By Eric Andrew Kristof, RN, CAHIMS | Healthcare IT Professional | HIMSS Arkansas Chapter Member
About This Series: The HIMSS Word of the Day is a running blog series drawing from the HIMSS Dictionary of Health Information and Technology Terms, Acronyms, and Organizations, 6th Edition (2025) — the authoritative reference for healthcare IT professionals and the primary study resource for CAHIMS and CPHIMS certification. Each post paraphrases the term in plain language, grounds it in real-world healthcare IT context, and adds a bedside nursing perspective you won’t find in a textbook.
📖 The Term: Alert
Source: HIMSS Dictionary of Health Information and Technology Terms, Acronyms, and Organizations, 6th Edition (2025)
🔍 Plain-Language Definition
The HIMSS Dictionary defines an alert as a written or acoustic signal that announces the arrival of messages and results, and that helps avoid undesirable situations such as contradictions, conflicts, erroneous entries, tasks not done on time, or an exceptional result. The Dictionary distinguishes two types. A passive alert simply displays on the screen as a message. An active alert demands prompt notice, and the responsible person is contacted right away, such as by pager. The Dictionary links the term to decision support systems.
The distinction helps explain much of what goes right and wrong with alerts. A passive alert is easy to ignore, which makes it appropriate for information that is useful but not urgent. An active alert interrupts, which makes it appropriate for information that cannot wait. Using an active alert for something that could be passive wastes attention; using a passive alert for something urgent risks a missed action. Most real systems blend styles, using banners, pop-ups that require a response, messages sent to a mobile device, and sounds from monitors and pumps.
Alert design involves several questions. What triggers it? Who receives it? How is it displayed? What response is expected? What happens if nobody responds? A well-designed alert answers all of these, and a poorly designed one only says that something might be wrong.
| Feature | Passive Alert | Active Alert |
|---|---|---|
| Delivery | Message on screen | Immediate notification to a person |
| Interruption | Low | High |
| Best for | Helpful, non-urgent information | Time-critical risk |
| Risk if misused | Missed action | Overload and fatigue |
| Example | Reminder banner about a due screening | Page for a critical lab result |
⚠️ Exam Alert: A passive alert appears on the screen as a message. An active alert needs immediate attention and notifies the right person right away. Alerts are a form of clinical decision support. Do not confuse an alert with an alarm from a bedside monitor, and do not confuse alert with alert fatigue, which is the desensitization that results from too many alerts.
🌐 Why It Matters: Real-World Healthcare IT Context
Alerts are one of the most visible parts of clinical decision support, and one of the most debated. The evidence shows both their value and the ways they can fail.
A 2020 systematic review in JMIR Medical Informatics looked at overridden alerts in computerized provider order entry. The four authors searched literature from 2000 through March 2019 and included 23 articles. The range of average override rates was 46.2 percent to 96.2 percent. The share of overrides judged appropriate ranged from 29.4 percent to 100 percent, and it varied by alert type: drug-allergy alerts from 63.4 to 100 percent, drug-drug interaction alerts from 0 to 95 percent, dose alerts from 43.9 to 88.8 percent, geriatric alerts from 14.3 to 57 percent, and renal alerts from 27 to 87.5 percent. The most common reasons given for overriding were “will monitor” and “patients have tolerated before.” The authors concluded that override rates are high, that some categories of overrides (drug-drug interaction, renal, and geriatric) were more often inappropriate, and that other categories such as duplication, allergy, and formulary alerts were often appropriately overridden, making them logical targets for revision. The wide ranges across studies mean that no single override rate describes every setting.
How an alert is delivered matters as much as what it says. A 2019 systematic review in the Journal of the American Medical Informatics Association by three authors included 39 articles on medication safety alerts and compared conventional interruptive pop-ups with alternative designs. They found that the most common type of decision support, in which a pop-up interrupts the prescriber, was accepted the least often. Alternatives included tiering alerts by risk, offering shortcuts for common corrections, requiring a reason to override, and tailoring alerts to the roles of pharmacists and prescribers. Only one alternative appeared to increase prescriber acceptance: role tailoring. The authors also noted that the studies measured acceptance in different ways, which made results incomparable. The message for health systems is that sending the right alert to the right person is often more effective than adding another pop-up for the same person.
Alerts can also be tied to patient outcomes, though results vary. A 2026 multi-methods study in Health and Social Care Delivery Research, with 14 authors, examined digital sepsis alerts in four National Health Service acute trusts in the United Kingdom. All four trusts experienced reduced mortality among patients with serious infections after introducing digital sepsis screening tools. After adjustment for case mix, admission patterns, and pre-existing trends, one trust showed a statistically significant decrease in mortality linked to alert implementation. Qualitative findings pointed to factors that supported effective use: deployment on general wards rather than in intensive care units, use by clinicians familiar with similar technology, availability of 24-hour emergency outreach teams, strong technological infrastructure, and alerts that were user-friendly, non-intrusive, and not one of many competing alert systems. The authors noted that effectiveness varies. Because the study used routine data without randomization, it cannot prove that alerts alone caused the change.
