Educational outreach visits: effects on professional practice and health care outcomes
Bibliographic record
Abstract
BACKGROUND: Educational outreach visits (EOVs) have been identified as an intervention that may improve the practice of healthcare professionals. This type of face-to-face visit has been referred to as university-based educational detailing, academic detailing, and educational visiting. OBJECTIVES: To assess the effects of EOVs on health professional practice or patient outcomes. SEARCH STRATEGY: For this update, we searched the Cochrane EPOC register to March 2007. In the original review, we searched multiple bibliographic databases including MEDLINE and CINAHL. SELECTION CRITERIA: Randomised trials of EOVs that reported an objective measure of professional performance or healthcare outcomes. An EOV was defined as a personal visit by a trained person to healthcare professionals in their own settings. DATA COLLECTION AND ANALYSIS: Two reviewers independently extracted data and assessed study quality. We used bubble plots and box plots to visually inspect the data. We conducted both quantitative and qualitative analyses. We used meta-regression to examine potential sources of heterogeneity determined a priori. We hypothesised eight factors to explain variation across effect estimates. In our primary visual and statistical analyses, we included only studies with dichotomous outcomes, with baseline data and with low or moderate risk of bias, in which the intervention included an EOV and was compared to no intervention. MAIN RESULTS: We included 69 studies involving more than 15,000 health professionals. Twenty-eight studies (34 comparisons) contributed to the calculation of the median and interquartile range for the main comparison. The median adjusted risk difference (RD) in compliance with desired practice was 5.6% (interquartile range 3.0% to 9.0%). The adjusted RDs were highly consistent for prescribing (median 4.8%, interquartile range 3.0% to 6.5% for 17 comparisons), but varied for other types of professional performance (median 6.0%, interquartile range 3.6% to 16.0% for 17 comparisons). Meta-regression was limited by the large number of potential explanatory factors (eight) with only 31 comparisons, and did not provide any compelling explanations for the observed variation in adjusted RDs. There were 18 comparisons with continuous outcomes, with a median adjusted relative improvement of 21% (interquartile range 11% to 41%). There were eight trials (12 comparisons) in which the intervention included an EOV and was compared to another type of intervention, usually audit and feedback. Interventions that included EOVs appeared to be slightly superior to audit and feedback. Only six studies evaluated different types of visits in head-to-head comparisons. When individual visits were compared to group visits (three trials), the results were mixed. AUTHORS' CONCLUSIONS: EOVs alone or when combined with other interventions have effects on prescribing that are relatively consistent and small, but potentially important. Their effects on other types of professional performance vary from small to modest improvements, and it is not possible from this review to explain that variation.
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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 | 0.018 | 0.099 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".