Impact of a Comprehensive Safety Initiative on Patient-controlled Analgesia Errors
Bibliographic record
Abstract
BACKGROUND: Adverse drug events related to patient-controlled analgesia (PCA) place patients at risk. METHODS: We reviewed all critical incident reports at three tertiary care hospitals dated January 1, 2002, to February 28, 2009. In this longitudinal cohort study, critical incidents attributable to PCA errors were identified, and each incident was investigated. A safety intervention was implemented in February 2006 and involved new PCA pumps, new preprinted physician orders, nursing and patient education, a manual independent double-check, and a formal nursing transfer of accountability. RESULTS: A total of 25,198 patients were treated with PCA during this study, and 62 errors were found (0.25%), with 21 (0.08%) involving pump programming. All errors occurred before the safety interventions were put in place. Compared with the preintervention period, the odds ratio of a PCA error postintervention was 0.28 (95% CI = 0.14, 0.53; P < 0.001) whereas the odds ratio of a pump-programming error postintervention was 0.05 (95% CI = 0.001, 0.30; P < 0.001). Programming the wrong drug concentration was the most common programming error (10 of 21). Improper setup of intravenous tubing was also common (8 of 62), with one incident leading to respiratory arrest. Most PCA errors resulted in no harm, but there was negative impact to patients 34% of the time. CONCLUSION: At less than 1%, the incidence of PCA errors is relatively low. Most errors occur during PCA administration. Safety can be improved by addressing equipment, education, and process issues.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".