Implementation Strategies for Knowledge Products in Primary Health Care: Systematic Review of Systematic Reviews
Bibliographic record
Abstract
BACKGROUND: The underuse or overuse of knowledge products leads to waste in health care, and primary care is no exception. OBJECTIVE: This study aimed to characterize which knowledge products are frequently implemented, the implementation strategies used in primary care, and the implementation outcomes that are measured. METHODS: We performed a systematic review (SR) of SRs using the Cochrane systematic approach to include eligible SRs. The inclusion criteria were any primary care contexts, health care professionals and patients, any Effective Practice and Organization of Care implementation strategies of specified knowledge products, any comparators, and any implementation outcomes based on the Proctor framework. We searched the MEDLINE, EMBASE, CINAHL, Ovid PsycINFO, Web of Science, and Cochrane Library databases from their inception to October 2019 without any restrictions. We searched the references of the included SRs. Pairs of reviewers independently performed selection, data extraction, and methodological quality assessment by using A Measurement Tool to Assess Systematic Reviews 2. Data extraction was informed by the Effective Practice and Organization of Care taxonomy for implementation strategies and the Proctor framework for implementation outcomes. We performed a descriptive analysis and summarized the results by using a narrative synthesis. RESULTS: Of the 11,101 records identified, 81 (0.73%) SRs were included. Of these 81, a total of 47 (58%) SRs involved health care professionals alone. Moreover, 15 SRs had a high or moderate methodological quality. Most of them addressed 1 type of knowledge product (56/81, 69%), common clinical practice guidelines (26/56, 46%) or management, and behavioral or pharmacological health interventions (24/56, 43%). Mixed strategies were used for implementation (67/81, 83%), predominantly education-based (meetings in 60/81, 74%; materials distribution in 59/81, 73%; and academic detailing in 45/81, 56%), reminder (53/81, 36%), and audit and feedback (40/81, 49%) strategies. Education meetings (P=.13) and academic detailing (P=.11) seemed to be used more when the population was composed of health care professionals alone. Improvements in the adoption of knowledge products were the most commonly measured outcome (72/81, 89%). The evidence level was reported in 12% (10/81) of SRs on 62 outcomes (including 48 improvements in adoption), of which 16 (26%) outcomes were of moderate or high level. CONCLUSIONS: Clinical practice guidelines and management and behavioral or pharmacological health interventions are the most commonly implemented knowledge products and are implemented through the mixed use of educational, reminder, and audit and feedback strategies. There is a need for a strong methodology for the SR of randomized controlled trials to explore their effectiveness and the entire cascade of implementation outcomes.
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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 | 0.091 | 0.309 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.013 |
| Bibliometrics | 0.027 | 0.028 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".