Electronic Health Record Workflows in Acute Care Surgery: Ethnographic Study.

BACKGROUND: Systematic strategies to harness electronic health record (EHR) workflows, reduce redundancy, and support decision-making remain limited in acute care surgery (ACS). Understanding how EHR systems and workflows intersect with time-sensitive settings is critical to improving decision-making and outcomes in ACS. OBJECTIVE: This study aimed to evaluate how ACS clinicians leverage the EHR for decision-making and to identify opportunities and challenges for EHR-enabled decision support. METHODS: We conducted a qualitative ethnographic study over a 6-month period, combining in-depth interviews with 15 ACS surgeons and providers and 100 hours of "paired fieldwork" observations spanning the entire perioperative arc by a surgical provider and an organizational sociologist. Using constructivist grounded theory, we identified the enablers, challenges, and opportunities for EHR-enabled decision-making in ACS. RESULTS: Surgeons fell into two groups: (1) those who accepted information overload as inherent to the EHR, relying on generic templates and standard attestations, and (2) others who viewed it as a problem to fix, actively correcting errors and composing individualized summaries. Ambiguity in billing requirements drove overdocumentation, resulting in "note bloat" that obscured high-yield information. EHR use during decision-making focused primarily on risk assessment, though navigation challenges hindered access to critical data. Forecasting key outcomes that alter management or facilitate shared decision-making was seen as valuable. Automated risk stratification, generated from live EHR data while minimizing alert fatigue, was seen as a potential solution. CONCLUSIONS: ACS clinicians use various tactics to navigate EHR challenges and focus on high-value tasks. Streamlined risk assessment using EHR data may strengthen decision-making in critical moments, but solutions must integrate seamlessly within existing workflows to provide rapid and accurate outputs that prioritize meaningful outcomes.