Health-care staff perspectives in optimising delirium prevention using data-driven interventions

Area of Science:

• Implementation Science
• Healthcare Management
• Geriatric Medicine

Background:

• Delirium prevention is critical in healthcare settings.
• Data-driven optimisations offer potential for improved delirium prevention.
• Understanding staff perspectives is key for successful implementation.

Purpose of the Study:

• Identify factors influencing delirium prevention implementation from health service staff viewpoints.
• Determine characteristics and strategies for clinical adoption of data-driven delirium prevention optimisations.
• Utilise the Monash Learning Health System (LHS) paradigm for integrated assimilation of delirium prevention.

Main Methods:

• Qualitative study conducted in an Australian metropolitan public health network.
• Purposive sampling of 18 clinical and non-clinical participants with delirium care expertise.
• Inductive analysis of semi-structured interviews using the Consolidated Framework for Implementation Research (CFIR).

Main Results:

• Challenges exist in integrating delirium risk identification and screening into clinical workflows.
• Infrastructure obstacles hinder the digitisation of clinical decision support.
• Engaging caregivers and staff is essential for designing effective delirium prevention optimisations.

Conclusions:

• Key factors influencing delirium prevention include IT infrastructure, workforce digital literacy, and accountability.
• Automated delirium risk prediction models require improved hospital IT and staff support.
• Future research should focus on pragmatic clinical trials for optimised delirium prevention interventions.