Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units

Appl Ergon. 2024 Jul:118:104275. doi: 10.1016/j.apergo.2024.104275. Epub 2024 Apr 3.

Abstract

Weaning patients from ventilation in intensive care units (ICU) is a complex task. There is a growing desire to build decision-support tools to help clinicians during this process, especially those employing Artificial Intelligence (AI). However, tools built for this purpose should fit within and ideally improve the current work environment, to ensure they can successfully integrate into clinical practice. To do so, it is important to identify areas where decision-support tools may aid clinicians, and associated design requirements for such tools. This study analysed the work context surrounding the weaning process from mechanical ventilation in ICU environments, via cognitive task and work domain analyses. In doing so, both what cognitive processes clinicians perform during weaning, and the constraints and affordances of the work environment itself, were described. This study found a number of weaning process tasks where decision-support tools may prove beneficial, and from these a set of contextual design requirements were created. This work benefits researchers interested in creating human-centred decision-support tools for mechanical ventilation that are sensitive to the wider work system.

Keywords: Cognitive task analysis; Human centred AI; Intensive care units; Mechanical ventilation weaning; Work domain analysis.

MeSH terms

  • Adult
  • Artificial Intelligence
  • Decision Support Systems, Clinical
  • Decision Support Techniques
  • Female
  • Humans
  • Intensive Care Units*
  • Male
  • Middle Aged
  • Respiration, Artificial
  • Task Performance and Analysis
  • Ventilator Weaning* / methods