The Alberta Telestewardship Network: Building a platform to enable capacity building in antimicrobial stewardship—results of an initial pilot study
Bibliographic record
Abstract
Background: Resources to improve antimicrobial stewardship (AS) are limited, but a telestewardship platform can enable capacity building and scalability. The Alberta Telestewardship Network (ATeleNet) was designed to focus on outreach across the province of Alberta, Canada, and facilitate AS activities. Methods: Outreach occurred virtually between pharmacists and physicians in hospital and long-term care settings throughout Alberta via secure, enterprise video conferencing software on both desktop and mobile devices. We used a quantitative questionnaire adapted from the telehealth usability questionnaire to capture the health provider's experience during each session. The questionnaire consisted of 39 questions, and a 5-point Likert scale was used to assess the degree of agreement and collate responses into a descriptive analysis. Results: A total of 33 pilot consultations were completed between July 6, 2020 and December 15, 2021. The majority (22, 85%) of respondents agreed that video conference-based virtual sessions are an acceptable means to provide health care and that they were able to express themselves effectively to other health care professionals (23, 88%). Respondents agreed the system was simple to use (23, 96%), and that they could become productive quickly using the system (23, 88%). Overall, 24 (92%) respondents were satisfied or very satisfied with the virtual care platform. Conclusions: We implemented and evaluated a telehealth consultation and collaborative care service between AS providers at multiple centres. AHS has since prioritized similar workflows, including access to specialists in acute care, as part of their virtual health strategy. Evaluation results will be shared with provincial stakeholders for further strategic planning and deployment.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".