Together, these studies suggest that an alert is only one link in a chain. The signal must be accurate, reach the right person, fit the workflow, and lead to an action that the organization is ready to support. If any link is missing, the alert can become noise.
Common alert-related problems:
- Interruptive alerts for low-value information
- Alerts sent to a person who cannot act on them
- High override rates that nobody reviews
- Multiple alert systems that compete for attention
- No clear escalation if an alert is not acknowledged
- Alert rules built once and never revisited
What supports effective alerts:
- Tiering by risk, with interruption reserved for urgent items
- Role tailoring so the right person receives the alert
- Review of override reasons and rates by clinical governance
- Clear action steps and a defined response expectation
- Support staff such as outreach teams for time-critical alerts
- Regular tuning based on clinician feedback and outcome data
🏥 The Nurse’s Perspective: Clinical, Bedside, & Workflow
Nurses receive many kinds of alerts every shift, from medication warnings to early warning scores to device notifications, and they are often the ones who must act on them.
At the Bedside
A nurse who gets an alert weighs it against what is visible at the bedside. A sepsis score may prompt a reassessment, a fall risk flag may trigger precautions, and a drug interaction warning may lead to a call to the pharmacist. Nurses report alerts that seem wrong, repetitive, or poorly timed, because that feedback is how systems improve.
In Clinical Workflow
Nurse managers and informaticists review which alerts reach nurses and whether those alerts require nursing action. The role-tailoring finding supports routing alerts to the role that can act, such as a pharmacist or rapid response nurse, instead of sending everything to the bedside nurse. Escalation steps, such as who is called when an alert is not acknowledged, are written down and practiced.
In EHR Implementation (Go-Live Perspective)
An Epic Go-Live brings many default alerts that may not fit local practice. At-the-elbow support analysts hear which alerts nurses find useful and which they dismiss, and they pass this to the clinical decision support team so alerts can be tuned after go-live. Early feedback helps prevent a pattern of automatic dismissal from becoming habit.
🎓 CAHIMS / CPHIMS & HIMSS Perspective
CAHIMS Exam Domain Mapping
Alerts appear in decision support, safety, and governance questions:
| CAHIMS Domain | How Alerts Appear |
|---|---|
| Healthcare & Technology Environments | Clinical decision support concepts, notification technology |
| Clinical Informatics | Alert design, workflow, medication safety |
| Healthcare Information & Systems Management | Rule maintenance, interfaces, monitoring of alert performance |
| Management & Leadership | Governance, safety culture, change management |
Key Terms to Know Alongside Alert
- Passive Alert — message displayed on screen without immediate notification
- Active Alert — alert that immediately notifies the appropriate person
- Clinical Decision Support — tools that provide knowledge and prompts at the point of care
- Alert Fatigue — reduced response to alerts because of overload
- Override — clinician decision to proceed despite an alert
- Early Warning Score — score from vital signs that flags possible deterioration
HIMSS Organizational Position
HIMSS supports health technology professionals through its communities, education, and certification programs. The HIMSS Nursing Informatics Community is one place for nurses working with decision support and alerts to connect with peers.
🔗 Explore Further: External References
- Poly, Islam, and Yang (2020), JMIR Medical Informatics — Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review https://pubmed.ncbi.nlm.nih.gov/32706721/
- Hussain, Reynolds, and Zheng (2019), Journal of the American Medical Informatics Association — Medication Safety Alert Fatigue May Be Reduced via Interaction Design and Clinical Role Tailoring: A Systematic Review https://pubmed.ncbi.nlm.nih.gov/31206159/
- Honeyford et al. (2026), Health and Social Care Delivery Research — Digital Alerting to Improve Sepsis Detection and Patient Outcomes in NHS Trusts: A Multi-Methods Study https://pubmed.ncbi.nlm.nih.gov/41773349/
- HealthIT.gov — Clinical Decision Support https://healthit.gov/clinical-quality-and-safety/clinical-decision-support/
- HealthIT.gov — SAFER Guides https://healthit.gov/clinical-quality-and-safety/safer-guides/
- HIMSS — Nursing Informatics Community https://www.himss.org/networking/communities/nursing-informatics/
Term source: HIMSS Dictionary of Health Information and Technology Terms, Acronyms, and Organizations, 6th Edition (2025). All definitions in this series are paraphrased for editorial purposes. Readers are encouraged to consult the primary source for exact language.
Eric Andrew Kristof, RN, CAHIMS is a Healthcare IT professional and HIMSS Arkansas Chapter member based in Hot Springs Village, AR, with hands-on Epic Go-Live experience and a diverse healthcare and IT background. He writes at kristof.org at the intersection of clinical care and healthcare technology.
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