ArticleApplied clinical informatics2019
Evaluating the Impact of Interruptive Alerts within a Health System: Use, Response Time, and Cumulative Time Burden.
Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 27 citations in OpenAlex.
- Lessons Learned from Sepsis Microlearning Intervention.Applied clinical informatics · 2025Trial
- Improving sepsis best practice utility and clinical acceptance using an LLM-enhanced prediction system.npj health systems · 2026Article
- Promoting palliative care for people with heart failure: the P3HF study protocol.BMC palliative care · 2026Article
- Experiences of Alert Fatigue and Its Contributing Factors in Hospitals: Qualitative Study.Journal of medical Internet research · 2026Article
- A Systematic Approach to Screen, Identify, and Correct Malfunctioning Interruptive Alerts.Applied clinical informatics · 2025Article
- Evolution of an Electronic Health Record-Based Alert to Optimize Venous Thromboembolism Prophylaxis.Applied clinical informatics · 2025Article
- Do Decision Support Tools Decrease the Prevalence of Hospital-Acquired Venous Thromboembolisms When Compared to Clinical Judgement? A Single-Center Pre-Post Study.Journal of clinical medicine · 2024Article
- Randomized Comparison of Electronic Health Record Alert Types in Eliciting Responses about Prognosis in Gynecologic Oncology Patients.Applied clinical informatics · 2024Article
- Addressing Alert Fatigue by Replacing a Burdensome Interruptive Alert with Passive Clinical Decision Support.Applied clinical informatics · 2024Article
- Clinical Informatics in Critical Care Medicine.The Yale journal of biology and medicine · 2023Review
- Acceptance of Acute Kidney Injury Alert by Providers in Cardiac Surgery Intensive Care Unit.Applied clinical informatics · 2023Article
- The value of incorporating patient-consulted medication reconciliation in influencing drug-related actions in the outpatient rheumatology setting.BMC health services research · 2022Observational
- Impact of Kidney Failure Risk Prediction Clinical Decision Support on Monitoring and Referral in Primary Care Management of CKD: A Randomized Pragmatic Clinical Trial.Kidney medicine · 2022Article
- Clinical Decision Support Stewardship: Best Practices and Techniques to Monitor and Improve Interruptive Alerts.Applied clinical informatics · 2022Review
- Modulators Influencing Medication Alert Acceptance: An Explorative Review.Applied clinical informatics · 2022Review
- Electronic Health Record Data in Cancer Learning Health Systems: Challenges and Opportunities.JCO clinical cancer informatics · 2022Review
- Associations of physicians' prescribing experience, work hours, and workload with prescription errors.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- An Alternate Viewpoint on Information Sharing: There is no Paradox.Applied clinical informatics · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHealth systems often employ interruptive alerts through the electronic health record to improve patient care. However, concerns of "alert fatigue" have been raised, highlighting the importance of understanding the time burden and impact of these alerts on providers.
objectivesOur main objective was to determine the total time providers spent on interruptive alerts in both inpatient and outpatient settings. Our secondary objectives were to analyze dwell time for individual alerts and examine both provider and alert-related factors associated with dwell time variance.
methodsWe retrospectively evaluated use and response to the 75 most common interruptive ("popup") alerts between June 1st, 2015 and November 1st, 2016 in a large academic health care system. Alert "dwell time" was calculated as the time between the alert appearing on a provider's screen until it was closed. The total number of alerts and dwell times per provider per month was calculated for inpatient and outpatient alerts and compared across alert type.
resultsThe median number of alerts seen by a provider was 12 per month (IQR 4-34). Overall, 67% of inpatient and 39% of outpatient alerts were closed in under 3 seconds. Alerts related to patient safety and those requiring more than a single click to proceed had significantly longer median dwell times of 5.2 and 6.7 seconds, respectively. The median total monthly time spent by providers viewing alerts was 49 seconds on inpatient alerts and 28 seconds on outpatient alerts.
conclusionMost alerts were closed in under 3 seconds and a provider's total time spent on alerts was less than 1 min/mo. Alert fatigue may lie in their interruptive and noncritical nature rather than time burden. Monitoring alert interaction time can function as a valuable metric to assess the impact of alerts on workflow and potentially identify routinely ignored alerts.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.