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Correlations between monitor alarm workload and overall workload in Swedish emergency departments: a prospective multicenter cross-sectional study

This prospective multicenter study found a significant positive correlation between perceived alarm and overall workload in Swedish emergency departments, identifying that the proportion of ambulance arrivals and the frequency of technical alarms independently contribute to increased alarm workload beyond general staffing demands.

Original authors: Sebastian Johansson, Erika Johannesson, Daniel Wilhelms, Jens Wretborn

Published 2026-06-24

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Sebastian Johansson, Erika Johannesson, Daniel Wilhelms, Jens Wretborn

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine an Emergency Department (ED) as a high-speed, chaotic control room. The staff are like air traffic controllers, but instead of planes, they are managing patients. To keep everyone safe, they rely on a fleet of "digital watchdogs"—the heart rate monitors and vital sign machines attached to patients. These machines are designed to bark (or beep) whenever a patient's condition changes or if the machine itself has a glitch.

This study, conducted in three Swedish hospitals, asked a simple question: Does the noise from these watchdogs make the controllers feel more overwhelmed, or is the overwhelm just because there are too many planes to manage?

Here is the breakdown of what the researchers found, using simple analogies:

The Main Discovery: The "Double Whammy"

The researchers found a strong link between how busy the staff felt overall and how much they felt bothered by the beeping machines.

The Analogy: Think of the overall workload as a heavy backpack. The alarm workload is a second, smaller backpack. The study found that when the first backpack gets heavy, the second one usually feels heavier too. They move together.
The Result: There is a clear correlation (0.53) between general stress and alarm stress. When the ER is packed and the staff are running around, the beeping machines feel more annoying and burdensome.

The Surprising Twist: It's Not Just About "Busy"

Usually, you'd assume that if you have more patients, or sicker patients, the machines would beep more, and the staff would feel more stressed. However, the study found that two specific things made the alarm burden feel worse, even if the general busyness of the room stayed the same.

1. The "Ambulance Express" Factor

The Finding: The percentage of patients arriving by ambulance was a major driver of alarm stress.
The Analogy: Imagine your kitchen. If you are cooking dinner for your family (regular patients), it's busy but manageable. But if a delivery truck pulls up every 5 minutes dropping off huge, heavy crates (ambulance patients), the kitchen suddenly feels like a loading dock. Even if you aren't cooking more meals, the sheer volume of incoming "heavy" items makes the whole operation feel chaotic and increases the pressure on the alarms.
The Paper's Claim: More ambulance arrivals = higher perceived alarm workload, independent of how many total patients are there.

2. The "False Alarm" Noise (Technical Alarms)

The Finding: The study found that "technical alarms" (beeps caused by the machine malfunctioning, wires getting loose, or sensors slipping) were nine times more common than actual medical alarms (beeps caused by a patient's heart rate changing).
The Analogy: Imagine trying to listen to a radio station, but 9 out of every 10 beeps are just static or a broken speaker, and only 1 beep is actually a song. Eventually, you stop listening to the radio entirely because the noise is so annoying. The study found that this "static" (technical errors) was a huge, independent factor making staff feel overwhelmed.
The Paper's Claim: Reducing these technical glitches is a key way to lower stress, separate from just hiring more staff or slowing down patient flow.

What Didn't Matter (Surprisingly)

The researchers tested several other ideas that people often assume cause stress, but the data said otherwise:

Total Number of Patients: Having more people in the room didn't automatically mean more alarm stress.
Sick Patients: Even though sicker patients (Level 1 or 2) are supposed to be monitored more closely, their presence didn't statistically increase the perceived alarm burden in this specific study.
Older Patients: The age of the patients (over 65) didn't change how annoying the alarms felt.
Chest Pain Patients: Even though these patients were expected to trigger many alarms, they didn't correlate with higher stress levels in the data.

The Bottom Line

The study concludes that while the machines are helpful tools (68% of staff said they were helpful), they can become a source of noise pollution.

The authors suggest that if hospitals want to make the staff's life easier, they shouldn't just try to "slow down" the whole hospital. Instead, they should focus on two specific levers:

Fix the machines: Drastically reduce the "technical alarms" (the broken speakers/static).
Manage the flow: Be aware that a sudden influx of ambulance patients creates a unique type of pressure that needs specific attention.

In short: The staff are stressed by the noise, but the noise isn't just caused by the patients; it's caused by the machines breaking and the specific type of patients arriving by ambulance. Fixing those two things could quiet the room, even if the hospital remains busy.

