Running head: MONITOR ALARM FATIGUE
Monitor Alarm Fatigue: Proposal of an Informatics Solution
Mary E. Hefferan
Ferris State University
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MONITOR ALARM FATIGUE
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Alarm Fatigue
Inherent in providing effective patient care as a nursing professional, are numerous
demands, tasks, and responsibilities designed to uphold patient safety and deliver quality care.
In addition, many nursing environments entertain cacophony of various alarms, alerts, and rings.
Each monitored bed can produce up to 700 physiologic alarms per day (Cvach, Biggs, Rothwell,
& Charles-Hudson, 2013). Although these alarms are designed to alert nurses to potentially
dangerous changes in patient vital signs, up to 80-99% of alarms are not clinically significant and
require no intervention (American Association of Critical Care Nurses [AACN], 2013). When
inundated with alarms, nurses can become desensitized to them, leading to a dangerous
phenomenon called alarm fatigue.
Alarm fatigue, a result of being exposed to too many alarms, causes a disruption of
workflow and creates distractions, increasing the likelihood of error (Cvach, 2012). As patient
assignments become busier and more complex, performance and responsiveness to alarms
decrease as well. During 2005 and 2008, the Food and Drug Administration (FDA) reported 566
patient deaths associated with monitor alarms and 98 alarm related events were recorded from
2009 to 2012 in the Joint Commission’s (JC) Sentinel Event database (Cvach, 2012; Stokowski,
2014). Desensitization to alarms also leads to unsafe workarounds such as disabling or pausing
of alarms, posing a serious risk to patient safety (Grahm & Cvach, 2010).
Recognizing the risk alarm fatigue has towards patient safety, the JC has introduced a
new national patient safety goal tasking hospitals to improve alarm safety and implement
specific policies regarding alarm system management (JC, 2013). The JC states that improper
alarm system management is a multifaceted problem caused by alarms that are difficult to detect,
excessive and unnecessary alarming, and overly sensitive parameters. To reach this goal, the JC
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emphasizes standardizing alarm management while customizing solutions to meet specific needs
of each area of practice (JC, 2013). The Emergency Care Research Institute (ECRI) has also
consistently ranked alarm hazards near the top of their “Top Ten Health Technology Hazards”
each year and stress the need for improvement (Keller, 2012). Alarm systems need to be both
highly sensitive and specific so an actionable patient event is never missed (Stokowski, 2014).
In this paper, an evidence based hardware and software solution will be described as well as a
description of human-computer interaction (HCI) considerations. Measures of success will also
be defined and the leadership skills necessary to implement this solution will be outlined.
Evidence Based Solution
Safely managing a demanding patient assignment requires the support and assistance
from innovative health care technology. Alarms from patient monitors, IV pumps, or ventilators
are designed to assist nurses by alerting them to a change in a patient’s condition or a failure
reading. However, in order to prevent alarm fatigue, alarms need to be designed to be accurate
so only clinically significant alarms sound and promptly reach the nurse responsible for the
patient. Efficiency of alarm systems can be improved through integrating mobile technology that
augments nurse call system and improving the sensitivity and specificity can be achieved
through software that improves the intelligence of alarm systems.
The use of mobile technology has the ability to improve overall efficiency and accuracy
of clinicians by allowing access to important patient data throughout the hospital (Krauskopf &
Farrell, 2011). Alarm systems that send alerts directly to nurses’ mobile phones reduce nurses’
alarm response times and eliminate unnecessary overhead paging or patient call alarms
(McGonigle & Mastrian, 2015; Vocera, 2014). Guarascio (2011) found that after mobile
technology was introduced to assist in alerting nurses to patient status changes, response time
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was significantly decreased and 62% of calls were responded to in less than one minute. After
mobile alert systems were introduced in a 1,061 bed facility, nurse response times were reduced
from 9.5 minutes to an average of 39 seconds (Turisco & Rhoads, 2008).
Also important in improving alarm safety and reducing alarm fatigue, is to incorporate
alarm response protocols. A clear process for identifying who is responsible for responding to
alarms is crucial to ensuring alarm systems are safely managed (Phillips & Barnsteiner, 2005).
Mobile technology can assist in achieving this goal as well. Nurse call systems that incorporate
mobile technology can expedite care by helping identify the appropriate nurse to alert and where
they are located within the hospital (Meyers, 2011). If these alerts are refused or not
acknowledged by a busy nurse, responsibility escalates to the next appropriate person. Turisco
and Rhoads (2008) found that mobile alert systems closed the communication loop “100 percent
of the time, compared with the previous 35 percent rate” (p. 6) with a pager only system.
Additionally, if phones are imbedded with infrared or radio-frequency technology that
communicates with “an installed locator detector” (Meyers, 2011, p. 22), staff can be identified
by job description and alerts can be cancelled as the appropriate staff enters the patient’s room.
