# ICU Disparnumerophobia and Triskaidekaphobia: The 'Irrational Care Unit'?

## TL;DR

This study investigates subconscious cultural biases in ICU ventilator settings, revealing superstitious preferences such as odd number preference and aversion to 13, which may influence clinical decision-making.

## Contribution

It introduces a novel Monte Carlo statistical method to detect superstitious number preferences in medical treatment settings.

## Key findings

- Patients preferred odd ventilator settings over even numbers.
- There was an aversion to the number 13 in certain ventilator parameters.
- A novel statistical approach was effective in identifying superstitious biases.

## Abstract

Whilst evidence-based medicine is the cornerstone of modern practice, it is likely that clinicians are influenced by cultural biases. This work set out to look for evidence of number preference in invasive mechanical ventilatory therapy as a concrete example of subconscious treatment bias. A retrospective observational intensive care electronic medical record database search and analysis was carried out in adult general, specialist neurosciences and paediatric intensive care units within a tertiary referral hospital. All admitted, invasively mechanically ventilated patients between October 2014 and August 2015 were included. Set positive end-expiratory pressure (PEEP), respiratory rate (RR) and inspiratory pressure (Pinsp) settings were extracted. Statistical analysis using conventional testing and a novel Monte Carlo method were used to look for evidence of two culturally prevalent superstitions: Odd/even preference and aversion to the number 13. Patients spent significantly longer with odd choices for PEEP ($OR=0.16$, $p<2\times10^{-16}$), RR ($OR=0.31$, $p<2\times10^{-16}$) and Pinsp (OR=0.48, $p=2.9\times10^{-7}$). An aversion to the number 13 was detected for choices of RR ($p=0.00024$) and Pinsp ($p=3.9\times10^{-5}$). However a PEEP of 13 was more prevalent than expected by chance ($p=0.00028$). These findings suggest superstitious preferences in intensive care therapy do exist and practitioners should be alert to guard against other, less obvious but perhaps more clinically significant decision-making biases. The methodology described may be useful for detecting statistically significant number preferences in other domains.