Abstract
Traditional methods for prioritization are limited and insufficient for today's magnetic resonance imaging (MRI) demands. In particular, the discrepancy in urgency of the heterogeneous emergency department (ED) patient population necessitates risk stratification to meet different degrees of urgency. The purpose of this study is to more effectively prioritize the MRI imaging needs of ED patients commensurate with the severity of their presenting illness. A 3-level tiered classification system (tier 1: critical, tier 2: emergent, and tier 3: urgent) of ED patients with unambiguous hierarchically defined numerical classifications was implemented to replace a traditional method of MRI orders. Each tier was accompanied by guiding consensus-driven clinical definitions and common qualifying examples. Lastly, each tier imaging order was tied to a specific target "order to imaging start time" (OTST). After implementation, a month-by-month 1-year retrospective analysis of ED MRI imaging order volume was conducted to assess the percentage distribution of each category. In addition, a month-by-month 1-year retrospective analysis of the OTST for each tier was conducted. The OTST outcome measure was used to monitor the ability of the system to meet tier target times based on severity. The system effectively prioritized ED patients into 3 tiers based on acuity. An inverse relationship existed between ED MRI OTST and the tier severity into which the patient was stratified. We found that only 4% of the ED-specific volume is truly critical (tier 1). In addition, tier 3 MRI examinations constituted 75% of the ED volume. Month-by-month quality assurance analysis demonstrated consistent completion of examinations under or close to the target times tied to each tier. The average overall wait time from order time to begin scan time for all ED MRIs decreased from 245 minutes (4.1 hours) at baseline to less than 136 minutes (2.7 hours). We implemented and evaluated a 3-tiered system of ED MRI imaging orders based on patient severity. The system was unambiguous due to its numerical hierarchy, and each of the 3 tiers was accompanied by explicit guiding definitions for each category. A quality assurance process following implementation allowed us to monitor the ability of the system to meet target times tied to each tier. Our current ability to accurately predict a target performance time allows us to set accurate expectations for both providers and patients.
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