Patient Safety Tip of the Week

October 17, 2017    Progress on Alarm Management



Among our numerous columns on alarm fatigue and alarm management issues, two columns were aimed at helping hospitals meet Joint Commission’s national patient safety goal on alarm safety (see our Patient Safety Tips of the Week July 2, 2013 “Issues in Alarm Management” and August 16, 2016 “How Is Your Alarm Management Initiative Going?”). Hopefully, all of you have your alarm management programs up and running and reducing unnecessary alarms without increasing adverse patient events.


So how are other hospitals doing? The whole Spring 2017 issue of Biomedical Instrumentation & Technology was dedicated to articles on clinical alarm management (Biomedical Instrumentation & Technology 2017).


One of the articles described one hospital’s program to reduce nonactionable alarms in a medical intensive care and stepdown unit at Yale New Haven Hospital (De Vaux 2017). De Vaux and colleagues used data collected by observational methods to identify PVCs as the most frequent cause of nonactionable alarms contributing to alarm fatigue. The alarm management team implemented changes to the default settings for PVC alarms to "off". The number of audible alarms after the intervention decreased from 210 to 48, a 77% reduction in audible alarms. Moreover, there was a decrease in nonactionable alarms to six from the original 122 in the pre-intervention period. The group also found that the percentage of customized alarms increased during the study period. All this occurred with no adverse patient events related to the changes reported in the event reporting system or by clinical staff during the post-intervention observational period.


We are also happy to see that their team decided to default the parameter for continuous QTc monitoring to "on" to allow for early identification of QTc prolongation and the associated risk of the life-threatening arrhythmia torsade de pointes, in keeping with the spirit of our October 10, 2017 Patient Safety Tip of the Week “More on Torsade de Pointes”.


Next, a paper by Pelter and colleagues (Pelter 2017) discussed steps UCSF took to address alarm management. Their clinical alarm management (CALM) committee selected the patient safety manager, a masters-prepared nurse responsible for patient safety for all three campuses, to link together this diverse committee, which included clinical leaders, administrative leaders, and clinical staff. These included representatives from nursing, medicine, clinical engineering, biomedical engineering, information technology, risk management, respiratory therapy, and materials management.


Next an alarm inventory was conducted, with individual committee members scoring each piece of equipment on: potential for harm, clinical oversight required, current clinical oversight, use frequency per patient during hospitalization, and urgency. The scores were summed for each piece of equipment or device to produce an overall risk assessment score which was used by the consensus committee to prioritize alarms. The inventory also included assessment of alarm default settings and levels of alarm alerts.


Settings for arrhythmia and SpO2 alarms were changed in the adult intensive care units. Also, based upon literature review, they also standardized electrode management and took steps to ensure provision of fresh electrodes on all their units. Facility-wide education included examples of how alarm fatigue led to adverse patient events. The CALM Committee was established as the centralized governing and oversight committee for ensuring alarm safety. The Pelter article does not provide details on the outcomes but we previously discussed the UCSF experience (Drew 2014) in our August 16, 2016 Patient Safety Tip of the Week “How Is Your Alarm Management Initiative Going?”.


Several papers discussed the role of middleware in alarm management. One (Jaques 2017) addresses the questions you must ask (and answer!) in developing middleware as part of your alarm management system. This includes questions like:


The type of device selected to receive messages from the middleware is important since it impacts what type of data can be sent (eg. text only? waveforms? etc.). It also impacts how receipt of messages may be acknowledged and escalated. The article nicely addresses each of the questions above and even provides some real-life scenarios to demonstrate issues.


Zaleski and Venella (Zaleski 2017) looked at the role of middleware in monitoring of patients receiving opioids. They especially focused on smart alarms and noted several techniques and strategies that work to reduce false, or nonactionable, alarm signals, including:


They note that multiparameter physiologic monitors are critical components for continuous patient monitoring and data capture. Capnography and continuous pulse oximetry monitoring provide a sensitive and early indicator of OIRD (opioid-induced respiratory distress) as long as the appropriate clinical indications are detected and the associated smart alarm signals communicated to clinical staff. Capnography, which measures respiratory rate and exhaled end-tidal carbon dioxide and inhaled carbon dioxide, produces a waveform together with the instantaneous values of end-tidal carbon dioxide and trends in respiratory rate that are key indicators as to whether a patient is in respiratory failure or is trending towards respiratory failure,


Middleware retrieves episodic data from medical devices, translates it to a standard format, combines it with data from the patient health record and then uses methods for disseminating and distributing the data and the smart alarm signals to those who need to know in a timely fashion (eg. to dashboards or mobile devices). It is important, however, to ensure your system updates who the responsible parties are and how they receive the information. For example, in our February 9, 2016 Patient Safety Tip of the Week “It was just a matter of time…” we described a case where a critical alarm alert was sent to a party who was no longer responsible for the patient rather than to the responsible party, leading to a delay in response.


