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Record W2588549329 · doi:10.1093/eurpub/ckt126.075

Facilitators and Barriers to the Application of Health Equity Planning and Assessment Tools

2013· article· en· W2588549329 on OpenAlexaff
HA Amare, IT Tyler, HM Mansonor, Brian Hyndman

Bibliographic record

VenueEuropean Journal of Public Health · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsEquity (law)BusinessEnvironmental planningProcess managementRisk analysis (engineering)Political scienceEnvironmental science

Abstract

fetched live from OpenAlex

Objectives To identify factors that facilitates or hinders the application and evaluation of health equity planning and assessment tools. Methods Published and grey literature from Western jurisdictions was reviewed. Key informants who designed and applied the tools in Canada, Australia and New Zealand were interviewed to share their experiences. Thematic analysis was used to analyze the qualitative data. Results We identified facilitators and barriers to both: 1) the application/use of health equity impact assessment and other health equity planning and assessment tools; as well as 2) the adoption of recommendations coming from the use of the tools. Three levels of facilitators and barriers were identified: system, organizational and operational. System level facilitators included leadership support, mandates to use health equity focused tools, and organizational performance management incentives. Organizational level facilitators included organizational commitment and readiness, and buy-in from top management. Facilitators at the operational level included having a clearly defined approach to the application of these tools, staff training and access to technical support. Involvement of stakeholders and application of the health equity focused tool in the project planning phase facilitated the adoption of recommendations arising from the use of the tool. Operational level barriers included lack of resources, limited capacity within the health care system for this work, subjectivity introduced during the equity analysis, and lack of data and literature on equity outcomes. Evaluation efforts were largely descriptive, focusing on the process of applying the tools, rather than outcomes and impacts. Challenges to evaluation included difficulties in measuring the impact of recommendations arising from the use of the tools and assessing indirect impacts such as increasing awareness of health equity issues and partnership building. Conclusions The application and evaluation of health equity planning and assessment tools could be strengthened by including both process and outcome evaluation, broader adoption of a standardized reporting framework for case studies, and facilitated information sharing. Key messages Three levels of facilitators and barriers were identified for the application of health equity impact assessment tools: system, organizational and operational. Assessment and prioritization of these facilitators and barriers for action will help in wider application of the tools.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.291
metaresearch head score (Gemma)0.571
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.291
Threshold uncertainty score0.875

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2910.571
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.005
Science and technology studies0.0050.006
Scholarly communication0.0130.011
Open science0.0060.017
Research integrity0.0040.012
Insufficient payload (model declined to judge)0.0090.001

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.

Opus teacher head0.186
GPT teacher head0.367
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations5
Published2013
Admission routes1
Has abstractno

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