Hospital noise is associated with adverse effects on patients and staff. Communication through overhead paging is a major contributor to hospital noise. Replacing overhead paging with smartphones through a clinical mobility platform has the potential to reduce transitory noises in the hospital setting, though this result has not been described. The current study evaluated the impact of replacing overhead paging with a smartphone-based clinical mobility platform on transitory noise levels in a labor and delivery unit. Transitory noises were defined as sound levels greater than 10 dB above baseline, as recorded by a sound level meter. Prior to smartphone implementation, 77% of all sound levels at or above 60 dB were generated by overhead paging. Overhead pages occurred at an average rate of 3.17 per hour. Following smartphone implementation, overhead pages were eliminated and transitory noises decreased by two-thirds (P < 0.001). The highest recorded sound level decreased from 76.54 to 57.34 dB following implementation. The percent of sounds that exceeded the thresholds recommended by the Environmental Protection Agency and International Noise Council decreased from 31.2% to 0.2% following implementation (P < 0.001). Replacement of overhead paging with a clinical mobility platform that utilized smartphones was associated with a significant reduction in transitory noise. Clinical mobility implementation, as part of a noise reduction strategy, may be effective in other inpatient settings.

Noise, or unwanted sound, has long been associated with adverse effects on sleep, as well as on cardiovascular, metabolic, and mental health.13  In addition to potential health impacts on hospitalized patients, noise is a known cause of patient dissatisfaction. To address these concerns, the World Health Organization (WHO), International Noise Council (INC), and Environmental Protection Agency (EPA) recommend maximum allowable sound level limits; however, sound levels in excess of these limits are well documented.4  Overhead paging, as a means of hospital communication, is a major contributor to noise, accounting for as much as 39% of disruptive noise in the hospital setting.58  Current recommendations to decrease unnecessary hospital noise include reducing or eliminating the use of overhead paging systems through implementation of mobile communication devices.8,9  Clinical mobility platforms have the potential to reduce noise by providing real-time patient information to mobile computers or smartphones while integrating communication modalities (e.g., text, telephony) for healthcare providers, thereby eliminating the need for overhead paging. Despite the emergence of mobile communication systems to replace overhead paging, a reduction in hospital noise levels has not been described.810 

We sought to evaluate the impact of mobile communication devices and clinical mobility on noise levels in the labor and delivery (LD) unit of an academic medical center. The legacy overhead paging system in our original LD unit involved broadcasts into the general staff work areas and individual patient rooms. Pilot data revealed that overhead pages accounted for sound levels that were 20 dB higher than baseline sound levels in patient rooms (Figure 1). During the construction of a new LD unit, communications that occurred with overhead paging were replaced with communication through a clinical mobility platform that utilized smartphones. We hypothesized that this mobile communication strategy would significantly decrease transitory noises (defined as the percent of sound levels >10 dB above median [baseline] sound levels).

Figure 1.

Pilot sound level data representing 187 continuous minutes of A-weighted sound levels (Leq). 1 indicates staff talking in hallway outside room, 2 indicates unidentifiable noise in hallway, 3 indicates cleaning in hallway, 4 indicates iPhone calendar alert in room, 5 indicates overhead page, and 6 indicates iPhone ringing in room at loudest setting.

Figure 1.

Pilot sound level data representing 187 continuous minutes of A-weighted sound levels (Leq). 1 indicates staff talking in hallway outside room, 2 indicates unidentifiable noise in hallway, 3 indicates cleaning in hallway, 4 indicates iPhone calendar alert in room, 5 indicates overhead page, and 6 indicates iPhone ringing in room at loudest setting.

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This study was conducted in an urban academic medical center that operates a high-risk birthing center and Level IV neonatal intensive care unit. The original LD unit included seven birthing rooms, three operating suites, two triage bays, three postoperative recovery bays, and an intermediate care bay. Communications among staff members involved an overhead paging system that was broadcast within patient rooms using Rauland Pillow Speakers (Rauland, Mount Prospect, IL) and in clinical work areas using Cisco desktop phones (Cisco Systems, Inc., San Jose, CA). Providers who were not in the LD unit were reached directly using Cisco mobile telephones with telephony capability only.

The new LD unit housed 12 birthing rooms, three operating suites, five triage rooms, and five postoperative recovery rooms. Communication that previously used overhead paging was replaced with a combination of modalities, all of which were received on Zebra TC51 smartphones (Zebra Technologies Corporation, Lincolnshire, IL). Emergency notifications (e.g., code blue) were sent to smartphones from Rauland Responder 5 Staff Terminals (Rauland, Mount Prospect, IL) mounted in each patient room. Other mechanisms for communications between providers included direct telephony between smartphones using Workforce Connect (Zebra Technologies Corporation) and secure text messaging using Extension Engage (Vocera Communications, Inc., San Jose, CA).

