Unmasking Societal Biases in Respiratory Support for ICU Patients through Social Determinants of Health

TL;DR

This paper investigates societal biases in ICU respiratory support by analyzing social determinants of health, conducting fairness audits, and providing a benchmark dataset to improve understanding and evaluation of health disparities.

Contribution

It introduces a fairness auditing framework for respiratory support models and releases a verified temporal benchmark dataset for clinical evaluation.

Findings

Identified disparities in respiratory intervention outcomes across demographic groups

Demonstrated biases in predictive models related to social determinants of health

Provided a new dataset for benchmarking clinical respiratory tasks

Abstract

In critical care settings, where precise and timely interventions are crucial for health outcomes, evaluating disparities in patient outcomes is essential. Current approaches often fail to fully capture the impact of respiratory support interventions on individuals affected by social determinants of health. While attributes such as gender, race, and age are commonly assessed and provide valuable insights, they offer only a partial view of the complexities faced by diverse populations. In this study, we focus on two clinically motivated tasks: prolonged mechanical ventilation and successful weaning. Additionally, we conduct fairness audits on the models' predictions across demographic groups and social determinants of health to better understand health inequities in respiratory interventions within the intensive care unit. Furthermore, we release a temporal benchmark dataset, verified by clinical experts, to facilitate benchmarking of clinical respiratory intervention tasks.