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Record W4403323432 · doi:10.1017/ash.2024.247

Assessing the quality of Hand Hygiene data produced by Alberta Health Services using a time-in-motion study

2024· article· en· W4403323432 on OpenAlexaffabout
Jennifer Ellison, Zhe Lu, Alison Devine, Blair McFerran, Sandra Bolton, Helen Popson, Kathryn Bush

Bibliographic record

VenueAntimicrobial Stewardship & Healthcare Epidemiology · 2024
Typearticle
Languageen
FieldMedicine
TopicInfection Control in Healthcare
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsHygieneQuality (philosophy)Motion (physics)PsychologyEnvironmental healthBusinessMedicineComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Background: Alberta Health Services (AHS) measures hand hygiene compliance through direct observations performed by trained site-based reviewers (SBRs) and facilitated by the Infection Prevention and Control (IPC) program. Within AHS there are >100 acute care facilities, ranging in bed size from four beds to more than 1,000, with catchment populations ranging from one million. A time-in-motion study using trained AHS IPC staff was proposed to validate the completeness and accuracy of data being collected by the SBRs. Methods: The AHS IPC staff performed direct observations at pre-selected facilities across all five zones and four different unit types (emergency, medical, surgical, and intensive care) for four 30-minute periods during weekdays between June and September 2023. An iPad app was used to capture results from all four moments of hand hygiene. The reviewer indicated the day and time of the review and captured as many representative hand hygiene moments and healthcare providers as possible. The distributions of the four moments of hand hygiene, healthcare provider group and overall compliance were compared at the unit type and facility level (tertiary, large urban, regional, pediatric, and small sites) between this time-in-motion study and SBR data collected June-September 2023. Results: The study collected 175 reviews and 4,683 observations from 14 facilities and 48 units. Between June and September 2023, SBRs collected 2,625 reviews and 61,506 observations from these same facility and unit types. Across all facility and unit types, the distribution of the four moments was similar between the study and SBRs. Similar proportions of healthcare providers were also observed. However, the overall hand hygiene compliance collected in the study was approximately 10% lower across all unit types as compared to that collected by the SBRs (study: 63%-84%; SBRs: 75%-92%). Conclusions: In public health surveillance, completeness and accuracy are two characteristics of high-quality data. A time-in-motion study identified that the hand hygiene observations collected by SBRs were complete, as the range of healthcare providers observed, and the distribution of their moments, mirrored that collected in the study. However, the SBRs reported higher compliance than the study participants and the true hand hygiene compliance is likely lower than what is currently being reported. Since this difference was seen consistently across all unit and facility types, trending data over time should still identify areas in need of improvement and may help to suggest causes of the over-reporting.

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)0.030
metaresearch head score (Gemma)0.087
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 score0.538
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.087
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.013
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.002
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 head0.182
GPT teacher head0.495
Teacher spread0.313 · 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
Published2024
Admission routes2
Has abstractyes

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