A convenience sample of ambient sound levels was recorded in three original patient rooms (epoch 1) and seven new patient rooms (epoch 2). All sounds were recorded using an NSRT_mk2 sound level meter data logger (Convergence Instruments, Sherbrooke, Canada) and measured with logarithmic decibel scale, in dBA, in order to best mimic human auditory sensitivity. The meter was placed at the head of the flat patient bed to approximate the position of a resting patient. Average sounds levels (Leq) were measured at 1-second intervals. An observer (C.A.H.) documented the occurrence and source of audible sounds within the room. Sounds produced by or as a result of the observer were removed from analysis to estimate the sound levels in an otherwise empty room with the door closed.

The primary outcome (i.e., percent of transitory noises) was compared using the chi-squared test. Additional comparisons between the two epochs included median Leq and the percent of time that Leq was greater than 35 dBA (WHO limit) and 45 dBA (EPA and INC limit). Comparisons of continuous variables were made using Mann-Whitney U tests, and comparisons of categorical values were made using the chi-squared test, as appropriate.

Convenience samples were obtained from July 2018 to February 2019. Totals of 14.68 hours and 14.87 hours of sound levels were collected during epochs 1 and 2, respectively. Overhead pages occurred at an average rate of 3.17 per hour during epoch 1. The sound levels attributed to overhead paging ranged from 49.64 to 76.54 dB (mean 63.37 dB). All events at sound levels of 60 dB or greater were generated by overhead paging (77%), vacuuming in the hallway (1.6%), and staff members talking in the hallway (21%).

Sound levels were significantly lower following implementation of smartphones, with a decrease in the highest sound level from 76.54 dB in epoch 1 to 57.34 dB in epoch 2 (Figure 2). Transitory noises decreased by two-thirds (from 0.3% in epoch 1 to 0.1% in epoch 2; Table 1).

Figure 2.

Sound levels were significantly lower (P < 0.001) following implementation of smartphones

Figure 2.

Sound levels were significantly lower (P < 0.001) following implementation of smartphones

Close modal
Table 1.

Comparison of transitory noise levels

Comparison of transitory noise levels
Comparison of transitory noise levels

The percent of sounds that were greater than 45 dB decreased from 31.2% in epoch 1 to 0.2% in epoch 2 (P < 0.001). All sound measurements in epoch 1 were greater than 35 dB, and this decreased to 90.8% in epoch 2 (P < 0.001).

Noise disturbance in the hospital setting remains a major source of dissatisfaction for patients and staff.4,11  Hospital noise is known to be associated with adverse physiologic changes and sleep disturbances, and these adverse effects have prompted ongoing assessment of patient perceptions on noise within their environment.9,12,13  Despite a unanimous call to reduce noise levels, sound levels generated by routine inpatient health care clearly have increased during the previous several decades.9,14  Among many identifiable sources of noise, overhead paging is a frequent contributor. Thus, replacing overhead paging with a mobile communication strategy has been recommended as a way to mitigate noise.58 

To the authors' knowledge, we are the first to report a significant reduction in sound levels by replacing overhead paging with mobile technology. The Women's Hospital in Baton Rouge, LA, sought to reduce overhead paging as part of a larger program to reduce noise levels.8  This was done by encouraging physicians to utilize cellular phones, supplying hands-free mobile communication devices for nurses, and providing beepers and mobile phones for other essential staff. Johnson and Thornhill8  described a greater than 50% reduction in the frequency of overhead pages. However, they did not investigate the impact on sound levels either before or after implementation of mobile communication.

Baevsky et al.10  reported on sound levels in a high-volume emergency department before and after the implementation of a wireless communication network. They found no statistically significant differences in decibel levels associated with their change. However, the instrument used for sound measurement in the study of Baevsky et al. averaged sound levels during a 10-second interval. Based on the pilot data reported in the current work, which was recorded with 1-second averaging, 10-second averaging likely would be too long to detect the brief but loud overhead pages. Our study demonstrated that replacement of overhead paging with a clinical mobility platform led to a two-thirds reduction in such transitory noises.

