Optimizing emergency department layouts for noise reduction using spatial performance indicators and acoustic simulation

Hospital emergency departments (EDs) are a major source of noise pollution which has a negative impact on health outcomes, clinical communication, staff performance and health service delivery. Though becoming more widely recognised, most existing mitigation strategies are reactive interventions applied to surfaces or behaviour, and do not address the role of architectural design in shaping acoustic performance before construction is complete. The authors in this study suggest a proactive design-based approach that combines quantitative spatial indicators to screen and compare noise-related layout characteristics during the planning phase of a health care facility. The study involved four functional areas of a large tertiary care ED in a South Asian urban health care environment: the Triage Area, the Waiting Hall, the Nurses’ Station, and a Treatment Corridor, employing a comprehensive mixed methods approach. Objective acoustic monitoring was conducted over 20 consecutive weekdays (480 elapsed hours) using calibrated Class-1 sound level meters, which recorded sound pressure levels (SPL) of Leq, L10, L90 and peak. A structured survey was conducted, with 312 respondents (174 health care professionals and 138 patients/visitors), to record perceptions of noise sources and impacts. Architectural layout analysis was used to develop three new spatial indicators: Openness Index (OI), Flow Density (FD), and Zoning Index (ZI), while the propagation of noise was simulated using COMSOL Multiphysics® finite-element software and different design interventions were assessed. The results showed measured equivalent sound levels between 62.2 dB(A) and 67.0 dB(A), exceeding the study reference thresholds used for comparison. The largest noise sources identified were patient/visitor conversations (37.9%) and broadcast announcements (21.4%). Using the four zone-level values displayed in Table 3, OI, FD and ZI correlated with measured Leq at r = 0.996, 0.997 and −1.000 respectively (p = 0.004, 0.003 and <0.001); given the small number of study zones, these associations are best interpreted as descriptive preliminary relationships rather than an externally validated predictive model. Noise reductions up to 7.8 dB(A) in the most affected areas were obtained through the simulation-based modifications in the layout. These findings illustrate that spatial configuration is a key factor in determining acoustic environments and demonstrate the potential of the proposed framework as a practical, schematic-design-stage screening tool: architects and healthcare planners can compute OI, FD and ZI directly from floor plans and occupancy estimates without specialist acoustic equipment to compare layout options, flag high-risk zones such as open triage counters or undivided waiting halls, and prioritise the specific interventions (bay enclosure, sub-zoning, broadcast localisation) shown here to be most effective, before construction decisions are finalised.