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Record W4309862308 · doi:10.1111/jnu.12847

Representations of clinical practice guidelines and health equity in healthcare literature: An integrative review

2022· review· en· W4309862308 on OpenAlexafffundabout
Christina McMillan Boyles, Philippa Spoel, Phyllis Montgomery, Mika Nonoyama, Kyle H. Montgomery

Bibliographic record

VenueJournal of Nursing Scholarship · 2022
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsCambrian CollegeOntario Tech UniversityLaurentian University
FundersLung Health Foundation
KeywordsCINAHLMEDLINEHealth careGrey literatureEquity (law)Context (archaeology)PsycINFOHealth equitySystematic reviewMedicinePsychologyNursingPolitical sciencePsychological interventionPublic health

Abstract

fetched live from OpenAlex

AIM: This paper reports an integrative review of international health literature that discusses health equity in relation to clinical practice guidelines (CPGs). BACKGROUND: Healthcare professionals (HCPs), policy makers, and decision makers rely on sound empirical evidence to make fiscally responsible and appropriate decisions about the allocation of health resources and health service delivery. CPGs provide statements and recommendations that aim to standardize care with an implicit goal of achieving equity of care among diverse populations. Developers of CPGs must be careful not to exacerbate inequity when making recommendations. As such, it is important to determine how equity is discussed within the context of CPGs. DESIGN: This integrative review was conducted according to integrative review methods as outlined by Whittemore and Knafl (2005), and Toronto and Remington (2020). These authors outlined a systematic process for the identification of relevant literature across health disciplines to examine the state of knowledge pertaining to a phenomenon such as health equity. SEARCH METHODS: The computerized databases PubMed, CINAHL, Cochrane, Embase, Medline, and Web of Science were searched using a combination of keywords. Search parameters included international peer-reviewed published, full-text, English language articles, editorials, and reports over the last decade (January 2011 to February 2022). A reference search of included articles was conducted to identify any additional articles. Dissertations and theses were not included. SEARCH OUTCOME: A total of 139 peer-reviewed English language articles were identified. RESULTS: The findings of this review revealed five main ways in which health equity is in context of CPGs including if they target or exacerbate inequity among disadvantaged populations, equity and CPG development, implementation, and evaluation, and checklists and tools to assist developers and users of CPG to consider equity. Although critical appraisal tools exist to assist users of CPGs assess and to evaluate how well CPGs address issues of equity, the definition of equity and how CPG development panels should incorporate and articulate it remains unclear and haphazard. As such, recommendations intended to be implemented by HCPs to optimize health equity remains diverse and unclear. CONCLUSION: The way equity is discussed within the reviewed health literature has implications for their uptake by and utility for HCPs. The ability of HCPs to implement CPGs may be hindered without an appreciation and integration of equity considerations across the various phases of CPG conceptualization, development, implementation, and evaluation, and their relevance and appropriateness to diverse geographic and socioeconomic contexts with variable access to health human resources and services. This situation could be improved if equity were more clearly articulated within all aspects of the CPG process. CLINICAL RELEVANCE: Understanding how equity is discussed in the literature relative to CPGs has implications for their uptake by and utility for HCPs in their goal of providing equitable health care. Successful implementation of CPGs with consideration equity could be improved if equity were more clearly articulated within all aspects of the CPG process including conceptualization, development, implementation, and evaluation.

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)0.053
metaresearch head score (Gemma)0.193
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.947
Threshold uncertainty score0.279

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0530.193
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0340.031
Science and technology studies0.0020.005
Scholarly communication0.0120.016
Open science0.0040.007
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.844
GPT teacher head0.761
Teacher spread0.083 · 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 designNot applicable
DomainEvaluation
GenreReview

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

Citations9
Published2022
Admission routes3
Has abstractyes

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