Nurses’ preferences for interventions to improve infection prevention and control behaviors based on systems engineering initiative to patient safety model: a discrete choice experiment

Abstract

Abstract Background The evidence of preferences for infection prevention and control (IPC) intervention from system perspective was lacked. This study aimed to elicit nurses’ preferences for the intervention designed to improve IPC behaviors based on the Systems Engineering Initiative to Patient Safety (SEIPS) model using Discrete Choice Experiment (DCE). Methods A DCE was conducted among nurses who were on active duty and willing to participate from July 5th to 10th, 2021 in a tertiary hospital in Ganzhou City, Jiangxi Province, using convenience sampling. A self-administered questionnaire included scenarios formed by six attributes with varying levels based on SEIPS model: person, organization, tools and technology, tasks, internal environment and external environment. A conditional logit and latent class logit model were performed to analyze the data. Results A total of 257 valid questionnaires were analyzed among nurses. The results from the latent class logit model show that nurses’ preferences can be divided into three classes. For nurses in multifaceted-aspect-preferred class (41.9%), positive coefficients were obtained in those six attributes. For person-preferred class (19.7%), only person was positively significant. For environment-preferred class (36.4%), the most important attribute were tasks, tools and technology, internal environment and external environment. Conclusions This finding suggest that nurses have three latent-class preferences for interventions. Multifaceted interventions to improve IPC behaviors based on the SEIPS model are preferred by most nurses. Moreover, relevant measured should be performed targeted the latent class of person-preferred and external-environment-preferred nurses.

Keywords

• Behavior and behavior mechanisms
• Infection control
• Cross Infection
• Patient safety
• Latent class analysis
• Ergonomics