Turning the Social Determinants of Health to Our Advantage: Policy Fundamentals for a Better Approach to Children's Health
Bibliographic record
Abstract
Turning the Social Determinants of Health to Our Advantage Role of Policy in Reframing Our Approach to Child HealthThe first two articles in this volume provide a compelling case for improving child health and for the critical role to be played by social determinants.The goal of this article is more prosaic: to lay out the policy approaches that can support the case for improving child health by improving the social determinants of health.But first, it's important to define what we mean by policy.Policy is often used as a synonym for anything that government does, and it can cover election platform commitments, capital investments, new legislation and the written and unwritten practices of bureaucrats as they administer government programs.However, this is too broad a definition of policy to address in a single article or even an entire edition of Healthcare Quarterly.Instead, we will work with a more traditional definition of policy -a standing or consistent position on repeated decisions.This means that policy takes the form of frameworks, that is, the conceptual models that decision-makers use when approaching any relevant problem.In this sense, a policy functions as a sort of checklist covering the set of factors that need to be addressed in any decision on how to improve child health.There are several reasons for this more narrow focus, including the current economic situation, the focus across the country on broader policy questions around access to safe care and difficulties in deciding how to balance programs that favour one population group (e.g., children) against another (e.g., the elderly).The most important reason for the more narrow focus is the fact -already well described by Halfon et al. in this issue -that improving the social determinants of children's health requires joined-up action across government.This in turn requires decision-makers across the health and social services ministries, agencies and providers to approach their policy decisions in a consistent way that supports improvements in the determinants of health for children.This is not the usual approach in parliamentary democracies, or in the health system itself.After more than a century focused on sanitation, nutrition and acute, intermittent infectious disease, contemporary Canadian child health systems are now heavily invested in caring for complex medically fragile children with multiple health needs.Technological innovations enabling the survival of newborns at earlier gestational ages mean that the largest share of child health expenditures in Ontario -and likely Canada -focuses on children under one month old.Bringing a more comprehensive, joined-up approach to child health policy deserves the focus of an entire article. Reframing a Policy Approach to Child HealthAn innovative concept called population health inheritance (PHI) enables reframing of complex child health questions.PHI focuses on policies improving the societal asset of health passed from adults to children in two forms: direct PHI, each generation's collective resiliency, lifespan and quality of life; and indirect PHI, the health system as a sustainable asset, in and of itself, and its capacity to meet enduring population health needs.This inter-generational frame enables us to consider the importance of child health outcomes within the context of a health system that overwhelmingly treats people much later in life and considers health improvement in the context of individuals rather than collectively, as passed between generations.Critical to the notion of direct PHI is the life course approach.Strategies based on this approach reflect an understanding that a person's developmental trajectory can be substantially altered and improved based on factors present during pregnancy and early parenthood (Ben-Shlomo and Kuh 2002).As such, research using this framework tends to emphasize parenting education, an enriched preschool environment and various interventions for mothers and infants.Similarly, critical to indirect PHI are transitions out of the child or youth health system and into the adult health system.Thanks to the progress and success of medicine, children who would have died in infancy or adolescence from a range of health problems now survive into adulthood but enter into an adult healthcare system that is poorly prepared to deal with challenges that, in many cases, are entirely new to this system.Almost by definition, a focus on PHI, the life course approach and transitions requires policy approaches that both recognize Photo credit: istockphoto
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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 | 0.020 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.017 | 0.022 |
| Insufficient payload (model declined to judge) | 0.012 | 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".