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Record W2921778868 · doi:10.1097/xeb.0000000000000164

Adapting guidelines to local settings

2019· editorial· en· W2921778868 on OpenAlexaboutno aff
Hanan Khalil

Bibliographic record

VenueInternational Journal of Evidence-Based Healthcare · 2019
Typeeditorial
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
Fundersnot available
KeywordsCredibilityBest practiceEvidence-based practiceQuality (philosophy)Health careAdaptation (eye)UsabilityClinical PracticeProcess managementKnowledge managementMedical educationMedicinePsychologyNursingComputer scienceBusinessPolitical scienceAlternative medicine

Abstract

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Using the best evidence is essential to support quality healthcare and develop valid guidelines for clinical practice to inform evidence-based practice. Clinical practice guidelines are generally developed from synthesized evidence that has been translated into specific practice-oriented recommendations.1 Practice guidelines are used in many settings to reduce variations across clinical practice and to ensure the use of the best available evidence for patient care. Many organizations across the world are adapting existing high-quality guidelines in their own settings to avoid work duplication and enhance applicability. However, little research is done into the best way of adapting clinical practice guidelines into local settings. The challenge in this area is compromising the integrity of the evidence base and the resources required for the implementation of the guidelines.1,2 A few systematic reviews addressed the effectiveness of adaptation models of clinical guidelines into local settings.3–5 Gagliardi et al. developed a framework of guidelines implementation into local settings. The framework consisted of 22 elements organized in the domains of adaptability, usability, validity, applicability, communicability, accommodation, implementation and evaluation. Another review identified the importance of opinion leaders, reminders and feedback to be essential in translating evidence into practice.3 A third review of the literature identifying factors that are important in guidelines implementation in low-income countries found several challenges to translate evidence into practice.4 Some of these barriers included the degree of support from facility management and higher organizations such as the Ministry of Health or similar organizations, credibility and acceptability of clinical guidelines from the viewpoint of healthcare providers and willingness to adapt clinical guidelines to local circumstances.5 Wang et al. identified two main ways to adapt existent guidelines in local settings. These were divided into formal and informal processes. The informal process may include identifying international guidelines on a particular area in the literature, compare them according to the Appraisal of Guidelines Research and Evaluation instrument and then develop a best practice guideline for the local setting. Another example of an informal adaptation is at either a local provider or a patient level, when doctors use international guidelines and apply them in an ad-hoc manner for their local patients. Such an adaptation may not be suitable as it poses the risk of working outside the scope of practice of the practitioners in their countries.7 Another approach of guidelines adaptation is a formal process. This process involves several steps of implementation. Examples of these steps include forming a committee of experts in the field on a particular topic, identifying resources and skills required for the process, devising an adaptation plan, searching for relevant guidelines, formal screening and evaluating the existing guidelines, external reviewing of the adapted guidelines by experts in the field and relevant endorsement bodies and finally scheduling reviews for guidelines updates.7 Several implementation frameworks are described in the literature such as the ADAPTE, the Alberta Ambassador Program adaptation process, CAN-IMPLEMENT, SNAP IT by GRADE MAGIC and Adapted ADAPTE.7,8 They all have four main stages and these are defining the health questions, searching and screening the guidelines, evaluating the guidelines and selecting a single or a set of guideline/s to adapt.7,8 Some of the limitations of the above-mentioned frameworks are the lack of information about the resources, time and cost needed for the implementation of the guidelines. Other limitations are the need for specialized experts in methodologies to be able to evaluate the evidence generated, and a lack of data on their uptake by organizations and patient-related outcomes.6–8 Having a checklist of and procedures on how to implement guidelines into local settings might be one way of enhancing their uptake. Furthermore, dedicating a section in each newly developed guideline on adaptation methods might facilitate their uptake into various and differing settings. Finally, clinical decisions about guideline use and implementation are influenced by the availability and mobilization of organizational or system level resources, which are governed by managers and policy makers who need to meet the competing interests of multiple stakeholders. Guidelines adaptation has been a recent priority of the WHO, and further research is needed into effective ways to adapt high-quality guidelines developed in high-income countries into different settings, especially in low-income countries. Acknowledgements Conflicts of interest The author reports no conflicts of interest.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.134
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.318
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.134
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.527
GPT teacher head0.596
Teacher spread0.069 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

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
Published2019
Admission routes1
Has abstractyes

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