Examining the implementation of clinical practice guidelines for the management of adult cancers: A mixed methods study
Bibliographic record
Abstract
RATIONALE, AIMS, AND OBJECTIVES: Focusing on the implementation of clinical practice guidelines (CPGs) for the management of adult cancers, the objectives of this study were to (a) describe the intrinsic elements known to influence CPG use; (b) identify the ways in which CPGs are implemented; and (c) explore how CPG characteristics and contextual factors influence implementation and use. METHODS: We conducted a sequential mixed methods study. First, we performed a content analysis of all CPGs developed and approved for the management of adult cancers in Nova Scotia, Canada, from 2005 to 2015. CPGs were examined for the presence of 22 elements known to influence CPG use. Next, we conducted semistructured interviews with CPG developers and end users. Participants were purposively sampled, based on the findings of the content analysis. All interviews were audiotaped and transcribed verbatim. Data were analysed by two researchers using the Framework Method. RESULTS: CPGs (n = 20) demonstrated large variation with respect to elements shown to influence CPG use. For example, 85% included content related to individualization and objectives. Yet no CPGs (0%) had journal or patient versions; discussed the education, training, or competencies needed to deliver recommendations; contained an explicit statement on anticipated work changes, or on potential direct or productivity costs; or identified barriers or facilitators that might influence CPG adoption. Interview data from CPG developers (n = 4) and users (n = 6) revealed five themes related to CPG implementation and use: (a) lack of consistency in CPG development; (b) timing and nature of stakeholder engagement; (c) credibility of the CPG development process and final CPGs; (d) limited understanding of implementation as an active process; and (e) factors at organizational and system levels influence CPG implementation and use. CONCLUSIONS: This mixed methods study provides complementary data that may help inform more effective CPG implementation efforts and optimize their use in practice.
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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 | 0.080 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".