Technical Summary: Correlations between Monitor Alarm Workload and Overall Workload in Swedish Emergency Departments

Problem Statement
Emergency departments (EDs) operate under high clinical demands characterized by time-critical decisions and substantial staff workload, which increases the risk of diagnostic errors, procedural delays, and staff burnout. While continuous physiological monitoring is integral to ED care, the resulting alarms—categorized as clinical (indicating vital sign deviations) or technical (indicating equipment malfunction)—often contribute to "alarm fatigue." Alarm fatigue is defined as the desensitization and delayed response to alarms by healthcare workers, recognized as a patient safety hazard. While existing evidence from intensive care units (ICUs) and inpatient wards suggests that customizing alarm thresholds and reducing nuisance alarms can improve outcomes, the ED environment differs fundamentally due to unselected patient populations, rapid turnover, and open workspaces. It remains unclear whether alarm workload in the ED is merely a reflection of general clinical workload or if specific ED operational variables contribute independently to the perceived burden.

Methodology
This study employed a prospective, multicenter, cross-sectional design conducted across three EDs in southeastern Sweden (one rural, one urban community, and one academic hospital) serving a combined population of approximately 470,000.

Data Collection: The researchers utilized a multi-source data approach:
1. Staff Surveys: An online survey (Webropol) was administered to physicians, nurses, and nurse assistants during clinical shifts. Participants rated their "overall workload" and "alarm-specific workload" from monitoring equipment over the preceding hour using a Likert scale (0–6).
2. Monitor Data: Alarm data (type, level, timestamp, confirmation time) were extracted from a central server for Philips monitoring systems (X3, MX450, MX550 models) used at all sites. Alarms were categorized as clinical (Level 1 and 2) or technical (Level 3).
3. Electronic Health Records (EHR): Patient data were matched to survey intervals, including triage acuity (RETTS levels 1–5), mode of arrival, age, chief complaint, and team assignment.
Statistical Analysis: Data were stratified by ED team and hour. A Pearson correlation test determined the relationship between overall and alarm-specific workload. Multivariate linear regression analysis was used to identify associations between alarm workload and ED-specific covariates (patient volume, ambulance arrivals, acuity, age, chest pain, and alarm frequencies), treating variables as continuous where appropriate.

Key Contributions

Quantitative Correlation in ED: This is the first study to quantitatively examine the correlation between perceived alarm workload and overall workload specifically within the ED setting, distinguishing it from ICU-focused literature.
Identification of Independent Modifiable Factors: The study moves beyond the general assumption that alarm burden is solely a function of patient volume. It isolates specific operational variables that independently influence alarm workload perception.
Differentiation of Alarm Types: The research explicitly separates the impact of clinical alarms (physiological deviations) from technical alarms (equipment malfunctions), highlighting the disproportionate frequency and impact of the latter.

Results

Correlation: A moderate positive correlation was found between overall workload and alarm-specific workload ( $r = 0.53$ , $p < 0.001$ ).
Survey Demographics: Of 184 surveys collected, 68 hours of data (where patients were present) were included in the final analysis. The mean overall workload was 2.0, and mean alarm workload was 1.4.
Alarm Frequency: Technical alarms were significantly more frequent than clinical alarms (median 18.0 vs. 2.0 per hour). Approximately 18% of respondents reported being disturbed by monitoring equipment, while 68% found it helpful.
Regression Analysis:
- Overall Workload: Remained a significant predictor of alarm workload ( $\beta = 0.5$ , $p < 0.001$ ).
- Ambulance Arrivals: The percentage of patients arriving by ambulance assigned to a team was positively associated with alarm workload ( $\beta = 1.6$ , $p = 0.01$ ).
- Technical Alarms: The frequency of technical alarms was independently associated with increased alarm workload ( $\beta = 0.4$ , $p = 0.03$ ).
- Non-Significant Factors: The total number of patients per team, the proportion of high-acuity patients (RETTS 1–2), geriatric patients (>65 years), and patients with chest pain did not show a statistically significant association with alarm workload in the multivariate model.

Significance and Claims
The authors claim that their findings confirm a close connection between general workload and alarm workload but, crucially, identify that alarm burden is not solely a reflection of patient volume or acuity. The study asserts that two specific, modifiable ED factors—the volume of patients arriving by ambulance and the frequency of technical alarms—independently contribute to the staff's experienced alarm workload.

The paper concludes that while monitoring equipment is generally helpful, the high frequency of technical alarms (nearly nine times that of clinical alarms) represents a distinct, actionable target for intervention. The authors suggest that future alarm management strategies in the ED should focus specifically on reducing technical alarms and managing the flow of ambulance arrivals, rather than solely targeting clinical alarm thresholds or general staffing levels. This approach could reduce the overall burden on staff and mitigate alarm fatigue without requiring fundamental changes to patient flow or staffing ratios.

The Main Discovery: The "Double Whammy"

The Surprising Twist: It's Not Just About "Busy"

What Didn't Matter (Surprisingly)

The Bottom Line

Technical Summary: Correlations between Monitor Alarm Workload and Overall Workload in Swedish Emergency Departments

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