Background: Emergency department (ED) quality indicators monitor timeliness, safety, effectiveness, patient flow, and patient-centered care. Several indicators also signal the performance of patient-flow logistics, including queueing, throughput, handoffs, and coordination of time-critical resources. Nurses influence these processes, yet their familiarity with formal measurement frameworks may vary. Aim: To assess ED nurses' self-reported awareness of selected clinical quality indicators, examine its association with ED experience, and interpret the measured flow- and timeliness-related indicators from a healthcare-logistics perspective. Methods: A cross-sectional survey was completed by 45 ED nurses. Ten indicators were rated on a five-point self-reported awareness scale and grouped into four domains. Internal consistency was assessed using Cronbach's alpha. Descriptive statistics, exploratory contingency-table analyses, and Spearman correlation were reported. Healthcare logistics was an interpretive framework rather than a directly measured construct; the instrument did not assess procurement, inventory, replenishment, internal transport, or supply-chain performance. Sparse cells and multiple item-level tests required cautious inference. Results: The awareness scale showed good internal consistency (Cronbach's alpha = .89). Longer ED experience was positively correlated with the overall awareness score (Spearman's rho = .374, p = .011; N = 45). The reported omnibus association between experience group and categorized overall awareness was significant (chi-square (6) = 23.104, p = .001), although sparse expected counts limit conventional chi-square inference. Of the flow- and timeliness-related item tests, only door-to-doctor/ECG time met a conservative Bonferroni benchmark of .005. Clinical experience was the most frequently reported information source. Conclusion: Longer ED experience was associated with greater self-reported awareness. The findings support integrating patient-flow logistics into nursing orientation and quality-improvement training, but they do not provide evidence about supply-chain performance. The small sample, self-report measure, sparse cells, and cross-sectional design restrict causal and generalizable conclusions.