Furthermore, increasing alarm sensitivity and specificity by assuring only clinically
significant events are activating alarm systems will reduce false alarms that promote alarm
fatigue. Improving monitor alarm software through use of simple reactive intelligent agent (IA)
technology can achieve this (Blum, Kruger, Sanders, Gutierrez, & Rosenburg, 2009). Blum and
colleagues (2009) noted an 88% improvement of the specificity of mean arterial blood pressure
alarms after IA was introduced on a 14 bed intensive care unit. Also, alarm algorithms that
incorporate delays eliminating alarms for very brief, self-corrected changes, or identify periods
where patients are coughing or moving, can reduce unnecessary alarming. Gorges, Markewitz,
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and Westenskow (2009) found after incorporating a 6 second alarm delay for pulse oximeters,
alarms rates were reduced by 50%. If able to incorporate circumstantial data (coughing,
suctioning, moving), false alarms could be further reduced by up to 77%.
Human Computer Interaction
When proposing an informatics solution, careful consideration must be paid to the HCI to
ensure the solution will enhance the current nursing workflow and match the needs of the end
users (McGonigle & Mastrian, 2015). Users of the new technology should be involved early to
provide input and evaluation should follow implementation. To begin, a cognitive task analysis
would help identify how well the technology could be incorporated into current workflow and
how responsibilities are distributed between user and technology. McGonigle and Mastrian
(2015) describe a cognitive task analysis begins with gathering data regarding a specific task by
interviewing those involved. Interviews of experts who perform the task will elicit information
regarding thought processes and decision making behind alarm management (Hysong et al.,
2010).
To ensure the HCI is effective and discourages workarounds, McGonigle and Mastrian
(2015) also emphasize implementation should allow for adaptation and refinement as problems
are identified. Involving end users in a formal usability test that studies “actual users using the
interface” (McGonigle & Mastrian, 2015, p. 210) provides insight regarding potential problems
with implementation and allows for strategic management of these issues. Also, the usability of
mobile technology for alarm notification should be carefully studied to ensure it is efficient and
easily incorporated into nursing workflow (Yen & Bakken, 2011). For example, if phones or
mobile devices lose signal frequently or fail to consistently receive alerts, errors can occur, users
will become frustrated, and cost of implementation could increase.
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Finding Success
Evaluation of an informatics solution is important in all stages of implementation and
measures of success can be identified through various evaluative methods (McGonigle &
Mastrian, 2015). In addition to a formal usability test described previously, success can be
evaluated through field studies that trial the new process in its intended setting. Field studies
should test efficiency and accuracy of mobile alert system and upgraded monitor software by
collecting quantitative and qualitative data. Success through quantitative data would show a
reduction in both alarm retrieval time and amount of false alarms. Qualitative data should focus
on end-user satisfaction questionnaires that evaluate ease of use, integration into workflow, and
value towards practice. Groups of experts could be gathered where open discussion is facilitated
regarding the new process and its impact.
Finding success following implementation with these measures does not imply
completion. McGonigle and Mastrian (2015) highlight the importance of identifying why a
solution was successful or unsuccessful in order to continue to improve the HCI. Findings
should continue to be evaluated to identify where further refinements could be made and
processes improved. This important “maintenance phase” ensures end users are supported and
provides the opportunity for addressing potential changes to the process. The iterative nature of
this method will ensure advancements towards safer patient care are made and informatics
solutions are optimized to meet end-user needs.
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Leadership Skills
Leaders in nursing informatics must embody key leadership skills that assist
implementation of informatics solutions. These skills will guide successful implementation and
connect end-user needs with the project’s goals. The American Nurses Association ([ANA],
2008) Scope and Standards of Nursing Informatics identifies specific measures to fulfill the
standard of leadership. The informatics nurse (IN) should exhibit the ability to work within and
support a team environment and utilize their specialized knowledge to educate and mentor
others. Establishing a clear vision and goals is important for the IN leader to implement a
proposed solution as outlined in this paper (ANA, 2008). This will help aid direction of the
project and “enhance the effectiveness of the interdisciplinary team” (ANA, 2008, p. 90). Also,
during the transitional period following implementation, the IN leader should demonstrate
flexibility and identify mistakes as expected and areas for learning. These leadership qualities
should inspire loyalty of others and promote end-user adoption.
Conclusion
Alarm fatigue occurs when excessive alarming in a clinical environment leads to
desensitization and disruption in workflow. This poses a serious risk to patient safety and has
led to patient death and sentinel events recorded by the JC. The use of mobile technology aimed
at reducing alarm response time and advanced monitor technology to increase the sensitivity and
specificity of alarms could be implemented in an effort to reduce alarm fatigue. Measures of
success should include evaluation of qualitative and quantitative data that show improvement in
retrieval time, a reduction of false alarms, and end user satisfaction. Evaluation should continue
through a maintenance phase to maintain support for end-users and further refine the solution. In
order to assist successful implementation, the IN leader should exhibit leadership qualities
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outlined by the ANA (2008) that promote teamwork, establish a clear vision and goals, exhibit
flexibility, and inspire loyalty.
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