Publication/Presentation Date

7-25-2014

Abstract

Abstract

This program was named the HUSH project and is funded by the American Association of Critical Care Nurses. H.U.S.H. has come to stand for "Helping Understand Sleep Heals". The purpose of the current study was to evaluate the noise levels of the various alarms in the ICU and to determine if noise levels had an impact on the quality of sleep the patient received at night. This project looked at 260 patients out of a total of 430 patients in the ICU with an average age of 67 years old in a 20-bed Intensive Care Unit at Lehigh Valley Hospital-Muhlenberg. During this project, five different evaluation tools were used to measure areas of the project. These tools include: HCAPHS, manual alarm counts, decibel meter readings, Phillips Monitor Alarm Trigger printouts, and the Richard-Campbell Sleep Study. The results had no significant difference from the pre-launch and launch, except for a 16.% decrease in false alarms. Noise is still a huge issue in hospitals and is a factor in sleep, but decibel levels are still too high with alarms being the leading cause.

Keywords: alarms, decibel meter readings, sleep, HUSH, noise

Sleep is a time for the body to restore elements lost and recuperate after stress. For many patients in the Intensive Care Units (ICUs) at hospitals, sleep is not always obtainable in these noisy and chaotic environments. This can become an issue for the critically-ill patients that are trying to recover from a traumatic, acute episode, and "it can take as little as 24 to 48 hours for the body to begin reacting negatively to a lack of sleep in patients" (Dennis, Lee, Knowles Woodard, Szalaj, & Walker, 2010). In fact, one study found that patients were disturbed on average every 20 minutes, even while they were sleeping (Dennis. et al., 2010). A lack of sleep has been shown to play a part in falls, confusion, and increased medication and restraint use for patients (Mazer, 2006, p. 145). Furthermore, ICU patients are at a higher risk of developing delirium (Olson, 2012).

A large reason for sleep disturbances in hospitals can be attributed to noise levels. According to the United States Environmental Protection Agency (EPA), the guidelines for background noise are 45 decibels (dβ) during the day and 35 dβ at night in patient rooms. Research has shown that hospital noise levels exceed this recommended guideline of the EPA, making sleep harder to come by in an already hectic environment (Kahn, et al., 1998). The Help Understand Sleep Heals (H.U.S.H.) project, took place in the 20-bed ICU of Lehigh Valley Hospital-Muhlenberg over a 16-month period. The project was launched at the beginning of September 2013 and will conclude at the end of July 2014. This study includes a population with an average age of 67 years old, and consists of sample 260 patients out of a total of 430 patients admitted to the ICU within that 16-month period. The purpose of the current study was to decrease the level of noise and the number of controllable alarms to help aid in increased patient and staff satisfaction.

Methods

The H.U.S.H. Project is a two stage project. The first stage is to evaluate the decibel levels of alarms that are used in the ICU, and the number of alarms that sound during a two hour time period. The second stage is assessing the patient's perception of sleep along with the nurse's perception of the patient's sleep. During the week the project was first launched, the ICU at Muhlenberg introduced "Quiet Time" to the unit between the hours of 1 o'clock to 4 o'clock a.m., and 2 o'clock to 4 o'clock p.m. Actions taken during "Quiet Time" hours include: dimmed lights, visitors may be asked to leave, television volumes are reduced, headsets and ear buds may be used, staff will limit nursing activities during these hours, patient's door will be closed, and therapeutic interventions will be performed in a quiet manner. During this first week, the unit eliminated hallway ventilator alarms that had the potential to average around 86 to 90 plus decibels.

In the first stage, manual alarm counts were done in two hour sessions. The observer would station themselves at either the front or back monitors. Each monitoring sections received information for 12 rooms with four of the rooms overlapping between stations. The observer would use a chart, shown in Figure 1, that listed all the alarms that would be monitored. These alarms included: ventilators and BiPAP, EKGs, blood pressure, pulse ox, IV pumps, apnea, bed alarms, patient call bells, loud staff, tubing station, and other miscellaneous alarms that are too uncommon to be grouped into its own category. During the two hours period, the observer would time the duration of the alarms going off and then determine whether it was a "true" or "false" alarm. Meanwhile, there would be a SL120 decibel counter located at the monitoring station. The decibel counter would be read at the beginning and the end of the two hour period, as well as fifteen minute intervals in between. At the end of the two hour reading, the observer would access the information in the monitors and printout the Phillip Monitor Alarm Trigger Printout. This tool calculated the amount of red, yellow, and bed alarms that registered for each room.

The second stage of the project includes the Richard-Campbell Sleep Study Questionnaire, and HCAPH scores. At night, the Richard-Campbell Sleep Study Questionnaire would be given to the nurse and any patient who is not on any type of ventilator, and who is awake and oriented to time, place, and person. The observer would hand out the surveys to the night nurse and their patient at eleven o'clock p.m. to either even or odd rooms for evaluation of the upcoming night's sleep. The rooms used per night was determined by whether the date was an even or odd number. For example, if the date was the twenty-second, then all the even room numbers would be given the survey. Each survey received a code that was made up of the date, room number, and participant. For instance, the night the survey is given out is December 22, 2013, and the patient that will be receiving the survey is in room 234. The code for the matching survey would be 12221334-P. The survey code for the nurse of that same room would be 12221334-N. The Richard-Campbell Sleep Study Questionnaire is a five question survey with a sixth question being optional, shown in Figure 2. In order to answer the survey, the patient must put an "X" on the 100 centimeter line below each question. The placement of the "X" should correspond to the perception of the participant of the survey, whether that be the nurse or the patient. In order to calculate the survey into a numerical value, the observer would draw a line through the center of the "X", and then measure the 100 cm line to the vertical line running though the "X". On the other hand, the HCAPH scores were analyzed monthly. The section studied for the HCAPH scores was "Quietness" to see if the scores met the target goals for each month.

