Clustering acoustical measurement data in pediatric hospital units

Relating clustered noise data to hospital patient satisfaction

Hospital noise can be problematic for both patients and staff and consistently is rated poorly on national patient satisfaction surveys. A surge of research in the last two decades highlights the challenges of healthcare acoustic environments. However, existing research commonly relies on conventional noise metrics such as equivalent sound pressure level, which may be insufficient to fully characterize the fluctuating and complex nature of the hospital acoustic environments experienced by occupants. In this study, unsupervised machine learning clustering techniques were used to extract patterns of activity in noise and the relationship to patient perception. Specifically, nine patient rooms in three adult inpatient hospital units were acoustically measured for 24 h and unsupervised machine learning clustering techniques were applied to provide a more detailed statistical analysis of the acoustic environment. Validation results of five different clustering models found two clusters, labeled active and non-active, using k-means. Additional insight from this analysis includes the ability to calculate how often a room is active or non-active during the measurement period. While conventional LAeq was not significantly related to patient perception, novel metrics calculated from clustered data were significant. Specifically, lower patient satisfaction was correlated with higher Active Sound Levels, higher Total Percent Active, and lower Percent Quiet at Night metrics. Overall, applying statistical clustering to the hospital acoustic environment offers new insights into how patterns of background noise over time are relevant to occupant perception.

Environmental noise in hospitals: a systematic review

Environmental noise has been growing in recent years, causing numerous health problems. Highly sensitive environments such as hospitals deserve special attention, since noise can aggravate patients' health issues and impair the performance of healthcare professionals. This work consists of a systematic review of scientific articles describing environmental noise measurements taken in hospitals between the years 2015 and 2020. The researchers started with a consultation of three databases, namely, Scopus, Web of Science, and ScienceDirect. The results indicate that for the most part, these studies are published in journals in the fields of medicine, engineering, environmental sciences, acoustics, and nursing and that most of their authors work in the fields of architecture, engineering, medicine, and nursing. These studies, which are concentrated in Europe, the Americas, and Asia, use as reference values sound levels recommended by the World Health Organization. L_eq measured in hospital environments showed daytime values ranging from 37 to 88.6 dB (A) and nighttime values of 38.7 to 68.8 dB (A). L_eq values for outdoor noise were 74.3 and 56.6 dB (A) for daytime and nighttime, respectively. The measurements were taken mainly inside hospitals, prioritizing more sensitive departments such as intensive care units. There is a potential for growth in work carried out in this area, but research should also include discussions about guidelines for improvement measures aimed at reducing noise in hospitals.