Impact of a Sleep-Promoting Schedule on Sleep Quality in the Intensive Care Unit
Bibliographic record
Abstract
BACKGROUND: Hospitalized patients often experience sleep disruption that fragments their sleep and disturbs their circadian rhythms, putting them at risk for sleep deprivation. The risk increases with greater severity of illness and is especially high in intensive care unit patients. Sleep deprivation can prolong the intensive care unit stay, contribute to emotional and physiological distress, and even increase the patient's risk of death. LOCAL PROBLEM: Critical care nurses in a 28-bed medical intensive care unit reported that patients often complained of sleep disruption or exhibited emotional and physical distress resulting from sleep deprivation. An analysis of the gap between recommended evidence-based best practice and current practices in the unit revealed numerous opportunities to improve patients' sleep. The aim of this evidence-based quality improvement project was to increase interprofessional adherence to an existing sleep-promoting schedule to reduce avoidable interruptions and improve patient sleep quality. METHODS: To promote sleep, staff member interactions with patients between midnight and 4 am were minimized, if appropriate. Documented patient encounters and call bell initiation were evaluated as process measures. Patients' self-perceived sleep quality, an outcome measure, was evaluated using the Richards-Campbell Sleep Questionnaire. RESULTS: Adherence to a sleep-promoting schedule reduced patient sleep interruptions between midnight and 4 am by as much as two-thirds while increasing patients' overall self-perceived sleep quality by 6.7 percentage points. CONCLUSION: An interprofessional effort to minimize patient interruptions at night in an intensive care unit setting led to improved patient sleep quality and sustainable practice changes.
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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 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".