Defining and classifying public health systems: a critical interpretive synthesis
Bibliographic record
Abstract
BACKGROUND: The introduction of the determinants of health has caused a shift towards understanding health from a holistic perspective as well as increased recognition of public health's contributions to the health of the population. Several frameworks exist to conceptualise healthcare systems, highlighting the stark contrast of frameworks unique to public health systems. The objectives of this study were to define public health systems and assess differences between healthcare systems and public health systems within established health systems frameworks. METHODS: A critical interpretive synthesis was conducted. Databases searched included EBSCOhost, OVID, Scholars Portal, Web of Science, Cochrane Library and Health Systems Evidence. Data extraction, coding and analysis followed a best-fit framework analysis method. Initial codes were based on a current leading health systems and policy classification scheme - health systems arrangements (governance, financial and delivery arrangements). RESULTS: A total of 5933 unique documents were identified and 67 were included in the analysis. Definitions of public health and public health systems varied significantly as did their roles and functions across jurisdictions. Public health systems arrangements generally followed those of health systems, with the addition of partnerships (community and inter-sectoral) and communication playing a larger role in public health. A public health systems framework and conceptualisation of how public health currently fits within health systems are presented. CONCLUSIONS: Public health systems are unique and vital entities within health systems. In addition to examining how public health and public health systems have been defined within the literature, this review suggests that establishing the scope of public health is crucial to understanding its role within the larger health system and adds to the discourse around the relationship between public health, healthcare and population health. More broadly, this study addresses an important gap in understanding public health systems and provides conceptual and practical contributions as well as areas for future research.
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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 | Qualitative | low |
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
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 | 0.280 | 0.349 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.054 | 0.036 |
| Science and technology studies | 0.009 | 0.025 |
| Scholarly communication | 0.027 | 0.026 |
| Open science | 0.008 | 0.014 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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, 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".