PP19 Advances in community paramedicine in response to COVID-19
Bibliographic record
Abstract
Background Already well situated in the community, paramedics work collaboratively with other community partners to ensure patients receive the services that they require and the high quality in-home and in-community care they deserve. The ongoing COVID-19 pandemic has highlighted the prevalence of social inequities in Canada, particularly in already marginalized groups, and the importance of social connectedness and caregiver wellbeing solutions. We sought to explore innovations in community paramedicine programs across Canada in response to COVID-19. Methods We conducted a scoping literature review of community paramedicine publications since 2020, with a focus on Canadian context, and undertook semi-structured interviews with key informants to capture innovations that may not be well represented in the literature. Results A total of 22 studies, combined with 26 grey literature sources were identified through the literature search. We interviewed ten stakeholders from diverse community care and community paramedicine settings across Canada to further explore each element of the conceptual framework. A conceptual framework (Figure 1) was developed to categorize the literature and findings into themes, namely: leveraging technology (e.g., virtual consultations, remote monitoring); responding to COVID-19 (e.g., mass testing and vaccination); addressing social needs (e.g., home visits, helping patients with groceries); caring for vulnerable populations (e.g., providing palliative care at home). These innovations were united in the idea of collaborating with other health care professionals and agencies, while facilitating care and case management coordination. Conclusions The COVID-19 pandemic has highlighted the essential collaborative care role community paramedicine programs can provide to patients in their homes or communities. Community paramedicine programs have evolved to meet the needs of their communities. These programs have demonstrated their ability to support public health measures, provide home and community-based care, and most importantly, collaborate with other health care professionals in coordinating and providing care to Canadians regardless of social circumstances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.041 | 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 teacher head, 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".