The ability to detect succinct, but loud, sounds in our environment was critical to determining the impact of overhead paging on noise. These sounds, which are markedly louder than the environmental background, constitute a pattern of noise referred to as intermittent noise. Consideration must be given to the type of noise being studied. Intermittent, continuous, impulsive, and low-frequency noises have varying characteristics, and their impact on annoyance, sleep, human performance, and health outcomes differ.1517  Intermittent noise is thought to be particularly distressing to patients, as the abrupt change in decibel level garners immediate attention and habituation may be less likely to occur.1820  Future studies of the effects of overhead paging on patients should consider the duration of sound occurrence and time interval between sound events, as differences may alter psychologic and physiologic human responses.

Due to the intermittent nature of overhead paging noise, and as a means to control for differences in construction acoustics, we chose to evaluate for a reduction in sound levels greater than 10 dB above baseline. It is important to recognize that the A-weighted scale used in our study is logarithmic, where each 10-dB increase approximates a doubling in perceived sound, thereby making the elimination of overhead paging all the more significant. The highest documented sound level in our study was attributed to overhead paging and reached a sound level consistent with the noise generated by a vacuum cleaner. In our sample, overhead paging accounted for a small fraction of sound overall but contributed to 89% of sound levels that are in a range known to cause annoyance.21 

A call for noise reduction within the medical literature has been ongoing for nearly three decades, and relatively few studies have been able to demonstrate positive results.9,20  Proposed mechanisms to reduce noise include utilization of single patient room design, application of sound-absorbing or -masking materials, and reduction of noise-generating sources. The first two approaches may be challenged by the scale of construction projects with respect to cost and time. Consideration of environmental materials as part of a sound-reduction program may be more easily incorporated into new hospital construction, though less feasible for older, existing structures. Therefore, a hospital's most practical approach may be to reduce noise-generating sources. The number of noise-generating sounds in patient care areas is increasing. Some sounds are mechanical in nature (e.g., ventilation systems, computers, equipment) and others are behavioral (e.g., staff talking, doors closing).7  Behavioral modification for the purpose of noise reduction has been studied with limited results.4 

The implementation of “quiet hours” in patient care areas has resulted in reduced noise levels and improved sleep.11  However, behavioral modification has its challenges. Unfortunately, the unpredictable realities of patient care may not always be compatible with scheduled quiet times. Anecdotally, adherence to quiet hours requires frequent re-education for visitors and staff. The extent to which quiet hours are effective and sustainable in a busy inpatient environment is not entirely understood. Efforts to reduce noise in the hospital setting must address the additional sources of noise that were observed in our study with an emphasis on sustainability.

In addition to reducing the most disruptive noise in our unit, replacing overhead paging through a clinical mobility platform is inherently sustainable because its design is compatible with the clinical workflows of our staff. Although our staff have access to an overhead paging system, as a tertiary backup communication mechanism during planned and unplanned downtimes, no overhead pages have been executed in the first year since implementing smartphones for communication.

Implementation of clinical mobility platforms to eliminate overhead paging requires attentive planning. The combination of devices and systems described in this article are specific to the authors' medical center. In general, device selection is dependent on a number of factors and likely will be tailored to the institution. From the physical aesthetic of the handset to the information technology (IT) security features, careful consideration must be given to multiple aspects of smartphones and their clinical use. In this case, clinical alarms are managed through a third-party system that receives and routes alarms from nurse call and clinical monitors. Value is added to this platform, as it can expand to include other systems that send alarms. Such alarms can be routed to targeted recipients, imparting the ability to acknowledge receipt by the end user. Integrating nurse call, clinical monitors, and handsets required extensive planning meetings with clinicians, manufacturers, IT, and clinical engineering.

Communication among these systems enables shift-based patient assignments within the nurse call system to connect with the clinical monitors to the handsets. Of note, handsets needed to be sufficiently robust to be dropped, to be cleaned with standard sanitizing wipes between shifts, and to allow battery swapping at any time during a shift. IT needs to be engaged to manage the devices on a Wi-Fi network with adequate quality of service. The devices are controlled by a mobile management control platform (SOTI Inc., Mississauga, Ontario). This enables all events and activities on handsets to be tracked fully for audit purposes. It also controls the handset functions that are available to users, limiting them to the clinical applications and alarms appropriate to their specific role. The control system restricts the handsets to only operate on the institution's Wi-Fi network. With a robust control platform and a programmable operating system, the expansion of the platform to other clinical and nonclinical communications makes it possible to continue to add utility to the platform beyond its initial investment.

