Impact of Electronic Surveillance on Isolation Practices
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of an electronic surveillance system on isolation practices and rates of methicillin-resistant Staphylococcus aureus (MRSA). DESIGN: A pre-post test intervention. SETTING: Inpatient units (except psychiatry and labor and delivery) in 4 New York City hospitals. PATIENTS: All patients for whom isolation precautions were indicated, May 2009-December 2011. METHODS: Trained observers assessed isolation sign postings, availability of isolation carts, and staff use of personal protective equipment (PPE). Infection rates were obtained from the infection control department. Regression analyses were used to examine the association between the surveillance system, infection prevention practices, and MRSA infection rates. RESULTS: A total of 54,159 isolation days and 7,628 staff opportunities for donning PPE were observed over a 31-month period. Odds of having an appropriate sign posted were significantly higher after intervention than before intervention (odds ratio [OR], 1.10 [95% confidence interval {CI}, 1.01-1.20]). Relative to baseline, postintervention sign posting improved significantly for airborne and droplet precautions but not for contact precautions. Sign posting improved for vancomycin-resistant enterococci (OR, 1.51 [95% CI, 1.23-1.86]; [Formula: see text]), Clostridium difficile (OR, 1.59 [95% CI, 1.27-2.02]; [Formula: see text]), and Acinetobacter baumannii (OR, 1.41 [95% CI, 1.21-1.64]; [Formula: see text]) precautions but not for MRSA precautions (OR, 1.11 [95% CI, 0.89-1.39]; [Formula: see text]). Staff and visitor adherence to PPE remained low throughout the study but improved from 29.1% to 37.0% after the intervention (OR, 1.14 [95% CI, 1.01-1.29]). MRSA infection rates were not significantly different after the intervention. CONCLUSIONS: An electronic surveillance system resulted in small but statistically significant improvements in isolation practices but no reductions in infection rates over the short term. Such innovations likely require considerable uptake time.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| 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".