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Sleep Disruption due to Hospital Noises: A Prospective Evaluation

Orfeu M. Buxton, PhD; Jeffrey M. Ellenbogen, MD; Wei Wang, PhD; Andy Carballeira, BM; Shawn O'Connor, BS; Dan Cooper, BS; Ankit J. Gordhandas, SB; Scott M. McKinney, BA; and Jo M. Solet, PhD
[+] Article, Author, and Disclosure Information

From Harvard Medical School, Brigham and Women's Hospital, Massachusetts General Hospital, and Berklee College of Music, Boston; Cambridge Health Alliance, Cambridge; and Cavanaugh Tocci Associates, Sudbury, Massachusetts.

Acknowledgment: The authors thank Jenny Lai Olsen, Margaret Merlino, Karen Gannon, Leah Rondon, Vanessa Castro, Carolina Smales, Deirdre McLaren, and James Porter for technical assistance; Peg Toro, audiologist, for consultation on screening for normal hearing; and Drs. Dean M. Hashimoto, John W. Cronin, and Matt Travis Bianchi for helpful comments on the manuscript.

Grant Support: This study was funded by investigator-initiated grants (Dr. Solet) from the Academy of Architecture for Health, the Facilities Guidelines Institute, and The Center for Health Design. Sleep laboratory work was completed through the generosity of Massachusetts General Hospital and with acoustic consultation by Cavanaugh Tocci Associates.

Potential Conflicts of Interest: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M11-1159.

Reproducible Research Statement:Study protocol, data set, and statistical code: Available from Dr. Buxton (e-mail, orfeu_buxton@hms.harvard.edu). Execution of a materials transfer agreement is required for the transfer of data.

Requests for Single Reprints: Orfeu M. Buxton, PhD, 221 Longwood Avenue, BLI438-K, Boston, MA 02115; e-mail, orfeu_buxton@hms.harvard.edu.

Current Author Addresses: Dr. Buxton: 221 Longwood Avenue, BLI438-K, Boston, MA 02115.

Dr. Ellenbogen: Wang ACC 720, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02114.

Dr. Wang: 221 Longwood Avenue, BLI438-M, Boston, MA 02115.

Mr. Carballeira: 10 Upton Street, Cambridge, MA 02139.

Mr. O'Connor: 3535 Market Street, Room 1514, Philadelphia, PA 19104.

Mr. Cooper: 221 Longwood Avenue, BLI2-230, Boston, MA 02115.

Mr. Gordhandas: 15 Parkman Street, WACC 7, Boston, MA 02114.

Mr. McKinney: ICME, Suite 053B, Huang Engineering Center, 475 Via Ortega, Stanford, CA 94305.

Dr. Solet: 15 Berkeley Street, Cambridge, MA 02138.

Author Contributions: Conception and design: O.M. Buxton, A. Carballeira, J.M. Solet.

Analysis and interpretation of the data: O.M. Buxton, J.M. Ellenbogen, W. Wang, A. Carballeira, A. Gordhandas, S.M. McKinney, J.M. Solet.

Drafting of the article: O.M. Buxton, J.M. Ellenbogen, S. O'Connor, D. Cooper, S.M. McKinney, J.M. Solet.

Critical revision of the article for important intellectual content: O.M. Buxton, J.M. Ellenbogen, A. Carballeira, S. O'Connor, D. Cooper, J.M. Solet.

Final approval of the article: O.M. Buxton, A. Carballeira, S. O'Connor, D. Cooper, A. Gordhandas, J.M. Solet.

Provision of study materials or patients: O.M. Buxton, J.M. Ellenbogen, D. Cooper, J.M. Solet.

Statistical expertise: W. Wang.

Obtaining of funding: O.M. Buxton, J.M. Ellenbogen, J.M. Solet.

Administrative, technical, or logistical support: O.M. Buxton, J.M. Ellenbogen, A. Carballeira, S. O'Connor, J.M. Solet.

Collection and assembly of data: O.M. Buxton, J.M. Ellenbogen, A. Carballeira, S. O'Connor, D. Cooper, J.M. Solet.

Ann Intern Med. 2012;157(3):170-179. doi:10.7326/0003-4819-156-12-201208070-00472
Text Size: A A A

Background: Sleep plays a critical role in maintaining health and well-being; however, patients who are hospitalized are frequently exposed to noise that can disrupt sleep. Efforts to attenuate hospital noise have been limited by incomplete information on the interaction between sounds and sleep physiology.

Objective: To determine profiles of acoustic disruption of sleep by examining the cortical (encephalographic) arousal responses during sleep to typical hospital noises by sound level and type and sleep stage.

Design: 3-day polysomnographic study.

Setting: Sound-attenuated sleep laboratory.

Participants: Volunteer sample of 12 healthy participants.

Intervention: Baseline (sham) night followed by 2 intervention nights with controlled presentation of 14 sounds that are common in hospitals (for example, voice, intravenous alarm, phone, ice machine, outside traffic, and helicopter). The sounds were administered at calibrated, increasing decibel levels (40 to 70 dBA [decibels, adjusted for the range of normal hearing]) during specific sleep stages.

