Measuring and Influencing Noise on an Intensive Care Unit Using a Visual Warning System

Monday, 9 November 2015

Marie-Louise Luiking, RGN, MA
Intensive Care Unit, Sint Antonius Ziekenhuis, Nieuwegein, Amersfoort, Netherlands

Introduction/ aim: The experience of background noise can hamper the recovery of a patient. It can cause sleep deprivation, agitation and delirium. (Darbyshire  & Young 2013, Bartick et al 2010) For this reason the World Health Organisation advises to keep the mean noise level below 35 to 40 decibel. The noise level in a hospital setting is generally high and on an intensive care unit it is generally very high . On an intensive care unit, an unavoidable part of the noise is generated by the equipment, but a substantial part of the noise is produced by the people present (staff, patients and visitors). How much noise is produced by the people present depends on the their awareness  that they generate unnecessary noise and their willingness to change their noise generating behaviour. In this study the noise reduction was researched that could be reached when the persons present in the room were notified of the (too high) sound level. Additionally it was investigated what the nurses considered unnecessary noise.

Method: In a prospective study, the sound levels were measured for 3 weeks in a 4 person intensive care room of a class 3 intensive care. Subsequently a visual noise warning system was fixed to the wall on a highly visible place. Thereafter the sound levels were again measured for 4 weeks. The sound level measurements were done using a BG-5 class 2 sound level meter, which recorded the sound level every minute. This meter was fixed to the roof in the middle of the room. The visual noise warning system looked like a traffic light and displayed an amber light at 45 to 55 dB and a red light above 55 dB.

The perception of the nurses of unnecessary noise factors was investigated using the Topf’s Disturbance of Hospital noise scale. (Topf, 2000) It exists of a list of 29 items each describing a particular sound. The respondent has to indicate using a 5 point Likert scale to what degree a particular sound disturbed him or her during work. The questionnaire was translated to Dutch.

Results: The mean sound level before the introduction of the traffic light was 54.6 dB, after the introduction it was reduced to 53.9 dB (ttest, p <0.001). The Topf’s Disturbance of Hospital noise scale had an internal consistency (Cronbach’s alpha) of  0.883. All 120 intensive care nurses were approached to complete the questionnaire, 83% of the questionnaires were returned. The 4 most disturbing noises beside alarm signals were all noises which are dependent upon the behaviour of the persons present: loud conversations in the corridors at night, mobile phone usage, conversations among nurses in the rooms and slamming of doors. The 5 least disturbing noises were all noises which are not dependent upon the behaviour of persons present: traffic noise, flushing of toilets, washing of hands, sounds created by cutlery or serving trays, airconditioning or heating.

Conclusion: In this study, the influence of a visual noise warning system was limited. Noise which was generated unnecessarily disturbed the nurses most. Therefore a visual noise warning system seems to contribute to noise reduction but additional interventions are necessary to effectuate a change in behaviour towards noise. The nurses are well aware of which behaviours need to change.