Work Interruptions and Their Contribution to Medication Administration Errors: An Evidence Review
Bibliographic record
Abstract
BACKGROUND: In many surveys, nurses cite work interruptions as a significant contributor to medication administration errors. OBJECTIVES: To review the evidence on (1) nurses' interruption rates, (2) characteristics of such work interruptions, and (3) contribution of work interruptions to medication administration errors. SEARCH STRATEGY: CINHAL (1982-2008), MEDLINE (1980-2008), EMBASE (1980-2008), and PSYCINFO (1980-2008) were searched using a combination of keywords and reference lists. SELECTION CRITERIA: Original studies published in English using nurses as participants and for which work interruption frequencies are reported. DATA COLLECTION AND ANALYSIS: Studies were identified and selected by two reviewers. Once selected, a single reviewer extracted data and assessed quality based on established criteria. Data on nurses' work interruption rates were synthesized to produce a pooled estimate. RESULTS: Twenty-three studies were considered for analysis. A rate of 6.7 work interruptions per hour was obtained, based on 14 studies that reported both an observation time and work interruption frequency. Work interruptions are mostly initiated by nurses themselves through face-to-face interactions and are of short duration. A lower proportion of interruptions resulted from work system failures such as missing medication. One nonexperimental study documented the contribution of work interruptions to medication administration errors with evidence of a significant association (p = 0.01) when errors related to time of administration are excluded from the analysis. Conceptual shortcomings were noted in a majority of reviewed studies, which included the absence of theoretical underpinnings and a diversity of definitions of work interruptions. CONCLUSIONS: Future studies should demonstrate improved methodological rigor through a precise definition of work interruptions and reliability reporting to document work interruption characteristics and their potential contribution to medication administration errors, considering the limited evidence found. Meanwhile, efforts should be made to reduce the number of work interruptions experienced by nurses.
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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 | 0.016 | 0.082 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.017 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".