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.

Intelligibility of medically related sentences in quiet, speech-shaped noise, and hospital noise.

Noise in healthcare settings, such as hospitals, often exceeds levels recommended by health organizations. Although researchers and medical professionals have raised concerns about the effect of these noise levels on spoken communication, objective measures of behavioral intelligibility in hospital noise are lacking. Further, no studies of intelligibility in hospital noise used medically relevant terminology, which may differentially impact intelligibility compared to standard terminology in speech perception research and is essential for ensuring ecological validity. Here, intelligibility was measured using online testing for 69 young adult listeners in three listening conditions (i.e., quiet, speech-shaped noise, and hospital noise: 23 listeners per condition) for four sentence types. Three sentence types included medical terminology with varied lexical frequency and familiarity characteristics. A final sentence set included non-medically related sentences. Results showed that intelligibility was negatively impacted by both noise types with no significant difference between the hospital and speech-shaped noise. Medically related sentences were not less intelligible overall, but word recognition accuracy was significantly positively correlated with both lexical frequency and familiarity. These results support the need for continued research on how noise levels in healthcare settings in concert with less familiar medical terminology impact communications and ultimately health outcomes.

Clustering acoustical measurement data in pediatric hospital units.

The previous hospital acoustic literature has highlighted some important considerations and various complexities regarding objective noise measurements. However, extensive use of conventional acoustical metrics such as logarithmically averaged equivalent sound pressure levels (Leq) do not sufficiently describe hospital acoustical environments and often lack considerations of the room-based activity status that can significantly influence the soundscape. The goal of this study was to explore utilizing statistical clustering techniques in healthcare settings with a particular aim of identifying room-activity conditions. The acoustic measurements were conducted in the patient rooms of two pediatric hospital units and subsequently classified based on two room-activity conditions-active and non-active conditions-by applying statistical clustering analyses with standard k-means and fuzzy c-means algorithms. The results of this study demonstrate the most probable noise levels and degree of associations of the measured noise levels for the two room-activity conditions. The results were further validated in terms of the clustered levels, the number of conditions, and parameter dependency. The clustering approach allows for a more thorough soundscape characterization than single-number level descriptors alone by providing a method of identifying and describing the noise levels associated with typical, intrinsic activity conditions experienced by occupants.

Examining the Utility of Perceptual Noise Categorization in Pediatric and Neonatal Hospital Units.

Medical and nursing staff working in hospitals often experience exposure to extreme sound environments, and there is growing evidence of the negative impacts. Previous research highlighted various complexities regarding noise sources in hospitals; however, identifications of intrinsic noise categories that can reveal the complex mixture of existing hospital noise is still limited. The objective of this work was to identify intrinsic categories of the noise sources based on staff perceived annoyance and explore clear associations of these categorized noise sources with psychological perceptions. The staff perceptual responses regarding hospital noise were assessed by conducting surveys at the three pediatric and neonatal care units in two hospitals. Using principle component analysis (PCA), the psychological annoyance responses of 94 participants were used to derive the inherent structural patterns of the existing noise sources. The derived PCA categorization was validated on mixed-model analysis of variances, and employed on regression models to explore potential associations between the categorized noise factors and the staff's psychological perceptions. The results highlighted three intrinsic noise categories and their negative impacts on staff's psychological perceptions including work/rest disturbance and noisiness. Taken as a whole, the findings better reveal problematic noise source categories and establish a framework for hospital noise control that is less source-specific and more broadly generalizable.

Evaluating hospital soundscapes to improve patient experience.

Hospital soundscapes can be difficult environments to assess acoustically due to alarms, medical equipment, and the continuous activity within units. Routinely, patients perceive these soundscapes to be poor when rating their hospital experience on HCAHPS (Hospital Consumer Assessment of Healthcare Providers and Systems) surveys administered after discharge. In this study, five hospital units of widely varying HCAHPS "quietness" performance were analyzed. Sound pressure levels were measured in 15 patient rooms and 5 nursing stations over 24-h periods. HCAHPS "quietness of the hospital environment" patient survey data were correlated with measured acoustical data at a room-level, revealing acoustical metrics linked to patient perceptions of hospital soundscape conditions. Metrics found to be statistically correlated (p < 0.05) included the absolute LAMIN levels in patient rooms, which found significantly higher HCAHPS quietness scores in units with average LAMIN levels below 35 dBA, in addition to specific low frequency octave bands and occurrence rates. Many other standard acoustical metrics (such as LAEQ, LAMAX, LCPEAK, and LA90) were not found to be statistically correlated between measured acoustical data and HCAHPS quietness patient responses. Taken as a whole, this study provides insights into the potential relationships between hospital noise and patient satisfaction.

Exploring the Relationships Between Patient Room Layout and Patient Satisfaction.