The current study had several limitations. Primarily, data were collected only during day shifts. Therefore, we do not know the prevalence of transitory sound levels during the night shift or how those sounds would be affected by the elimination of overhead paging. In a birthing unit, typical day/night sleep patterns may be less relevant due to the frequent awakenings of newborns for basic needs. Given the frequent maternal sleep disruptions imposed by newborn feeding needs, any opportunity to reduce noise and promote uninterrupted sleep during the daytime or nighttime is essential. Patients on maternity wards may be especially troubled by disruptive sound levels due to the fatigue associated with labor, childbirth, and newborn sleep patterns.22,23  In addition, even reduced noise during daytime hours has been shown to have beneficial effects on sleep in other hospitalized populations.11 

Second, we do not know how the reduction in transitory noises has affected patients in terms of self-reported satisfaction or sleep quality. To capture baseline sound levels, we were only able to record data from available empty rooms. Due to this convenience sampling, we were unable to control for factors that may have led to overall differences in noise or unit activity level. However, it should be stated that the number of births in our medical center increased in the year following implementation (from 1,738 to 1,817), suggesting that the number of potentially noise-generating clinical workflows were not decreased.

Because data from our two epochs were obtained in different units with unique structural and mechanical characteristics, we are unable to demonstrate that improvements in patient sleep patterns or overall satisfaction were independently related to the absence of overhead paging. In fact, overall baseline sound levels were significantly lower in epoch 2, suggesting that our choice of construction materials played a substantial role in reducing baseline sound levels. This also is an important finding because we were able to achieve baseline sound levels below the EPA and INC recommended thresholds.

Last, the architectural configurations of the two distinct LD units were different, which may have led to differences in the likelihood of sound exposures. Of note, the overall square footage and number of rooms were greater in the unit representing epoch 2. This environment allowed for a greater number of patients and clinical activities, potentially increasing the overall noise burden in epoch 2. However, this was not our observation.

Our study recorded sound levels in empty patient rooms, which did not include the use of patient care equipment. Equipment such as intravenous infusion pumps, cardiorespiratory monitors, and feeding pumps obviously generate a notable percentage of noise due to their associated alerts and alarms.5,24  Fortunately, many medical device manufacturers are developing products that can communicate alarm data within a clinical mobility platform. Clinical mobility has the potential to reduce patient exposure to noise from alarms by rapidly transmitting these notifications to staff members who may not be present at the patient bedside.

Aside from noise reduction, an additional benefit of communicating alerts and alarms through smartphones is that communication can be easily acknowledged by the receiver, with escalating messages generated in instances where the communication is not acknowledged. This may provide enhanced safety and accountability for communication compared with overhead pages, which have no inherent escalation pattern. Additional potential benefits include optimization of medication administration and patient throughput, as these particular devices allow for medication and patient bar code scanning. Further investigation in this area is warranted as more medical equipment and supplies are integrated into clinical mobility platforms.

Replacement of overhead paging communication through a clinical mobility platform that utilized smartphones was associated with a significant reduction in transitory noise. Clinical mobility implementation, as part of a noise reduction strategy, may be effective in other inpatient settings.

