Closing the indigenous health gap in Canada: Results from the TransFORmation of IndiGEnous PrimAry HEAlthcare delivery (FORGE AHEAD) program
Bibliographic record
Abstract
AIMS: TransFORmation of IndiGEnous PrimAry HEAlthcare Delivery (FORGE AHEAD) partnered with local clinical and community teams in 11 First Nations (FN) communities across Canada to develop quality improvement (QI) initiatives aimed at improving T2DM. METHODS: Pre-post mixed-methods case study design was used. The 18-month intervention included community and clinical readiness, development of a community diabetes registry and clinical system, and QI activities. Participants consisted of community members, 18 yrs and older, with diabetes. Changes in clinical outcomes and clinical practice guideline (CPG) recommendations were assessed pre and post intervention using multilevel regression (patients nested within communities) adjusted forindividual andcommunity baseline characteristics. RESULTS: No significant change in HbA1c orsBP, but a small reduction indBP(-0.75 mmHg, p < 0.05) and LDL (-0.09 mmol/L, p < 0.05) was observed in 2008 adults with T2DM (mean age: 60·5 (SD:14·6) years; female: 57·2%). Individuals not at CPG targets at baseline had significant reductions in: %HbA1c (N = 616): -0.40 (95%CI:-0·55,-0·24),sBP (N = 561): -7·67 mmHg (95%CI:-9·23, -5·72),dBP (N = 291): -7·46 mmHg (95%CI:-8·69, -6·26), LDL (N = 450): -0·37mmo/l (95%CI:-0·44, -0·29).Annual HbA1c (OR: 1·95; 95%CI:1·66, 2·29), BP (OR: 1·78; 95%CI:1·52, 2·09), LDL (OR: 1·27; 95%CI:1·10, 1·47) and CKD screening (OR: 6·37; 95%CI:5·16, 7·92)increased but retinopathy screening decreased (OR: 0·68; 95%CI:0·57, 0·82). No significant change in foot exams (OR: 0·97; 95%CI:0·76, 1·23) or BMI recordings (OR: 0·96; 95%CI:0·82, 1·12) was seen. Overall, individualsweremorelikely to receive ≥75% of CPG recommended services compared to baseline (OR: 1·51; 95%CI:1·27, 1·80). CONCLUSIONS: FORGE AHEAD is the first Canadian study to demonstrate that a FN community-led QI intervention can lead to diabetes improvements.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".