This retrospective, exploratory study examined 8,366 patient responses to surveys on patient satisfaction and patient room spatial layout in a large academic teaching hospital consisting of 17 nursing units and 382 patient rooms. This study included four spatial measures: average distance to the nurse station, room handedness, location of bed, and location of first encounter-and explored their statistical associations with two types of patient satisfaction surveys (Hospital Consumer Assessment of the Healthcare Provider and Systems and third party). The study had two phases: a preliminary study of 3,751 patient respondents in a limited diagnosis-related group (DRG) over 5 years and a general study of 4,615 patient respondents with a broader range of DRG's over 2 different years from the preliminary study. Findings indicated statistically significant relationships between all four spatial layout measures and specific survey questions pertaining to perception of nursing, physician, individual care, and overall room environment. Results emphasize the importance of hospital design-and spatial layout in particular-on patient satisfaction.

Environmental Variables That Influence Patient Satisfaction: A Review of the Literature.

Patient's perception of care-referred to as patient satisfaction-is of great interest in the healthcare industry, as it becomes more directly tied to the revenue of the health system providers. The perception of care has now become important in addition to the actual health outcome of the patient. The known influencers for the patient perception of care are the patient's own characteristics as well as the quality of service received. In patient surveys, the physical environment is noted as important for being clean and quiet but is not considered a critical part of patient satisfaction or other health outcomes. Patient perception of care is currently measured as patient satisfaction, a systematic collection of perceptions of social interactions from an individual person as well as their interaction with the environment. This exploration of the literature intends to explore the rigorous, statistically tested research conducted that has a spatial predictor variable and a health or behavior outcome, with the intent to begin to further test the relationships of these variables in the future studies. This literature review uses the patient satisfaction framework of components of influence and identifies at least 10 known spatial environmental variables that have been shown to have a direct connection to the health and behavior outcome of a patient. The results show that there are certain features of the spatial layout and environmental design in hospital or work settings that influence outcomes and should be noted in the future research.

Lighting and Nurses at Medical-Surgical Units: Impact of Lighting Conditions on Nurses' Performance and Satisfaction.

OBJECTIVE: This study investigates the perception of nurses about their lighting environment at medical-surgical hospital units in order to understand areas of improvement for lighting at these units. BACKGROUND: The bulk of the research about nurses and lighting is focused on nighttime nursing, exploring the disruptions of nurses' circadian rhythm and maintaining alertness. The understanding of nurses' perception about lighting and its impact on nurses' task performance and patient examination remains imprecise. METHODS: This study used an online survey to ask a set of questions about lighting in medical-surgical units at five key locations including centralized nurse stations, decentralized nurse stations (DCNS), patient bedsides, patient bathrooms, and corridors from 393 survey participants. It then explored the survey findings in more depth through conducting focus groups with eight volunteer nurses. RESULTS: Lighting conditions at patient besides and DCNSs were significantly less desirable for nurses compared to other locations. A significant relationship between nurses' access to lighting controls (switches and dimmers) and satisfaction about the lighting environment was found. No significant relationship was observed between the individual characteristics of nurses (such as age, years of experience, etc.) and findings of this study. CONCLUSIONS: Thoughtful design of the lighting environment can improve nurses' satisfaction and perception about their working environment.

Speech intelligibility in hospitals.

Effective communication between staff members is key to patient safety in hospitals. A variety of patient care activities including admittance, evaluation, and treatment rely on oral communication. Surprisingly, published information on speech intelligibility in hospitals is extremely limited. In this study, speech intelligibility measurements and occupant evaluations were conducted in 20 units of five different U.S. hospitals. A variety of unit types and locations were studied. Results show that overall, no unit had "good" intelligibility based on the speech intelligibility index (SII > 0.75) and several locations found to have "poor" intelligibility (SII < 0.45). Further, occupied spaces were found to have 10%-15% lower SII than unoccupied spaces on average. Additionally, staff perception of communication problems at nurse stations was significantly correlated with SII ratings. In a targeted second phase, a unit treated with sound absorption had higher SII ratings for a larger percentage of time as compared to an identical untreated unit. Taken as a whole, the study provides an extensive baseline evaluation of speech intelligibility across a variety of hospitals and unit types, offers some evidence of the positive impact of absorption on intelligibility, and identifies areas for future research.

The sound environment in an ICU patient room--a content analysis of sound levels and patient experiences.

This study had two aims: first to describe, using both descriptive statistics and quantitative content analysis, the noise environment in an ICU patient room over one day, a patient's physical status during the same day and early signs of ICU delirium; second, to describe, using qualitative content analysis, patients' recall of the noise environment in the ICU patient room. The final study group comprised 13 patients. General patient health status data, ICU delirium observations and sound-level data were collected for each patient over a 24-hour period. Finally, interviews were conducted following discharge from the ICU. The sound levels in the patient room were higher than desirable and the LAF max levels exceed 55dB 70-90% of the time. Most patients remembered some sounds from their stay in the ICU and whilst many were aware of the sounds they were not disturbing to them. However, some also experienced feelings of fear related to sounds emanating from treatments and investigations of the patient beside them. In this small sample, no statistical connection between early signs of ICU delirium and high sound levels was seen, but more research will be needed to clarify whether or not a correlation does exist between these two factors.

Influence of a wearer's voice on noise dosimeter measurements.

