Saying and doing are different things: a scoping review on how health equity is conceptualized when considering healthcare system performance
Bibliographic record
Abstract
INTRODUCTION: Ensuring healthcare systems provide equitable, high quality care is critical to their users' overall health and wellbeing. Typically, systems use various performance frameworks and related indicators to monitor and improve healthcare. Although these frameworks usually include equity, the extent that equity is reflected in these measurements remains unclear. In order to create a system that meets patients' needs, addressing this uncertainty is important. This paper presents findings from a scoping review that sought to answer the question 'How is equity conceptualized in healthcare systems when assessing healthcare system performance?'. METHODS: Levac's scoping review approach was used to locate relevant articles and create a protocol. Included, peer-reviewed articles were published between 2015 to 2020, written in English and did not discuss oral health and clinician training. These healthcare areas were excluded as they represent large, specialized bodies of literature beyond the scope of this review. Online databases (e.g., MEDLINE, CINAHL Plus) were used to locate articles. RESULTS: Eight thousand six hundred fifty-five potentially relevant articles were identified. Fifty-four were selected for full review. The review yielded 16 relevant articles. Six articles emanated from North America, six from Europe and one each from Africa, Australia, China and India respectively. Most articles used quantitative methods and examined various aspects of healthcare. Studies centered on: indicators; equity policies; evaluating the equitability of healthcare systems; creating and/or testing equity tools; and using patients' sociodemographic characteristics to examine healthcare system performance. CONCLUSION: Although equity is framed as an important component of most healthcare systems' performance frameworks, the scarcity of relevant articles indicate otherwise. This scarcity may point to challenges systems face when moving from conceptualizing to measuring equity. Additionally, it may indicate the limited attention systems place on effectively incorporating equity into performance frameworks. The disjointed and varied approaches to conceptualizing equity noted in relevant articles make it difficult to conduct comparative analyses of these frameworks. Further, these frameworks' strong focus on users' social determinants of health does not offer a robust view of performance. More work is needed to shift these narrow views of equity towards frameworks that analyze healthcare systems and not their users.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".