Ambient noise levels in the chemotherapy clinic

Older adults' recognition of medical terminology in hospital noise

Word identification accuracy is modulated by many factors including linguistic characteristics of words (frequent vs. infrequent), listening environment (noisy vs. quiet), and listener-related differences (older vs. younger). Nearly, all studies investigating these factors use high-familiarity words and noise signals that are either energetic maskers (e.g., white noise) or informational maskers composed of competing talkers (e.g., multitalker babble). Here, we expand on these findings by examining younger and older listeners' speech-in-noise perception for words varying in both frequency and familiarity within a simulated hospital noise that has important non-speech information. The method was inspired by the real-world challenges aging patients can face in understanding less familiar medical terminology used by healthcare professionals in noisy hospital environments. Word familiarity data from older and young adults were collected for 800 medically related terms. Familiarity ratings were highly correlated between the two age groups. Older adults' transcription accuracy for sentences with medical terminology that vary in their familiarity and frequency was assessed across four listening conditions: hospital noise, speech-shaped noise, amplitude-modulated speech-shaped noise, and quiet. Listeners were less accurate in noise conditions than in a quiet condition and were more impacted by hospital noise than either speech-shaped noise. Sentences with low-familiarity and low-frequency medical words combined with hospital noise were particularly detrimental for older adults compared to younger adults. The results impact our theoretical understanding of speech perception in noise and highlight real-world consequences of older adults' difficulties with speech-in-noise and specifically noise containing competing, non-speech information.

Impact of occupational noise exposure on the hearing level in hospital staffs: a longitudinal study

The study aimed to evaluate the impact of occupational noise on hearing loss among healthcare workers using audiometry. A longitudinal study was conducted with a six-month follow-up period in a hospital with 21 participants, divided into high-noise-exposure (HNE) and low-noise-exposure (LNE) groups. Mean noise levels were higher in the HNE group (70.4 ± 4.5 dBA), and hearing loss was measured using pure-tone audiometry at baseline and follow-up. The HNE group had significantly higher mean threshold levels at frequencies of 0.25 kHz, 0.5 kHz, 4.0 kHz, and an average of 0.5, 1, 2, and 4 kHz (all p-values < 0.05) after the follow-up period. After adjusting for confounding factors, the HNE group had significantly higher hearing loss levels at 0.25 kHz, 0.5 kHz, and average frequencies of 0.5, 1, 2, and 4 kHz compared to the LNE group at the second measurement. Occupational noise levels above 65 dBA over six months were found to cause significant threshold changes at frequencies of 0.25 kHz, 0.5 kHz, and an average of 0.5-4.0 kHz. This study highlights the risk of noise-induced hearing loss among healthcare workers and emphasizes the importance of implementing effective hearing conservation programs in the workplace. Regular monitoring and assessment of noise levels and hearing ability, along with proper use of personal protective equipment, are crucial steps in mitigating the impact of occupational noise exposure on the hearing health of healthcare workers.

Evaluating the accuracy of speech to text applications for cochlear implant candidates during COVID-19

OBJECTIVES

Universal mask wearing due to COVID-19 has introduced barriers to clear communication. In hearing impaired individuals this can impact informed surgical consent. For cochlear implant candidates, who do not rely on sign language, real-time transcription with a stenographer (CART) is the gold-standard in assistive technologies. If CART is not available, speech to text (STT) applications have been advertised as solutions, but their transcription accuracy with or without an N95 mask is not well-established. Herein, we sought to investigate the transcription accuracy of three STT solutions for iPhone and compare their performance to the CART service at our institution.

METHODS

Three native English speakers and three non-native English speakers read two passages (a cochlear implant consent and the non-medical 'Rainbow passage') with and without an N95 mask. Error rates from the comparison of the transcript (from either the STT app or CART) with the original passage were calculated.

RESULTS

The CART service had the lowest error rate of all testing conditions (4.79-7.14%). Ava 24/7 (15.0 ± 9.49%) and the iPhone dictation (15.6 ± 6.65%) had significantly lower average error rates than the Live Transcribe (37.7 ± 20.3%) (P < 0.0001) application. Neither the presence of an N95 nor the type of passage had a statistically significant impact on the error rate.

CONCLUSION

CART should be used to augment communication with patients who are hard of hearing. If CART is not available, a STT application such as Ava 24/7 or the native iPhone dictation application may be considered, even in the context of medical terminology.

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.

Environmental noise levels in hospital settings: A rapid review of measurement techniques and implementation in hospital settings

BACKGROUND

Hospitals provide treatment to improve patient health and well-being but the characteristics of the care environment receive little attention. Excessive noise at night has a negative impact on in-patient health through disturbed sleep. To address this hospital staff must measure night-time environmental noise levels. Therefore, an understanding of environmental noise measurement techniques is required. In this review, we aim to 1) provide a technical overview of factors to consider when measuring environmental noise in hospital settings; 2) conduct a rapid review on the equipment and approaches used to objectively measured noise in hospitals and identify methodological limitations.

DESIGN

: A rapid review of original research articles, from three databases, published since 2008. Studies were included if noise levels were objectively measured in a hospital setting where patients were receiving treatment.

RESULTS

1429 articles were identified with 76 included in the review. There was significant variability in the approaches used to measure environmental noise in hospitals. Only 14.5% of studies contained sufficient information to support replication of the measurement process. Most studies measured noise levels using a sound level meter positioned closed to a patient's bed area in an intensive care unit.