Results

During the project, 260 patients out of 430 patients were monitored through alarm and decibel counts for a two hour time period. Since the project finishes at the end of July, the data presented is incomplete. These results are missing the last few months of data collection. Figure 3 shows the noise levels in decibels (dβ) within the unit. It demonstrates a slight increase in the minimum, maximum, and mean from the pre-launch to the launch portions. Figure 4 and Figure 5 demonstrate the number of "true" and "false" alarms activated during pre-launch and launch portions of the project. There was a 16.8% decrease in false alarms from pre-launch to launch. Figure 6 and 7 show the eleven different alarms counted and the percent of which they occurred. No significant difference was noticed among the types of alarms. Some alarms increased slightly while others slightly decreased. Figure 8 shows the minimum, maximum, and average length of time alarms sounded within the unit. There was no significant difference noticed in the average length of time, but both the minimum and maximum lengths decreased. The minimum decreased 8.5% whereas the maximum decreased 29.9%. Figure 9 demonstrates the difference in the number of red, yellow, and bed alarms that signaled in the unit. No significant difference was noticed in the number of red alarms, even though yellow and bed alarms slightly decreased. Figure 10 and Table 1 show the HCAPHS for "Quietness" within the ICU along with the target score and yearly percentile. There was no significant difference though there was a slight change at the end of the project during the months from February 2014 to June 2014. Figure 11 shows the averages for the questions answered by nurses and patients from the Richard-Campbell Sleep Study Questionnaire. No significant difference was observed between nurses and patients, or between launch and pre-launch periods. The results do show that sleep in the ICU is neither perfect nor impossible. Most of the sleep scores range between the 30 and 40 percent which indicate a mediocre sleep. Through during the patients scored the noise levels during the launch stage an average of 12.3 where as during the pre-launch stage it was scored at a 31.4. This is 19.1 difference.

Conclusion

This project took on a very large task in evaluating eleven different alarms at one time. Quality of sleep and noise perception depend on multifaceted variables, especially for patients in the ICU. Some of these other variables that were not taken into consideration were medications, pain levels, and even the patient's hearing ability. Pain levels and some medications can disturb sleep and make the patient more intolerant to noise. Also with the population having an average age of 67 years old in the ICU at Muhlenberg, many of the patients were hard of hearing. This can either affect the results negatively or positively. Many of the patients may not notice some of the noises due to the hearing loss. On the other hand, nurses in return have to speak louder for the patient to understand them while patient teaching or implantation of nursing duties. In future research on sleep and alarm counts in ICU, studies should focus on a younger population and only a few alarms at a time to see if there is any change in data.

Before the implementation of the H.U.S.H project, several goals were designated to help better patient outcomes. These goals involved helping alleviate alarm fatigue with a decrease of at least 50% of controllable false alarms, safer decibel levels of 45 dβ during the day and 35 dβ at night, increase patient sleep quality, and improved HCAPHS. From the results, one can see that the false alarms were not reduced by 50% and decibels were decreased after the removal of the 90 decibel ventilator alarms, but after that decibel readings continued to stay around 50.3 decibels. The target score for HCAPH was not met at its 54.15 score and the ICU scored in the first percentile in quietness. These results from the H.U.S.H. project had demonstrated that noise is a huge issue in the hospitals, especially the ICUs. Not only does the noise levels not meet the EPA guideline for background noise levels, it can have implications for patients if they are unable to receive a goodnight's sleep when they are trying to recover from an injury or illness. The health of patients admitted to the hospital should be a priority of any health professional. The correction of high noise levels can possibly lead to better sleep at night. This trickle-down effect can lead to a shorter stay in hospitals, and eventually decreasing the hospital cost. Florence Nightingale once referred to noise as "that which damages the patient" (Mazer, 2012, p. 350). Future research should take a look to the past to improve the future of patient care.

References

Dennis, C. M., Lee, R., Knowles Woodard, E., Szalaj, J. J., & Walker, C. A. (2010, August). Benefits of Quiet Time for Neuro-Intensive Care Patients. American Association of NeuroScience Nurses, 42(4), 217-224.

Edwards, G. B., & Schuring, L. M. (1993). Pilot Study: Validating Staff Nurses' Observations of Sleep and Wake States Among Critically Ill Patients, Using Polysomnography. American Journal of Critical Care, 2(2), 125-131.

Kahn, D. M., Cook, T. E., Carlisle, C. C., Nelson, D. L., Kramer, N. R., & Millman, R. P. (1998, August). Identification and Modification of Environmental Noise in an ICU Setting . Clinical Investigations in Critical Care, 114(2), 535-540.

Mazer, S. E. (September/October 2012). Creating a Culture of Safely: Reducing hospital noise. Biomedical Instrumentation & Technology, 350-355.

Mazer, S. E. (March/April 2006). Increase Patient Safety by Creating a Quieter Hospital Environment. Biomedical Instrumentation & Technology, 145-146.

Olson, T. (2012). Delirium in the Intensive Care Unit Role of the Critical Care Nurse in Early Detection and Treatment. Canadian Association of Critical Care Nurses, 23(4), 32-36.

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Table 1

Target

YTD

YTD %ile

Quietness

54.15

34.3

1

Figure 11

Comments

Mentor: Denise Davis-Maludy

Department(s)

Research Scholars, Research Scholars - Posters

Document Type

Poster

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