Zaleski and Venella emphasize the importance of teamwork and involving all stakeholders in design and management of the alarm system and really emphasize the value of clinical workflow in such systems.


Connie Clements Dills (Dills 2017) addressed managing mechanical ventilator alarms with middleware. Her Hospital for Special Care (HSC) in New Britain, CT, manages approximately 100 mechanically ventilated patients each day. They identified middleware as the best route in addressing the challenge of managing alarms from so many ventilators and other monitoring devices. The middleware works as an electronic monitoring system, which interfaces with medical devices and continuously collects data and monitors for breaches in set alarm parameter settings. It then alerts caregivers to potential life-threatening conditions. Middleware allows for customization of alarms and then sends notifications to a secondary device (e.g., a pager, smartphone, laptop, desktop computer, and/or electronic message board). Dills feels that middleware's most invaluable contribution to clinical care is the ability to distinguish between actionable and nonactionable alarm conditions.


Their alarm inventory found that HIP (high inspiratory pressure) alarms accounted for nearly one-third of all alarms and their second most frequently occurring alarm was  HRR (high respiratory rate). Combined, these two alarms accounted for more than 50% of all ventilator alarms. Most of these alarms were nonactionable and precipitated by patient actions such as coughing, swallowing, attempting to speak, or repositioning. By using middleware, they filtered out those alarm conditions as a level one priority. But their interdisciplinary team identified other alarm conditions as critical to patient safety: patient disconnect, low exhaled minute volume (Low Ve), low inspiratory pressure (LIP), and no data. Respiratory therapists can also set "smart alarms" through the middleware to alert them to alarm conditions for patients whose clinical condition warrants a heightened level of concern.


They saw an immediate 80% reduction in the number of nonactionable ventilator alarms following implementation of the middleware. When an actionable alarm occurs, the respiratory therapist is notified via pager with a message indicating the patient's name, the room number, and the alarm condition and urgency. A secondary page alerts coworkers if the primary caregiver's response is delayed. They are now also in the process of monitoring response times.


Other articles in this dedicated supplement discuss AAMI’s work on addressing alarm standards (Moyer 2017), classification of alarms (Edworthy 2017), lessons on alarm management from other “process” industries (eg. chemicals, oil refining, oil and gas production, pulp and paper, pharmaceuticals, food and beverage, non-nuclear power generation) (Forrest 2017), and a good round table discussion about issues in alarm management. There is also a very thoughtful article on the difference between “monitoring” and “surveillance” (Giuliano 2017) which emphasizes the cognitive processes used by nurses, early warning systems, and rapid response team systems. Another article (Peters 2017) discusses use of the “influencer” model to promote change. There’s even a clever analogy comparing alarm management to a football game (Vanella 2017).


This whole supplement of Biomedical Instrumentation & Technology is well worth your reading. You’ll find many of the article contain valuable information that will help you with your alarm management system.


Prior Patient Safety Tips of the Week pertaining to alarm-related issues:








Biomedical Instrumentation & Technology. Horizons Spring 2017 supplement. Clinical Alarms: Managing the Overload.



De Vaux L, Cooper D, Knudson K, et al. Reduction of Nonactionable Alarms in Medical Intensive Care. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 58-61



Pelter MM, Stotts J, Spolini K, et al. Developing a Clinical Alarms Management Committee at an Academic Medical Center. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 21-29



Drew BJ, Harris P, Zègre-Hemsey JK, et al. Insights into the Problem of Alarm Fatigue with Physiologic Monitor Devices: A Comprehensive Observational Study of Consecutive Intensive Care Unit Patients. PLOS One 2014; Published: October 22, 2014



Jacques S.  Factors that Affect Design of Secondary Alarm Notification Systems. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 16-20



Zaleski J, Venella J. Using Middleware to Manage Smart Alarms for Patients Receiving Opioids. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 44-49



Dills CC. Managing Mechanical Ventilator Alarms with Middleware. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 62-65



Moyer J. AAMI Tackles Alarm Management Standards. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 7



Edworthy JR, Schlesinger JJ, McNeer RR, et al. Classifying Alarms: Seeking Durability, Credibility, Consistency, and Simplicity. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 50-57



Forrest S, Sands N. Alarm Management Lessons from the Process Industries. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 30-33



Giuliano KK. Improving Patient Safety through the Use of Nursing Surveillance. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 34-43



Peters K, Shields S. Using the Influencer Model to Improve Alarm Management Practices. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 66-70



Venella J. Drawing Up a New Game Plan to Reduce Alarm Fatigue. Biomedical Instrumentation & Technology: Clinical Alarms: Managing the Overload 2017; 51(s2): 71-72










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