Abstract:
Background: Anaesthetic drug administration is complex, and typical clinical environments can entail significant cognitive load. Colour-coded anaesthetic drug trays have shown promising results for error identification and reducing cognitive load.
Methods: We used experimental psychology methods to test the potential benefits of colour-coded compartmentalised trays compared with conventional trays in a simulated visual search task. Effects of cognitive load were also explored through an accompanying working memory-based task. We hypothesised that colour-coded compartmentalised trays would improve drug-detection error, reduce search time, and reduce cognitive load. This comprised a cognitive load memory task presented alongside a visual search task to detect drug errors.
Results: All 53 participants completed 36 trials, which were counterbalanced across the two tray types and 18 different vignettes. There were 16 error-present and 20 error-absent trials, with 18 trials presented for each preloaded tray type. Syringe errors were detected more often in the colour-coded trays than in the conventional trays (91% vs 83%, respectively; P=0.006). In signal detection analysis, colour-coded trays resulted in more sensitivity to the error signal (2.28 vs 1.50, respectively; P<0.001). Confidence in response accuracy correlated more strongly with task performance for the colour-coded tray condition, indicating improved metacognitive sensitivity to task performance (r=0.696 vs r=0.447).
Conclusions: Colour coding and compartmentalisation enhanced visual search efficacy of drug trays. This is further evidence that introducing standardised colour-coded trays into operating theatres and procedural suites would add an additional layer of safety for anaesthetic procedures.
Reference:Laxton V, Maratos FA, Hewson DW, Baird A, Archer S, Stupple EJN. Effects of colour-coded compartmentalised syringe trays on anaesthetic drug error detection under cognitive load. Br J Anaesth. 2024 Feb 8:S0007-0912(24)00004-7. doi: 10.1016/j.bja.2023.12.033. Epub ahead of print. PMID: 38336517.