Impact of a critical care clinical information system on interruption rates during intensive care nurse and physician documentation tasks.
Bibliographic record
Abstract
Computerized documentation methods in Intensive Care Units (ICUs) may assist Health Care Providers (HCP) with their documentation workload, but evaluating impacts remains problematic. A Critical Care clinical Information System (CCIS) is an electronic charting tool designed for ICUs that may fit seamlessly into HCP work. Observers followed ICU nurses and physicians in two ICUs in Edmonton, Canada, in which a CCIS had recently been introduced. Observers recorded amounts of time HCPs spent on documentation related tasks, interruptions encountered by HCPs, and contextual information in field notes. Interruption rates varied depending on the charting medium used, with physicians being interrupted less frequently when performing documentation tasks using the CCIS, than when performing documentation tasks using other methods. In contrast, nurses were interrupted more frequently when charting using the CCIS than when using other methods. Interruption rates coupled with qualitative observations suggest that physicians utilize strategies to avoid interruptions if interfaces for entering textual notes are not well adapted to interruption-rich environments such as ICUs. Potential improvements are discussed such that systems like the CCIS may better integrate into ICU work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".