1187. Estimation of Individual Healthcare Workers’ Relative Hand Hygiene Compliance Using an Anonymous Electronic Monitoring System
Bibliographic record
Abstract
Abstract Background The current hand hygiene (HH) auditing and feedback strategy include anonymized data collection using direct observation and feedback of aggregated data. We aimed to evaluate whether an anonymous (without wearable device) HH electronic monitoring system (EMS) could detect patterns associated with individual healthcare workers (HCWs) and estimate their relative HH performance. Methods Observational study of HH compliance via an EMS in 10 rooms in a tertiary care hospital. The EMS measures HH product dispenser activation (an indicator of HH events) as well as entries and exits from patient rooms (a surrogate of HH opportunities). HH rates were obtained by dividing the number of HH events by the number of opportunities. HH rates were aggregated at room-shift level (i.e., an 8-hour period for a single room). For each room-shift, the HH rate was converted to a Z score, which was then associated with the individual HCW assigned to that room-shift. The relative HH performance of individual HCWs was estimated by comparing the mean Z scores of each HCW with the rest of the group by the Student T-test, with a level of significance set at P < 0.001 after adjustment by Bonferroni’s correction. To investigate whether any association could be due to chance, we looked into the potential association between average Z scores and calendar days, as a counterexample. Results Over a 100-day period, there were 45 775 HH events and 136 821 opportunities (global compliance, 33%). Schedules were available for 2980 room-shifts. Fifty-four individual HCWs took part in at least one room-shift (average per HCW, 52 room-shifts; range 1–140). Eight HCWs (15%) had a mean Z score significantly above the group average (Figure 1, green boxes; mean Z score 0.71; range, 0.52 to 0.86; P < 0.001), whereas 9 HCWs (17%) had a significantly inferior Z score (Figure 1, red boxes; mean Z score -0.47, range -0.58 to -0.31, P < 0.001). In contrast, there was no significant difference in Z scores between calendar days (Figure 2; p >0.001). Conclusion Cross-linking a high-volume HH database with HCW schedules identified a significant association between individual HCWs and HH compliance in the rooms to which they were assigned. If confirmed in further studies, anonymous EMS could be used to provide HCWs with personalized relative HH compliance feedback. Disclosures All authors: No reported disclosures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".