
The expansive geography of Central Alberta presents many barriers to optimal care, including limited resources and access issues. In response to the COVID-19 pandemic, primary care networks (PCNs) within Central Alberta partnered with a technology provider to rapidly implement home health monitoring (HHM) for patients with chronic diseases. In the 37 patients evaluated in phase 1 (90 days), diabetes was most common (73%), followed by hypertension (38%), chronic obstructive pulmonary disease (27%), and heart failure (11%). Overall, patients were comfortable using the HHM technology, and >60% reported improved quality of life after follow-up. Patients also made fewer visits to their family physician/emergency department compared with the pre-enrolment period. In January 2021, the HHM initiative was expanded to a larger patient cohort (phase 2; n = 500). Interim results for 90 patients from eight PCNs up to the end of May 2021 show similar findings to phase 1.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".