A Novel Mixed Methods Approach to Understanding Priorities in Emergent Traumatic Brain Injury Anesthesia Care

Introduction Traumatic brain injury (TBI) has a high mortality rate. Given the limited evidence regarding optimal anesthesia care for patients with TBI, we elicited anesthesiology provider perspectives on priorities for improving emergent TBI anesthesia care through mixed methods. Methods We elicited survey and focus group responses from 177 anesthesiology attendings, nurse anesthetists, and residents. Textual data quantified word characteristics (frequency, repeated words and percentage) by word cloud generation and iterative development of common themes by inductive reasoning. Themes weighted on the frequency of phrases or words were analyzed within another word cloud and classified as structure, process, and outcome measures. A Pareto diagram of themes identified high interest content categories. Results In triangulation, the leading 20% of themes were classified into Agency for Healthcare Research and Quality (AHRQ) domains. Twenty-three (13%) survey responses and two focus group data (27 participants) were examined. "Time" was the largest word by word cloud and the most common word (3.57%). Inductive analysis produced 28 content categories ("timeliness" 28.07% most common theme), classified into 11 structure-type, 15 process-type, 2 outcome-type, and no balance quality improvement categories. There were no content categories classified into the balance-type quality measure. A Pareto diagram indicated "timeliness," "standardization," "hemodynamics," and "communication" as important themes. Leading AHRQ domains were "effective, equitable, timely, and safe." Conclusion Word cloud, inductive reasoning, and use of the Pareto diagram identified many opportunities for improving emergent TBI anesthesia care in our institution.