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Deliberate clinical inertia is the art of doing nothing as a positive response. Individual clinicians can promote deliberate clinical inertia through teaching, re-framing the act of 'doing nothing' as 'doing something' and engaging in shared decision making. Behaviour change on a larger scale requires a systematic approach. Nudging is a subtle change to the decision-making context to prompt specific choices. A nudge unit is a team of relevant professionals who engage with various multidisciplinary teams within a health service who help test and implement nudge interventions in a clinical environment. A nudge unit could be used to design environments to prompt clinicians to re-think before ordering unnecessary tests or treatments. Nudge units could improve knowledge translation, support continuous quality improvement and help build a learning health system. They could also boost collaboration and empower staff to evaluate their workplace decision-making frameworks.

The high-risk, high-stress and high-stakes environment of out-of-hospital or emergency department paediatric resuscitation is prone to human error, and medication errors are common. This could be contributing to the difference in survival rate of resuscitation in the out-of-hospital versus inpatient setting. Medication for children during resuscitation requires estimation of the child's weight and calculation of the corresponding drug dose. Whilst both of these steps can lead to error, calculation errors (including 10-fold errors) are much more common and harmful than weight errors. Previous solutions aim to optimise each stage of the medication dosing process. Currently, Australian guidelines suggest using the highly inaccurate original advanced paediatric life support formula, weight = 2 × (age + 4), to dose medications in these settings. This means age is converted to weight, which is then converted to dose. There is no evidence that this is causing harm to patients. Therefore, it could be suggested that age could safely be converted straight to dose according to preset doses. This eliminates the need for any weight estimation or dose calculation, thus reducing the potential for error and harm.

OBJECTIVES: To determine the accuracy of using parental estimate of a child's weight compared to actual weight in a paediatric emergency setting. METHODS: Prospective, observational study. Age, weight and height data were collected from children aged 1 month up to 11 years with an Australian Triage score of 3 or higher. This was compared with a parent weight estimate. Analysis is descriptive. RESULTS: A total of 450 children were studied with a mean age of 4 years 4 months. A total of 85.3% of parents were willing to provide a weight estimate (n = 384). The mean difference between the parent estimate (where provided) and the actual weight was 0.33 kg (measured weight > estimated; 95% confidence interval [CI] -6.9 kg to +7.6 kg). There was 75% agreement within 10% of the measured weight (95% CI 71-79%) and 92% agreement within 20% of the measured weight (95% CI 89-95%). Weight was more commonly underestimated than overestimated. Children of Polynesian/Pacific ethnicity were less likely to have an accurate parental weight estimation. CONCLUSIONS: Parent estimate is an accurate weight estimation method when parents are willing to give an estimate. There is ethnic variation in accuracy that should be taken into account when applying this method.

OBJECTIVE For seriously ill children, weight is often required to direct critical interventions. As it is not always feasible to measure weight in emergencies, age-based weight prediction formulae may be used as an alternative. The Best Guess formulae, derived in Australia, have been shown to be among the most accurate age-based methods in Australian children. They were validated in 2010. The present study aims to re-validate the Best Guess formulae and compare their performance to the previous validation cohort. METHODS A prospective observational study was conducted in the paediatric ED of a community teaching hospital. It included a convenience sample of children aged 1 month to 10 years who presented between July 2018 and April 2019. Seriously ill children were excluded. Data collected included measured weight, height, gender, age and ethnic group. The outcomes of interest were predictive performance of Best Guess formulae and comparison of predictive accuracy with a 2005 cohort from the same ED. RESULTS A total of 961 patients were included; 42% girls, median age 3 years. The sample was ethnically diverse. Mean percent difference in weight was -3.3% with the formulae usually over-estimating weight. Overall, agreement within 10% was 41.8%; agreement within 20% was 72.6%. Predictive accuracy was not significantly different between the cohorts. CONCLUSION The Best Guess method has not reduced in accuracy as a weight estimation method in emergent situations in this Australian cohort, despite a tendency to slightly over-estimate children's weight. Further study is needed to test the Best Guess method's accuracy in ethnic subgroups.