Aims In acutely ill children, weights are often estimated to calculate drug and fluid dosage. Many methods exist, attempting to balance complexity and accuracy. The most accurate are based on physical measurements, but those commonly used in the UK are based on age alone. In 2011 the Advanced Paediatric Life Support (APLS) recommendations changed from using a single formula to three. Meanwhile the UK Resuscitation Council maintains that complexity increases risks of error and still advocates the single formula. To date no studies have assessed the crucial human factors affecting ease of use or rates of error. This project aimed to pilot a technique for testing accuracy, speed and user preference (usability) of different methods.

Methods We developed a website (www.pemresearch.org) where participants applied four common weight estimation methods (table 1) to a range of ages. Orders of methods and ages were randomised between each entry. To reflect a real resuscitation scenario, participants were instructed to complete the test as quickly and accurately as possible. Psychological pressure was generated by a visible running timer combined with a leaderboard competition. Subject inter-method variability of speed and accuracy were analysed using one way ANOVA and pairwise t-tests with adjusted p-values.

Results 34 acute paediatric staff completed the test. 74% routinely used the single formula APLS method. Post-test 77% reported the reference table method easiest to use. Both single formula APLS and reference table were significantly quicker to use than other methods (p < 0.001 and <0.001). There was no significant difference detected in accuracy between methods. (table 2)

Conclusions This is a feasible technique of assessing usability. Although in our pilot there was no significant difference in accuracy detected, the time taken to apply each method and preference to use appear related to complexity. This novel method of assessing usability has potential advantages over other such as in-situ real-time simulation, including rapid turnaround and distribution via the internet. We plan to expand this study to a larger sample size and validate against in-situ simulation. After refining the technique we will extend its application to other everyday tools such as clinical decision rules.