Measurements: Encephalographic arousals, by using established criteria, during rapid eye movement (REM) sleep and non-REM (NREM) sleep stages 2 and 3.

Results: Sound presentations yielded arousal response curves that varied because of sound level and type and sleep stage. Electronic sounds were more arousing than other sounds, including human voices, and there were large differences in responses by sound type. As expected, sounds in NREM stage 3 were less likely to cause arousals than sounds in NREM stage 2; unexpectedly, the probability of arousal to sounds presented in REM sleep varied less by sound type than when presented in NREM sleep and caused a greater and more sustained elevation of instantaneous heart rate.

Limitations: The study included only 12 participants. Results for these healthy persons may underestimate the effects of noise on sleep in patients who are hospitalized.

Conclusion: Sounds during sleep influence both cortical brain activity and cardiovascular function. This study systematically quantifies the disruptive capacity of a range of hospital sounds on sleep, providing evidence that is essential to improving the acoustic environments of new and existing health care facilities to enable the highest quality of care.

Primary Funding Source: Academy of Architecture for Health, Facilities Guidelines Institute, and The Center for Health Design.


noise ; sleep ; arousal ; sound ; acoustics


Grahic Jump Location
Figure 1.

Study flow diagram.

EKG = electrocardiogram.

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Figure 2.

Schematic diagram of study protocol.

dBA = decibels, adjusted for the range of normal hearing; EEG = electroencephalogram; EMG = electromyogram; N2 = non-REM sleep stage 2; REM = rapid eye movement. Top. The solid vertical lines along the x-axis indicate stimuli evoking EEG arousals, and a sample of 4 noises is shown. Each color represents a different sound type. Ten-second noises were evaluated for their probability to induce a cortical arousal at increasing sound levels in varying stages of sleep and presented once per 30-second sleep epoch (while sleep stage was stable) until an arousal occurred, sleep stage changed, or the 70-dBA maximum was reached. Bottom. A typical sound-induced arousal from stage N2 sleep, as measured by polysomnography. Arousals are defined by their appearance on the EEG (the right frontal lead F3 shown here), characterized by an abrupt shift of frequency that lasts at least 3 seconds. Arousals during REM sleep require a concurrent increase in submental EMG activity. This transient arousal lasted for approximately 8.5 seconds before sleep resumed.

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Figure 3.

Sleep disruption due to noise stimuli presented during sleep, by stage of sleep.

Arousal probability of sound stimuli presented in sleep stages N2, N3, and REM. Ten-second noises were introduced during sleep stages N2, N3, and REM to evaluate their propensity to disturb sleep. Once a stable stage of at least 90 seconds was reached, noises were initiated at sound levels of 40 dBA (equivalent continuous A-weighted [adjusted for the range of normal human hearing] sound pressure level, averaged over the 10-second stimulus duration) and presented every 30 seconds in 5-dBA increments until an arousal occurred or the 70-dBA exposure level was reached. dBA = decibels, adjusted for the range of normal hearing; HR = heart rate; IV = intravenous; LA10, 10-s = sound pressure level, averaged over the 10-second stimulus duration, exceeded 10% of the time; N2 = non-REM sleep stage 2; N3 = non-REM sleep stage 3; REM = rapid eye movement. Top. Mean arousal probabilities for stimuli presented during sleep stages N2, N3, and REM versus presented sound level and adjusted for stimulus and body position (see Methods section). Middle. Mean arousal probabilities for individual noise stimuli by sleep stage, adjusted for body position. Bottom. Changes in the median HR during nonspontaneous, noise-induced arousals are aligned by the time of the peak HR response and expressed relative to the average HR in the 10 seconds preceding the arousals in sleep stages N2, N3, and REM. The vertical lines represent the median times of arousal onset (with CIs) before that peak.

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Figure 4.

Electroencephalogram arousal probabilities for noise stimuli presented, adjusted for body position.

See Methods section. dBA = decibels, adjusted for the range of normal hearing; IV = intravenous; LA10, 10-s = sound pressure level, averaged over the 10-second stimulus duration, exceeded 10% of the time; N2 = non-REM sleep stage 2; N3 = non-REM sleep stage 3; REM = rapid eye movement.

Grahic Jump Location




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Improving Patient Sleep in Hospitals: More than Noise
Posted on June 22, 2012
Vineet Arora MD MAPP, Howard Chiou, Claire Beveridge
University of Chicago and Emory University
Conflict of Interest: We acknowledge funding from the National Institutes on Aging through a Short-Term Aging-Related Research Program (1 T35 AG029795), National Institute on Aging career development award (K23AG033763), and a National Institutes on Aging Clinical Translational Sciences Award (UL1 RR024999).

