OBJECTIVES

: Early identification and response to sepsis is directly linked to patient outcomes. Currently, there are established guidelines and protocols, in practice - recognition and treatment of sepsis is challenging for emergency room (ER) staff, as sepsis can present with a multitude of symptoms during a variety of medical emergencies which cannot always be quantified. Qualitative research is able to detect unquantifiable data that quantitative research is unable to.

METHODS :

To better understand how ER staff and their response to sepsis may affect patient outcomes, fifteen in-depth, qualitative interviews were conducted across seven hospitals in the United States with physicians and nurses. These interviews focused on how ER staff identify sepsis, and how they perform current treatment protocols. This also included discussing how differing perceptions of sepsis amongst ER staff influence best practices. All interviews were tape-recorded, transcribed, and analyzed in qualitative software.

RESULTS

Interviewees generally defined sepsis in three levels of severity: stable, severe, or septic – but the early recognition of sepsis remained a contested issue amongst ER staff. All interviewees reported that it was best to treat possibly septic patients with rapid fluids for better immediate outcomes. ER staff reported that sepsis treatment required a heavy burden on their time due to the attention needed to administer fluids, and monitor the disease. Some reported they often refrained from making the diagnosis early to maintain their workplace schedule.

CONCLUSIONS

: This research highlights the increasing need to incorporate caregiver burden and workplace productivity in decision making, specifically for protocol adherence. Qualitative data is capable of highlighting nuances of hospital settings which would otherwise be missed quantitatively. In this instance, these nuances directly impact patient care. Future mixed-methods research is needed to further understand how ER staff and their diagnosis of septic patients affects patient morbidity and mortality.