Rate of Healthcare Worker–Patient Interaction and Hand Hygiene Opportunities in an Acute Care Setting
Bibliographic record
Abstract
OBJECTIVE: Identify factors affecting the rate of hand hygiene opportunities in an acute care hospital. DESIGN: Prospective observational study. SETTING: Medical and surgical in-patient units, medical-surgical intensive care unit (MSICU), neonatal intensive care unit (NICU), and emergency department (ED) of an academic acute care hospital from May to August, 2012. PARTICIPANTS: Healthcare workers. METHODS: One-hour patient-based observations measured patient interactions and hand hygiene opportunities as defined by the "Four Moments for Hand Hygiene." Rates of patient interactions and hand hygiene opportunities per patient-hour were calculated, examining variation by room type, healthcare worker type, and time of day. RESULTS: During 257 hours of observation, 948 healthcare worker-patient interactions and 1,605 hand hygiene opportunities were identified. Moments 1, 2, 3, and 4 comprised 42%, 10%, 9%, and 39% of hand hygiene opportunities. Nurses contributed 77% of opportunities, physicians contributed 8%, other healthcare workers contributed 11%, and housekeeping contributed 4%. The mean rate of hand hygiene opportunities per patient-hour was 4.2 for surgical units, 4.5 for medical units, 5.2 for ED, 10.4 for NICU, and 13.2 for MSICU (P < .001). In non-ICU settings, rates of hand hygiene opportunities decreased over the course of the day. Patients with transmission-based precautions had approximately half as many interactions (rate ratio [RR], 0.55 [95% confidence interval (CI), 0.37-0.80]) and hand hygiene opportunities per hour (RR, 0.47 [95% CI, 0.29-0.77]) as did patients without precautions. CONCLUSIONS: Measuring hand hygiene opportunities across clinical settings lays the groundwork for product use-based hand hygiene measurement. Additional work is needed to assess factors affecting rates in other hospitals and health care settings.
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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) | 0.001 | 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 | 0.000 |
| 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".