Slow adoption of automated infection prevention surveillance: Are human factors contributing?

Abstract

Although automated surveillance technology has been evolving for decades, adoption of these technologies is in a nascent state. The current trajectory of public reporting, continued emergence of multidrug-resistant organisms, and mandated antimicrobial stewardship initiatives will result in an increased surveillance workload for ICPs. The use of traditional surveillance methods will be inefficient in meeting the demands for more data and are potentially flawed by subjective interpretation. An examination is offered of the slow adoption of automated surveillance technology from a system perspective with the inherent ambiguities that may operate within the ICP work structure. Formal qualitative research is needed to assess the human factors associated with lack of acceptance of automated surveillance systems. Identification of these factors will allow the National Healthcare Safety Network and professional organizations to offer educational programs and mentoring to the ICP community that target knowledge deficits and the embedded culture that embraces the status quo. With the current focus on fully electronic surveillance systems that perform surveillance in its entirety without case review, effective use of the data will be dependent on ICP skills and their understanding of the strengths and limitations of output from algorithmic detection models.