1.
Eriksson
C
,
Pershagen
G
,
Nilsson
M.
Biological Mechanisms Related to Cardiovascular and Metabolic Effects By Environmental Noise.
www.euro.who.int/__data/assets/pdf_file/0004/378076/review-noise-bio-effects-eng.pdf?ua=1.
Accessed May 20, 2020
.
2.
World Health Organization.
Night Noise Guidelines for Europe
.
Copenhagen
,
2009
; www.euro.who.int/__data/assets/pdf_file/0017/43316/E92845.pdf.
Accessed Nov. 6, 2018
.
3.
Berglund
B
,
Lindvall
T
,
Schwela
DH
(
Eds
.).
Guidelines for Community Noise
. www.who.int/iris/handle/10665/66217.
Accessed Nov. 6, 2018
.
4.
Konkani
A
,
Oakley
B.
Noise in hospital intensive care units: a critical review of a critical topic
.
J Crit Care
.
2012
;
27
(
5
):
522.e1
9
.
5.
Wallis
L.
Hospital noise puts patients at risk
.
Am J Nurs
.
2012
;
112
(
4
):
17
.
6.
Yoder
JC
,
Staisiunas
PG
,
Meltzer
DO
,
et al
.
Noise and sleep among adult medical inpatients: far from a quiet night
.
Arch Intern Med
.
2012
;
172
(
1
):
68
70
.
7.
Davenny
B.
Auditory assistance: strategies to reduce hospital noise problems
.
Health Facil Manage
.
Jan
2010
;
23
(
1
):
16
9
.
8.
Johnson
PR
,
Thornhill
L.
Noise reduction in the hospital setting
.
J Nurs Care Qual
.
2006
;
21
(
4
):
295
7
.
9.
Joseph
A
,
Ulrich
R.
Sound Control for Improved Outcomes in Healthcare Settings
. www.healthdesign.org/system/files/Joseph_Sound%20Control_2007.pdf.
Accessed May 20, 2020
.
10.
Baevsky
RH
,
Lu
MY
,
Smithline
HA.
The effectiveness of wireless telephone communication technology on ambient noise level reduction within the ED
.
Am J Emerg Med
.
2004
;
22
(
4
):
317
8
.
11.
Dennis
CM
,
Lee
R
,
Woodard
EK
,
et al
.
Benefits of quiet time for neuro-intensive care patients
.
J Neurosci Nurs
.
2010
;
42
(
4
):
217
24
.
12.
Darbyshire
JL.
Excessive noise in intensive care units
.
BMJ
.
2016
;
353
:
i1956
.
13.
NVW Editorial Staff.
Reducing Noise at the Hospital
.
Noise & Vibration Worldwide
.
2007
;
48
(
11
):
151
3
.
14.
Busch-Vishniac
IJ
,
West
JE
,
Barnhill
C
,
et al
.
Noise levels in Johns Hopkins Hospital
.
J Acoust Soc Am.
2005
;
118
(
6
):
3629
45
.
15.
Thiesse
L
,
Rudzik
F
,
Spiegel
K
,
et al
.
Adverse impact of nocturnal transportation noise on glucose regulation in healthy young adults: effect of different noise scenarios
.
Environ Int
.
2018
;
121
(
Pt 1
):
1011
23
.
16.
Nassiri
P
,
Monazam
M
,
Fouladi Dehaghi
B
,
et al
.
The effect of noise on human performance: a clinical trial
.
Int J Occup Environ Med
.
2013
;
4
(
2
):
87
95
.
17.
Brink
M
,
Schaffer
B
,
Vienneau
D
,
et al
.
A survey on exposure-response relationships for road, rail, and aircraft noise annoyance: differences between continuous and intermittent noise
.
Environ Int
.
2019
;
125
:
277
90
.
18.
Pope
D.
Decibel levels and noise generators on four medical/surgical nursing units
.
J Clin Nurs
.
2010
;
19
(
17–18
):
2463
70
.
19.
Lawson
N
,
Thompson
K
,
Saunders
G
,
et al
.
Sound intensity and noise evaluation in a critical care unit
.
Am J Crit Care
.
2010
;
19
(
6
):
e88
98
.
20.
Grumet
GW.
Pandemonium in the modern hospital
.
N Engl J Med
.
1993
;
328
(
6
):
433
7
.
21.
Buelow
M.
Noise level measurements in four Phoenix emergency departments
.
J Emerg Nurs
.
2001
;
27
(
1
):
23
6
.
22.
Adatia
S
,
Law
S
,
Haggerty
J.
Room for improvement: noise on a maternity ward
.
BMC Health Serv Res
.
2014
;
14
:
604
.
23.
Hughes Driscoll
CA
,
Pereira
N
,
Lichenstein
R.
In-hospital Neonatal Falls: An Unintended Consequence of Efforts to Improve Breastfeeding
.
Pediatrics
.
2019
;
143
(
1
):
e20182488
.
24.
Darbyshire
JL
,
Young
JD.
An investigation of sound levels on intensive care units with reference to the WHO guidelines
.
Crit Care
.
2013
;
17
(
5
):
R187
.

Author notes

Colleen A. Hughes Driscoll, MD, is an assistant professor of pediatrics at the University of Maryland School of Medicine in Baltimore, MD. Email: cdriscoll@som.umaryland.edu Corresponding author

Michael Cleveland, RCDD, NTS, OSP, is an associate at Phase Shift Consulting in Columbia, MD. Email: mcleveland@phaseshift.com

Samuel Gurmu is a clinical engineering information technology manager at the University of Maryland Medical Center in Baltimore, MD. Email: sgurmu@umm.edu

Sarah Crimmins, DO, is an assistant professor of obstetrics, gynecology, and reproductive medicine at the University of Maryland School of Medicine in Baltimore, MD. Email: scrimmins@som.umaryland.edu

Dina El-Metwally, MB, BCh, PhD, is an associate professor of pediatrics at the University of Maryland School of Medicine in Baltimore, MD, and a professor of pediatrics at the Suez Canal University in Ismailia, Egypt. Email: dmetwally@som.umaryland.edu