An external facilitation intervention to increase uptake of an adverse drug event reporting intervention
Bibliographic record
Abstract
Background: Adverse drug events (ADEs) are a leading cause of emergency department visits and hospital admissions in Canada. ActionADE prevents repeat ADEs by enabling clinicians to document and communicate standardized ADE information across care settings. We used an external facilitation intervention to promote the uptake of ActionADE in four hospitals in British Columbia, Canada. This study examined whether, how and in what context external facilitation influenced the uptake of ActionADE. Methods: In this convergent-parallel mixed-methods study, an external facilitator used a four-step iterative process to support site champions using context-specific implementation strategies to increase the ADE reporting rate at their sites. We extracted archival data to assess implementation determinants before and after the implementation of the external facilitation and implementation strategies. We also retrieved data on the mean monthly counts of reported ADEs for each user from the ActionADE server. Zero-inflated Poisson models were used to examine changes in mean monthly counts of reported ADEs per user between pre-intervention (June 2021 to October 2021) and intervention (November 2021 to March 2022) periods. Results: The external facilitator and site champions co-created three functions: (1) educate pharmacists about what and how to report in ActionADE, (2) educate pharmacists about the impact of ActionADE on patient outcomes, and (3) provide social support for pharmacists to integrate ADE reporting into clinical workflows. Site champions used eight forms to address the three functions. Peer support and reporting competition were the two common strategies used by all sites. Sites' responses to external facilitation varied. The rate of mean monthly counts of reported ADEs per user significantly increased during the intervention period compared to the pre-intervention period at LGH (RR: 3.74, 95% CI 2.78 to 5.01) and RH (RR: 1.43, 95% CI 1.23 to 1.94), but did not change at SPH (RR: 0.68, 95% CI: 0.43 to 1.09) and VGH (RR: 1.17, 95% CI 0.92 to 1.49). Leave of absence of the clinical pharmacist champion and failure to address all identified functions were implementation determinants that influenced the effectiveness of external facilitation. Conclusion: External facilitation effectively supported researchers and stakeholders to co-create context-specific implementation strategies. It increased ADE reporting at sites where clinical pharmacist champions were available, and where all functions were addressed.
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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 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".