EQUIP Healthcare: An overview of a multi-component intervention to enhance equity-oriented care in primary health care settings
Bibliographic record
Abstract
BACKGROUND: The primary health care (PHC) sector is increasingly relevant as a site for population health interventions, particularly in relation to marginalized groups, where the greatest gains in health status can be achieved. The purpose of this paper is to provide an overview of an innovative multi-component, organizational-level intervention designed to enhance the capacity of PHC clinics to provide equity-oriented care, particularly for marginalized populations. The intervention, known as EQUIP, is being implemented in Canada in four diverse PHC clinics serving populations who are impacted by structural inequities. These PHC clinics serve as case studies for the implementation and evaluation of the EQUIP intervention. We discuss the evidence and theory that provide the basis for the intervention, describe the intervention components, and discuss the methods used to evaluate the implementation and impact of the intervention in diverse contexts. DESIGN AND METHODS: Research and theory related to equity-oriented care, and complexity theory, are central to the design of the EQUIP intervention. The intervention aims to enhance capacity for equity-oriented care at the staff level, and at the organizational level (i.e., policy and operations) and is novel in its dual focus on: (a) Staff education: using standardized educational models and integration strategies to enhance staff knowledge, attitudes and practices related to equity-oriented care in general, and cultural safety, and trauma- and violence-informed care in particular, and; (b) Organizational integration and tailoring: using a participatory approach, practice facilitation, and catalyst grants to foster shifts in organizational structures, practices and policies to enhance the capacity to deliver equity-oriented care, improve processes of care, and shift key client outcomes. Using a mixed methods, multiple case-study design, we are examining the impact of the intervention in enhancing staff knowledge, attitudes and practices; improving processes of care; shifting organizational policies and structures; and improving selected client outcomes. DISCUSSION: The multiple case study design provides an ideal opportunity to study the contextual factors shaping the implementation, uptake and impact of our tailored intervention within diverse PHC settings. The EQUIP intervention illustrates the complexities involved in enhancing the PHC sector's capacity to provide equity-oriented care in real world clinical contexts.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".