Healthy Eating Policy for a provincial health authority in Atlantic Canada
Bibliographic record
Abstract
Abstract Issue Poor diets, the global leading cause of death and disability, are influenced by individual and community factors. Community health care settings have the potential to shape dietary behavior through food and beverage environments, and a healthy eating culture that supports the healthier choice as the easier choice. Description of the Problem The Nova Scotia Health Authority (NSHA) is a provincial government health authority in Atlantic Canada, responsible for delivering services to nearly 1 million people in 10 hospitals, 8 ERs, and 135 community locations. The NSHA employs over 23,400 health workers. In 2015, the NSHA centralized its governance, merging 9 regional health districts into one. Policies and procedures were re-written with a provincial focus, including a new Healthy Eating Policy (HEP) adopted in 2018. In this paper, we discuss the implementation of the HEP as a case study for how healthy eating can be fostered through continuous quality improvement. Results The policy upholds NSHA as a community leader working collaboratively with internal and external partners. To be a credible leader in changing the landscape around healthy eating, NSHA agrees to “walk the talk” and model an evidence-based healthy eating policy. A hospital in Halifax piloted pricing, placement and promotion interventions to further support healthier eating. These have been expanded to other sites across NS. Lessons 1) Internal Capacity Building - A Healthy Eating Steering Committee promotes healthy eating across the health system, including initiatives in partnership with auxiliaries, foundations and staff. 2) Improving Evaluation Infrastructure- The interventions led to strategic thinking of future point of sale systems and ways to improve data collection for evaluation 3) Academic Partnerships - NSHA and Dalhousie University formed a collaborative partnership to strengthen evaluation capacity making use of the latest evidence and methods from food environments research. Key messages The Nova Scotia Health Authority’s Health Eating Policy supports healthy eating across the province, and promotes supportive environments where the healthier choice is the easier choice. A hospital site in Halifax, NS, implemented a variety of pricing, placement and promotion interventions to promote a healthy workplace environment for employees and community members.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.003 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".