The Effects of Interruptions on Oncologists′ Patient Assessment and Medication Ordering Practices
Bibliographic record
Abstract
Interruptions are causal factors in medication errors. Although researchers have assessed the nature and frequency of interruptions during medication administration, there has been little focus on understanding their effects during medication ordering. The goal of this research was to examine the nature, frequency, and impact of interruptions on oncologists' ordering practices. Direct observations were conducted at a Canadian cancer treatment facility to (1) document the nature, frequency, and timing of interruptions during medication ordering, and (2) quantify the use of coping mechanisms by oncologists. On average, oncologists were interrupted 17 % of their time, and were frequently interrupted during safety-critical stages of medication ordering. When confronted with interruptions, oncologists engaged/multitasked more often than resorting to deferring/blocking. While some interruptions are necessary forms of communication, efforts must be made to reduce unnecessary interruptions during safety-critical tasks, and to develop interventions that increase oncologists' resiliency to inevitable interruptions.
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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 | 0.004 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".