We commend Buxton and colleagues for a thought-provoking and rigorous study that examines the association between hospital noise and heart rate in a cohort of healthy volunteers (1). This work highlights the importance of studies of actual hospitalized patients, especially given that nearly half of hospitalized Medicare patients report that their room was not kept quiet at night (2). Using objective measures of sound and sleep in a cohort of medical inpatients, we have shown that hospitalization is a time of acute sleep loss, with patients suffering two hours less sleep than they receive at home. Moreover, each hour of in-hospital sleep loss, morning systolic blood pressure was increased by 6mmHg (2). In a follow-up study, hospital noise levels in actual patient rooms was far from acceptable— patients in the loudest rooms lost over an hour of sleep than those in the quietest rooms, with peak noise levels equivalent to chain saws (3). The study by Buxton et al. prompted us to examine the association between sleep loss and heart rate as measured by ambulatory blood pressure monitors from a pilot of 16 hospitalized older patients. We found a relationship between sleep efficiency, a measure of fragmentation, and higher heart rates (as measured by continuous ambulatory blood pressure monitors) that is independent of noise level. This is important since sleep fragmentation in hospitals is not only due to noise, but also due to other medical factors, such as vital signs or blood draws. Therefore, while improving hospital noise may be one part of improving hospital sleep and patient outcomes, it is also critical to consider redesigning nursing protocols to prevent stable patients from being awoken for routine measurement of vital signs and lab draws that could be delayed until morning. Although randomized controlled studies are lacking, research suggests there may be limited or no value for routine blood pressure measurements in a wide variety of patient categories (4). Unfortunately, changing the time-honored tradition of every 4 hour vital signs and routine lab draws will require intensive culture change for hospital staff, as well as patient empowerment to advocate for their own sleep in the hospitals. Given the potential effect of in-hospital sleep loss on physical function in surgical patients (5), future studies should also explore the association between sleep and functional recovery after hospitalization, especially in older adults hospitalized on medical wards who are at high risk for functional decline.


(1) Buxton OM, Ellenbogen JM, Wang W, Carballeira A, O'Connor S, Cooper D, Gordhandas AJ, McKinney SM, Solet JM. Sleep Disruption Due to Hospital Noises: A Prospective Evaluation. Ann Intern Med. 2012 Jun 11. [Epub ahead of print]

(2) Arora VM, Chang KL, Fazal AZ, Staisiunas PG, Meltzer DO, Zee PC, Knutson KL, Van Cauter E. Objective sleep duration and quality in hospitalized older adults: associations with blood pressure and mood. J Am Geriatr Soc. 2011;59(11):2185-6.

(3) Yoder JC, Staisiunas PG, Meltzer DO, Knutson KL, Arora VM. Noise and sleep among adult medical inpatients: far from a quiet night. Arch Intern Med. 2012;172(1):68-70.

(4) Conen D, Leimenstoll BM, Perruchoud AP, Martina B. Routine blood pressure measurements do not predict adverse events in hospitalized patients. Am J Med. 2006;119(1):70.e17-22.

(5) Redeker NS, Ruggiero JS, Hedges C. Sleep is related to physical function and emotional well-being after cardiac surgery. Nurs Res. 2004;53(3):154-62.

Engage Patients in Meeting Their Sleep Needs
Posted on June 26, 2012
Susan Frampton, PhD
Conflict of Interest: None Declared

The implications of sleep disruption on hospitalized patients are thoroughly documented in this article, which establishes that protecting sleep is a key goal in advancing the quality of care for inpatient medicine. Appreciation for the benefits of rest hardly requires any specialized clinical experience, however. Patients, too, know inherently that rest is good medicine. Focus groups with thousands of patients have established sleep and a serene auditory environment as a patient priority.

Sleep as part of the quality equation is consistent with a growing emphasis on patient-centered care, defined by Planetree as "…care organized around the patient. It is a model in which providers partner with patients and families to identify and satisfy the full range of patient needs and preferences."

Patient-centered hospitals around the world are considering the hospital experience from the patient perspective to develop strategies for minimizing noise emanating from hospital equipment, personnel and external causes—many of which are highlighted in this article.

Minimizing noise, however, is only half of the sleep quality equation. The restorative potential of sleep will only be optimized when noise reduction strategies are coupled with proactive systems and practices that promote partnerships between patients and caregivers to meet patients’ sleep needs. Examples include a implementing a flexible schedule for routine procedures such as blood draws and vital signs that accommodates patients’ sleep patterns. The Department of Veterans Affairs New Jersey Health Care System, a member of the Planetree Membership Network, has recently begun administering a sleep assessment on admission which enables patients to make known their sleep patterns and preferences for non-pharmacological sleep aids, such as sleep masks, sound machines, warmed blankets, and aromatherapy. This sleep assessment opens up a dialogue between patients and caregivers about the importance of sleep and becomes the foundation for supporting more comfortable sleep for patients that will yield the well-documented health benefits of uninterrupted rest.

To advance the quality of sleep, and by extension health care quality in the broadest sense, providers must not only work to reduce noise, but even more importantly, to engage patients in making their sleep needs and preferences known.

Frampton, S.B., Guastello, S. and others. Patient-Centered Care Improvement Guide. Planetree and Picker Institute: Derby, CT and Camden, ME, 2008.Ibid, pg. 4.

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Sleep Disruption due to Hospital Noises

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