Methods of a multi-faceted rapid knowledge synthesis project to inform the implementation of a new health service model: Collaborative Emergency Centres
Bibliographic record
Abstract
BACKGROUND: The aim of this rapid knowledge synthesis was to provide relevant research evidence to inform the implementation of a new health service in Nova Scotia, Canada: Collaborative Emergency Centres (CECs). CECs propose to deliver both primary and urgent care to rural populations where traditional delivery is a challenge. This paper reports on the methods used in a rapid knowledge synthesis project to provide timely evidence to policy makers about this novel healthcare delivery model. METHODS: We used a variety of methods, including a jurisdictional/scoping review, modified systematic review methodologies, and integrated knowledge translation. We scanned publicly available information about similar centres across our country to identify important components of CECs and CEC-type models to operationalize the definition of a CEC. We conducted literature searches in PubMed, CINAHL, and EMBASE, and in the grey literature, to identify evidence on the key structures and processes and effectiveness of CEC-type models of care delivery. Our searches were limited to published systematic reviews. The research team facilitated two integrated knowledge translation workshops during the project to engage stakeholders, to refine the research goals and objectives, and to share interim and final results. Citations and included articles were categorized by whether they addressed the CEC model or component structures and processes. Data and key messages were extracted from these reviews to inform implementation. RESULTS: CEC-type models have limited peer-reviewed evidence available; no peer-reviewed studies on CECs as a standalone healthcare model were found. As a result, our evidence search and synthesis was revised to focus on core CEC-type structures and processes, prioritized through consensus methods with the stakeholder group, and resulted in provision of a meaningful evidence synthesis to help inform the development and implementation of CECs in Nova Scotia. CONCLUSIONS: A variety of methods and partnership with decision-makers and stakeholders enabled the project to address the limitations in the evidence regarding CECs and meet the challenge of identifying the best available evidence in a transparent way to meet the needs of decision-makers in a short timeframe.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Metaresearch Domain: Methods · Genre: Methods About the Canadian research system: no · About a Canadian topic: no | Systematic review | medium |
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 | 0.057 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.001 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".