OR WAIT null SECS
Healthcare-associated infections (HAI) in intensive care units (ICU) can be significantly reduced or eliminated by increasing care providers compliance with evidence-based guidelines. Using a human factors and systems engineering approach, researchers from Johns Hopkins University, Baylor Health Systems and University of Maryland Medical Center conducted a qualitative study to identify the underlying causes of non-compliance with evidence-based guidelines for preventing four types of HAI in ICUs.
Gurses, et al. conducted semi-structured, in-depth interviews with a total of 20 surgical ICU care providers including three attending physicians, two residents, six nurses, three quality improvement coordinators, two infection control practitioners, two respiratory therapists and two pharmacists. Thematic analysis of the qualitative data was performed using a grounded theory approach.
A new framework called "systems ambiguity" that can be used to explain and prevent care providers non-compliance with evidence-based guidelines emerged from the data. We define systems ambiguity as "uncertainty or vagueness that may prevent a work system from achieving its purpose." Five major types of ambiguity that can affect care providers compliance behaviors have been identified: task ambiguity, responsibility ambiguity, expectation ambiguity, method ambiguity, and exception ambiguity.
Systems ambiguity framework can be used to identify the underlying causes of care providers non-compliance with guidelines aimed at preventing HAI, and guide efforts for developing effective interventions aimed at improving compliance rates. Future research should focus on designing multi-faceted interventions based on the systems ambiguity framework and evaluating the impact of these interventions.
Reference: AP Gurses, Y Xiao and K Seidl. Impact of systems ambiguity on guideline compliance in intensive care units. Presentation at ICPAC, June 2011. BMC Proceedings 2011, 5(Suppl 6):O48.