Barriers and facilitators to evidence-use in program management: a systematic review of the literature
Bibliographic record
Abstract
BACKGROUND: The use of evidence in decision-making at the program management level is a priority in health care organizations. The objective of this study was to identify potential barriers and facilitators experienced by managers to the use of evidence in program management within health care organizations. METHODS: The authors conducted a comprehensive search for published, peer-reviewed and grey literature that explores the use of evidence in program management. Two reviewers selected relevant studies from which data was extracted using a standard data abstraction form and tabulated for qualitative analysis. The results were summarized through narrative review. The quality of the included studies was assessed using published criteria for the critical appraisal of qualitative, quantitative and mixed methods research. RESULTS: Fourteen papers were included in the review. Barriers and facilitators were categorized into five main thematic areas: (1) Information, (2) Organization--Structure and Process, (3) Organization--Culture, (4) Individual, and (5) Interaction. CONCLUSION: This paper reviews the literature on barriers and facilitators to evidence-informed decision-making experienced by program management decision-makers within health care organizations. The multidimensional solutions required to promote evidence-informed program management can be developed through an understanding of the existing barriers and facilitators of evidence-use.
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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 | 0.079 | 0.249 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.019 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".