Improving incident reporting among physicians at south health campus hospital
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Reports of adverse events and near-misses provide the opportunity to learn about latent (systems) errors. However, voluntary incident reporting systems are underused by physicians. While reports submitted by nursing staff relate to common hazards such as medication administration or falls, physicians have broader exposure to patients' entire hospital journey. Reports by physicians have the potential to uncover more serious errors that could span multiple departments and layers of personnel. Organisational safety culture thrives when all staff are represented and feel empowered to share safety concerns.At the South Health Campus (SHC) Hospital in Calgary, Alberta, Canada, the baseline proportion of physician-submitted reports within our site's Reporting and Learning System (RLS) from July 2013 to December 2016 was 1.12%. We implemented an intervention to double the proportion of physician-submitted RLS reports, using quality improvement methods.Focus groups identified lack of experience with the RLS system, lack of feedback or closure after an RLS submission, and apprehensions about disclosing the incident to the affected patient as barriers to physician submission. Accordingly, the intervention involved direct responses from physician leadership to each physician-submitted RLS report, multimedia demonstrations of efficient RLS submission to physician groups and medical learners, and linkage to materials on safe disclosures. Effectiveness was assessed using a controlled before-and-after design, comparing SHC with the rest of Calgary and with the rest of Alberta.Following the intervention, the proportion of RLS reports that were physician submitted increased to 2.65% (OR 2.42 [95% CI 1.96 to 3.02], p<0.001), sustained over the following 4 years. While an increase was observed for the rest of Calgary, it was smaller (OR 1.27 [1.15 to 1.40], p<0.001). A decrease in the odds of physician submission was observed for the rest of Alberta. Differences between sites were significant (p<0.001).Overall, we found that physician-submitted incident reports can be increased and sustained over time if submitters receive personalised feedback by a physician safety leader. At our site, reports submitted by physicians have been valuable in uncovering complex systems issues that may not have been readily apparent.
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Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Reporting · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | low |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it