Journal of Pediatric Care

Description

Children are at high risk for Rapid Sequence Intubation (RSI), which has a low incidence but a high risk of cognitive overload and errors that could have negative consequences. Mental guides, for example, graphs, calculations and stream outlines, are prompts that externalize and structure mental cycles to lessen mental burden, accordingly decreasing mistakes. A simplified mathematical system for volume-based dosing is combined with a color-coded chart and medication box in the Paediatric Anaesthetic Emergency Drug Solution (PAEDS) approach; which has not previously been discussed in terms of its impact on cognitive load during a simulated RSI. Four highfidelity RSI simulations, two of which required the use of the PAEDS method, were performed by 26 multidisciplinary emergency medicine clinicians (doctors and nurses) assigned to four groups in a cross-over, randomised trial. Utilizing grounded theory methodology, this mixed methods study adhered to the pragmatic ontology. In order to facilitate appropriate open and axial coding, qualitative data from nine individual interviews were gathered through an inductive process of thematic analysis. Cognitive loading using the raw NASA-Task load index, time to intubation and drug dosage details were all quantitatively gathered for safety evaluation.

Blended Techniques

Paediatric RSI has both large intrinsic and extraneous loads, with a higher proportion of non-automatic actions (reduced automaticity due to the higher intrinsic load) and a large emotional burden associated with caring for a sick child. Additional cognitive load also comes from being rare events. There is a consensus in the literature that medications in paediatric RSI are a large source of stress and error and there is no universal approach for medication preparation and delivery in resuscitation each medication is diluted and prepared as a 0.1 mL/kg dosage in the Paediatric Anaesthetic Emergency Drug Solution (PAEDS) volume-based drug calculator, 21 kg child requires 2.1 mL of a given medication. These meds are restricted to the ones in the outline and have all been normalized for fixation and weakening. They are variety coded according to the Australian standard. PAEDS incorporates all drugs expected for a pediatric RSI in an ED and these are put away in a marked box. The purpose of this pilot study is to determine how the PAEDS method affects the cognitive load of emergency medicine practitioners during simulated paediatric RSI. This was a blended techniques investigation of focalized plan, following a logical cosmology with grounded hypothesis as the utilized exploration strategy. Participants were assigned to one of four study groups (A-D) via stratified randomization during the cross-over trial portion of the study. Each group performed four distinct paediatric RSI simulations, two of which allowed the team leader to manage the situation pragmatically as they would in their practice, referred to as the "standard approach." Teams were informed immediately prior to beginning the simulation of their random assignment to each scenario and the required approach. The Newborn and Paediatric Emergency Transport Service (NETS) calculator, which is an online pediatric clinical calculator that shows the concentrations, dilutions and doses required for a given weight, was available to all groups. The four EM Consultants led the team in this study, choosing the NETS calculator as their "standard approach" in the two mandated scenarios. Clinicians can take advantage of two aspects of the PAEDS approach's color-coded medication chart. Both the color coding and the cognitive aid it provides prompted positive responses. Colors are a key part of the PAEDS approach because they improve attention span and increase transfer of knowledge to long-term memory compared to monochromatic information. Color coding information reduces cognitive load because colors are processed subconsciously and do not contribute to working load memory. Cognitive aids are designed to provide accessible knowledge and to reduce intrinsic load by decreasing the reliance on memory, which can cause errors.

Axial Coding

A single researcher used thematic analysis to review and analyze interview transcripts in order to collect qualitative data. The process began with the transcription of the data and the assignment of pseudonyms. After each participant was assigned a unique code, coding began. Open coding, in which the researcher identifies pieces of data that shared a common concept and is labeled with a code, was the initial step of coding using grounded theory. Coding was done manually. Axial coding was used to organize multiple codes that were developed. In the end, themes are created by establishing connections between codes using axial coding. The quantitative data were first analyzed for normality using the Shapiro-Wilk test and then selective coding was used to further organize the data into global themes that were represented by thematic networks. Mean and standard deviation are shown for normally distributed data, while median and interquartile ranges are shown for nonnormally distributed data. The significance of the observed differences was evaluated using the Wilcoxon rank sum test. There was a lot of anxiety about weight-based dosing, especially about how to calculate the right dose. In these interviews, it was reported that the PAEDS approach made people feel faster and that the limited medication options made choosing a medication less stressful. The medication box helped keep the medications safe during these interviews and could be labeled and taken with the patient on transfers. Because it deviated from their established practice, one team leader stated that it cognitively loaded them. The PAEDS approach additionally had some regrettable input from staff that could have done without the reality they couldn't rapidly sort out the milligram portion given. It was thought that the medication chart's color-coding was helpful because it was quick and easy to use. Four distinct groups were used to analyze the raw NASA-TLX questionnaire data on cognitive load: The entire group of clinicians and three, predefined subgroups: Team leaders, drug preparation clinicians and drug administration administrators. There was ordinarily one medication manager and two members answerable for prescription readiness in every situation, with the exception of two situations which had two medication executives and one situation that had three staff planning meds.