Applying a Health Equity Promotion Lens to Prenatal Care for Inner-City Families in Winnipeg, Canada
Bibliographic record
Abstract
Issue/Problem Despite a history of social justice policies, substantial inequities persist, by georgraphy, in Canada. For example, life expectancy of a child born in the inner-city of Winnipeg, Canada is nineteen years less that of a child born in suburban areas. Thus, health equity promotion is a strategic priority of the Public Health team in Winnipeg with the prenatal period being identified as an opportune time to address health inequities. Description The objective of the Partners in Inner-City Integrated Prenatal Care (PIIPC) project is to improve access to, and use of, prenatal care (PNC) services within inner-city Winnipeg. PIIPC is an example of applying concepts of health equity promotion to transform health systems to better meet the needs of those who experience social and economic disadvantage. The PIIPC project is a collaboration between health providers, researchers, government representatives, and First Nations partners. PIIPC was implemented in Fall, 2012, and consists of four inter-related initiatives. Evaluation of the project uses a mixed methods approach to obtain qualitative input from women and their health care providers including; a questionnaire, chart review, and a “before and after” population level assessment of rates of inadequate PNC. Results Results indicate that the PIIPC approach has improved access to and use of prenatal care for women in the inner-city. Women describe the services as helpful, respectful and non-judgmental, while providers value improved communication and the team approach. Rather than expecting women and families who experience disadvantage to adapt to the health system, the project demonstrates how a health system can adapt to become more accessible and effective for families. Lessons An integrated knowledge translation approach contributed to development of an evidence-informed health system improvement with a robust evaluation plan. Our findings suggest that focused attempts to address health inequities have the potential to lead to health improvements at the individual and population level. Key messages The prenatal period is an opportune time to improve the health of disadvantaged families The PIIPC project demonstrates health equity promotion in action. Preliminary results are promising
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.007 |
| Scholarly communication | 0.007 | 0.001 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".