In recent years, interest in personal noise exposure has expanded beyond a workplace safety measure to become an effective means of investigating physiological effects of the acoustic environment on an individual. This work investigates the effects of the wearer's voice as a possible dominant sound source on body-mounted noise dosimeters and develops methods to improve the application of dosimeter measurements in medium-level noise environments. Subjects experienced a controlled set of acoustic conditions while wearing a dosimeter. In each condition, sound pressure levels were recorded with and without the subject speaking controlled phrases. Three experimental variables were considered-room type, noise type, and noise level. All three variables had a statistically significant effect upon the contribution of speech to a dosimeter measurement; for example, noise level was shown to cause a change in speech contribution by as much as 5.5 dB between sequential levels. Based upon the analysis, a method of predicting the decibel contribution of a wearer's voice was developed. The results of this study can be used to estimate the effect of a wearer's voice on dosimeter measurements in medium-level noise environments.

The role of physical environment on student health and education in green schools.

The role of physical school environment on student health and education is becoming better understood. A growing body of literature indicates that improved physical environments in schools (e.g., indoor air quality, lighting, and acoustic conditions) can enhance student health outcomes. In parallel, the green building movement centers around designing buildings, including schools, that are more sustainable to decrease energy consumption, minimize environmental impact, and create healthier spaces for occupants. This paper synthesizes the findings from both green design studies and school outcomes studies to provide a systematic evaluation of the potential impacts of green school design features on student health outcomes. Three inter-related topics are covered in detail: (i) overview of the "green" concept, including existing guidelines for "greening" schools, attitudes toward green schools, and condition of the physical environments in non-green schools; (ii) potential effects of the physical environment on school children, including documentation of national statistics and summary of findings from school research studies; (iii) synthesis of findings, including a discussion of the knowledge gaps in the field of green school research and conclusions.

Soundscape evaluations in two critical healthcare settings with different designs.

Intensive care units (ICUs) have important but challenging sound environments. Alarms and equipment generate high levels of noise and ICUs are typically designed with hard surfaces. A poor sound environment can add to stress and make auditory tasks more difficult for clinicians. However few studies have linked more detailed analyses of the sound environment to nurse wellbeing and performance. This study is aimed at understanding the relationships between objective acoustic measures and self-reported nurse outcomes. Two 20-bed ICUs with similar patient acuity and treatment models were tested: A recently built neurological ICU and a 1980s-era medical-surgical ICU. The medical-surgical ICU was perceived as louder, more annoying, and having a greater negative impact of noise on work performance, health outcomes, and anxiety as compared to the neurological ICU. Surprisingly, there were little differences between two ICU sound environments based on traditional overall noise measures. The objective differences between the occupied sound environments in the two units only emerged through a more comprehensive analysis of the "occurrence rate" of peak and maximum levels, frequency content, and the speech interference level. Furthermore, mid-level transient sound occurrence rates were significantly and positively correlated to perceived annoyance and loudness levels.

Implications of human performance and perception under tonal noise conditions on indoor noise criteria.

This research investigated differences in task performance and perception under six non-time-varying ventilation-type background noise spectra with differing tonality. The results were related to five indoor noise criteria systems: noise criteria, balanced noise criteria, room criteria, room criteria mark II, and the A-weighted equivalent sound pressure level (L(Aeq)). These criteria systems are commonly used in the U.S. building industry, but concerns exist over whether they are appropriate for all noise situations. Thirty test subjects completed three types of performance tasks (typing, reasoning, and math) and answered questions about their perception of the indoor environment under each noise condition. Results showed that performance scores did not change significantly across the six noise conditions, but there were differences in subjective perception. For example, perception trends for tonality, annoyance, and distraction changed based on the frequency and prominence of discrete tones in noise. However, these perceptual changes were not fully reflected in the criteria level or spectral quality ratings. Additionally, task performance was related to subjective perception but not to criteria level predictions. As a result, the authors suggest that the current criteria should be modified to account for the frequency and prominence of tones in background noise.

Characterizing noise and perceived work environment in a neurological intensive care unit.

The hospital sound environment is complex. Alarms, medical equipment, activities, and ventilation generate noise that may present occupational problems as well as hinder recovery among patients. In this study, sound measurements and occupant evaluations were conducted in a neurological intensive care unit. Staff completed questionnaires regarding psychological and physiological reactions to the sound environment. A-weighted equivalent, minimum, and maximum (L(Aeq),L(AFMin),L(AFMax)) and C-weighted peak (L(CPeak)) sound pressure levels were measured over five days at patient and staff locations. Acoustical descriptors that may be explored further were investigated, including level distributions, restorative periods, and spectral content. Measurements near the patients showed average L(Aeq) values of 53-58 dB. The mean length of restorative periods (L(Aeq) below 50 dB for more than 5 min) was 9 and 13 min for day and night, respectively. Ninety percent of the time, the L(AFMax) levels exceeded 50 dB and L(CPeak) exceeded 70 dB. Dosimeters worn by the staff revealed higher noise levels. Personnel perceived the noise as contributing to stress symptoms. Compared to the majority of previous studies, this study provides a more thorough description of intensive care noise and aids in understanding how the sound environment may be disruptive to occupants.