CONCLUSION

: Unwanted environmental noise in hospital setting impacts negatively on patient and staff health and well-being. However, this literature review found that the approaches used to objectively measure noise level in hospital settings have been inconsistent and poorly reported. Recommendations on best-practice methods to measure noise levels in hospital environments are provided.

Noise peaks influence communication in the operating room. An observational study

Noise peaks are powerful distractors. This study focuses on the impact of noise peaks on surgical teams' communication during 109 long abdominal surgeries. We related measured noise peaks during 5-min intervals to the amount of observed communication during the same interval. Results show that noise peaks are associated with less case-relevant communication; this effect is moderated by the level of surgical experience; case-relevant communications decrease under high noise peak conditions among junior, but not among senior surgeons. However, case-irrelevant communication did not decrease under high noise level conditions, rather there was a trend to more case-irrelevant communication under high noise peaks. The results support the hypothesis that noise peaks impair communication because they draw on attentional resources rather than impairing understanding of communication. As case-relevant communication is important for surgical performance, exposure to high noise peaks in the OR should be minimised especially for less experienced surgeons. Practitioner Summary: This study investigated whether noise during surgeries influenced the communication within surgical teams. During abdominal surgeries, noise levels were measured and communication was observed. Results showed that high noise peaks reduced the frequency of patient-related communication, but did not reduce patient-irrelevant communication. Noise may negatively affect team coordination in surgeries.

Acoustic assessment of speech privacy curtains in two nursing units

Hospitals have complex soundscapes that create challenges to patient care. Extraneous noise and high reverberation rates impair speech intelligibility, which leads to raised voices. In an unintended spiral, the increasing noise may result in diminished speech privacy, as people speak loudly to be heard over the din. The products available to improve hospital soundscapes include construction materials that absorb sound (acoustic ceiling tiles, carpet, wall insulation) and reduce reverberation rates. Enhanced privacy curtains are now available and offer potential for a relatively simple way to improve speech privacy and speech intelligibility by absorbing sound at the hospital patient's bedside. Acoustic assessments were performed over 2 days on two nursing units with a similar design in the same hospital. One unit was built with the 1970s' standard hospital construction and the other was newly refurbished (2013) with sound-absorbing features. In addition, we determined the effect of an enhanced privacy curtain versus standard privacy curtains using acoustic measures of speech privacy and speech intelligibility indexes. Privacy curtains provided auditory protection for the patients. In general, that protection was increased by the use of enhanced privacy curtains. On an average, the enhanced curtain improved sound absorption from 20% to 30%; however, there was considerable variability, depending on the configuration of the rooms tested. Enhanced privacy curtains provide measureable improvement to the acoustics of patient rooms but cannot overcome larger acoustic design issues. To shorten reverberation time, additional absorption, and compact and more fragmented nursing unit floor plate shapes should be considered.

Proposed comprehensive ototoxicity monitoring program for VA healthcare (COMP-VA)

Prevention and rehabilitation of hearing loss and tinnitus, the two most commonly awarded service-connected disabilities, are high priority initiatives in the Department of Veterans Affairs (VA). At least 4,000 Veterans, most with significant hearing loss, will receive cisplatin this year, with more than half sustaining permanent hearing shift and nearly 40% developing new tinnitus. With improved survivability following cancer treatment, Veterans treated with cisplatin are approached with the dual goals of effective treatment and preserved quality of life. This article describes COMP-VA, a comprehensive ototoxicity monitoring program developed for VA patients receiving cisplatin. The program includes an individualized pretreatment prediction model that identifies the likelihood of hearing shift given cisplatin dose and patient factors. It supports both manual and automated hearing testing with a newly developed portable audiometer capable of performing the recommended procedures on the chemotherapy unit during treatment. It also includes objective methods for identifying outer hair cell changes and predicting audiogram changes using distortion-product otoacoustic emissions. We describe this program of evidence-based ototoxicity monitoring protocols using a case example to give the reader an understanding of how this program would be applied, along with a plan for future work to accomplish the final stages of program development.

An investigation of sound levels on intensive care units with reference to the WHO guidelines

Introduction

Patients in intensive care units (ICUs) suffer from sleep deprivation arising from nursing interventions and ambient noise. This may exacerbate confusion and ICU-related delirium. The World Health Organization (WHO) suggests that average hospital sound levels should not exceed 35 dB with a maximum of 40 dB overnight. We monitored five ICUs to check compliance with these guidelines.

Methods

Sound levels were recorded in five adult ICUs in the UK. Two sound level monitors recorded concurrently for 24 hours at the ICU central stations and adjacent to patients. Sample values to determine levels generated by equipment and external noise were also recorded in an empty ICU side room.

Results

Average sound levels always exceeded 45 dBA and for 50% of the time exceeded between 52 and 59 dBA in individual ICUs. There was diurnal variation with values decreasing after evening handovers to an overnight average minimum of 51 dBA at 4 AM. Peaks above 85 dBA occurred at all sites, up to 16 times per hour overnight and more frequently during the day. WHO guidelines on sound levels could be only achieved in a side room by switching all equipment off.

Conclusion

All ICUs had sound levels greater than WHO recommendations, but the WHO recommended levels are so low they are not achievable in an ICU. Levels adjacent to patients are higher than those recorded at central stations. Unit-wide noise reduction programmes or mechanical means of isolating patients from ambient noise, such as earplugs, should be considered.