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Record W3096063348 · doi:10.1017/ice.2020.1170

Point of Care Stations: A Novel Way to Improve Stethoscope Hygiene

2020· article· en· W3096063348 on OpenAlexaffabout
Kimberly Gibbens, Susy Hota, Peter H. Seidelin, Carly Rebelo, Kathleen Ross, A Vaisman

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2020
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsStethoscopeHygieneMedicineHand sanitizerInfection controlIntervention (counseling)Medical emergencyHealth careEmergency medicineEnvironmental healthNursingIntensive care medicinePathology

Abstract

fetched live from OpenAlex

Background: Stethoscopes are known to be highly contaminated by a multitude of bacteria and therefore carry the potential to transmit pathogens within hospitals. North American infection prevention groups recommend low-level disinfection of stethoscopes for bioburden reduction between patients; however, adherence remains low in inpatient settings. Given that the lack of access to disinfection materials is the most commonly reported barrier to stethoscope hygiene, we studied an intervention using a point-of-care approach to increase stethoscope hygiene compliance among healthcare workers in critical care units. Methods: This quality improvement study was conducted in 2 critical-care units of a quaternary-care, academic, health sciences center in Toronto, Canada. We designed novel stethoscope hygiene stations consisting of a wall-mounted board with alcohol wipes, hooks for drying, and hand sanitizer dispensers to combine stethoscope and hand hygiene. Observations of stethoscope disinfection events per opportunity were collected by trained human auditors before and after the multimodal intervention, which consisted of the installation of 14 stations at the entrances of single-patient ICU rooms, accompanied by educational lectures and infographic dissemination. Anonymous feedback forms were used to gather information on healthcare workers’ stethoscope hygiene knowledge and behavior before and after the intervention. Results: In total, 124 observations were collected using convenience sampling between February and July 2019. Overall stethoscope hygiene compliance increased significantly from a baseline of 38% to 62% (P = .0316) (Fig. 1). Physician adherence to stethoscope disinfection increased by 22%. During the study period, hand hygiene compliance remained unchanged at 75%. Also, 74 healthcare providers completed feedback forms; they revealed an increase in awareness of stethoscope hygiene policies and/or recommendations (9% to 41%) and self reports of stethoscope hygiene compliance (28% to 44%). Conclusions: The implementation of stethoscope hygiene stations, coupled with an educational initiative, lead to a significant increase in overall stethoscope hygiene compliance among healthcare workers. Future quality improvement initiatives can adapt this strategy to promote disinfection and reduce pathogen burden of other personal and multiuse medical equipment. Funding: None Disclosures: Susy Hota reports contract research for Finch Therapeutics.

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)0.001
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.030
GPT teacher head0.338
Teacher spread0.308 · 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".

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Citations0
Published2020
Admission routes2
Has abstractyes

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