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Record W4387193733 · doi:10.1017/ash.2023.319

Measuring hand hygiene opportunities per hour across two neonatal intensive care units

2023· article· en· W4387193733 on OpenAlexaboutno aff
Eugene Lee, Souad Al-Muthree, Paige Reason, Meghan Rose Donohue, Michael Dunn, Meghan Statchuk, Sarah Khan, Shikha Gupta, Salhab el Helou, Jerome A. Leis, Dominik Mertz

Bibliographic record

VenueAntimicrobial Stewardship & Healthcare Epidemiology · 2023
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsIncubatorHygieneMedicineAuditNeonatal intensive care unitPediatricsEmergency medicine

Abstract

fetched live from OpenAlex

Background: To estimate hand hygiene compliance using electronic hand hygiene monitoring, the number of hand hygiene opportunities (HHOs) per period must be known in a given setting. Data on the number of HHOs in a neonatal ICU (NICU) are limited. We measured HHOs per hour and identified factors that may influence the number of HHOs per hour to calibrate compliance estimates for electronic hand hygiene monitoring. Methods: The study was conducted in 2 large NICUs in Ontario, Canada (72 and 42 beds, respectively). We centrally trained observers to identify HHOs using the Ontario-based “Four Moments of Hand Hygiene,” which is similar to combining moments 4 and 5 of the WHO “Five Moments of Hand Hygiene.” To apply the moments of hand hygiene to the NICU setting, the following modifications were made: moment 1 was entering the incubator or contact with anything within the ‘baby space’ directly around the incubator, and moment 4 was when hands exited the incubator and, as such, the ‘baby space.’ Using a standardized tool, the investigators conducted direct observation of HHOs during randomized observation periods from July 1, 2022, to January 9, 2023. In addition to HHOs, data on covariables potentially associated with the frequency of HHOs were collected: time and day of the week, acuity, additional precautions, corrected gestational age, and private versus multibed room or open pod. Results: We audited HHOs for 146 hours including 26 at site A and 120 at site B. Overall, 804 HHOs (69.2%) occurred during weekdays and 739 (63.6%) occurred during day shifts from 7:00 a.m. to7:00 p.m. The most frequent moments of hand hygiene were moment 1 (47.8%, before contact) and moment 4 (36.8%, after contact). The average numbers of HHOs were 7.8 per hour overall, 7.6 per hour on weekdays, 7.7 per hour on weekends, 8.8 per hour on day shifts, and 6.8 per hour on night shifts. The breakdown of HHOs by profession was 92.8% nurses, 0.6% physicians, 4.5% allied health, and 2.1% for others. Discussion: The rate of HHOs in NICU varied over a 24-hour period and was similar between 2 different NICUs. Evenings and weekends had considerably fewer average HHOs, and peaks were observed following nursing shift changes. The rate of HHOs may be influenced by other factors including unit design, patient acuity, and use of transmission-based precautions. Further analysis using a Poisson regression model will help to explore these factors and to calibrate electronic monitoring for this population. Disclosures: None

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.139
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.236
GPT teacher head0.399
Teacher spread0.163 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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