Evidence map›Paper›PMID 25849969›Full record

ArticlePloS one2015

An automated clinical alert system for newly-diagnosed atrial fibrillation.

David A Cook, Felicity Enders, Pedro J Caraballo, Rick A Nishimura, Farrell J Lloyd

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 28 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 1 institution in 1 country.

David A CookKnowledge Delivery Center, Mayo Clinic, Rochester, MN, United States of America; Division of General Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN, United States of America; Mayo Clinic Online Learning, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Felicity EndersKnowledge Delivery Center, Mayo Clinic, Rochester, MN, United States of America; Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Pedro J CaraballoKnowledge Delivery Center, Mayo Clinic, Rochester, MN, United States of America; Division of General Internal Medicine, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Rick A NishimuraKnowledge Delivery Center, Mayo Clinic, Rochester, MN, United States of America; Division of Cardiovascular Diseases, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Farrell J LloydKnowledge Delivery Center, Mayo Clinic, Rochester, MN, United States of America; Division of Hospital Medicine, Mayo Clinic College of Medicine, Rochester, MN, United States of America.
Mayo Clinic · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveClinical decision support systems that notify providers of abnormal test results have produced mixed results. We sought to develop, implement, and evaluate the impact of a computer-based clinical alert system intended to improve atrial fibrillation stroke prophylaxis, and identify reasons providers do not implement a guideline-concordant response. MATERIALS AND

methodsWe conducted a cohort study with historical controls among patients at a tertiary care hospital. We developed a decision rule to identify newly-diagnosed atrial fibrillation, automatically notify providers, and direct them to online evidence-based management guidelines. We tracked all notifications from December 2009 to February 2010 (notification period) and applied the same decision rule to all patients from December 2008 to February 2009 (control period). Primary outcomes were accuracy of notification (confirmed through chart review) and prescription of warfarin within 30 days.

resultsDuring the notification period 604 notifications were triggered, of which 268 (44%) were confirmed as newly-diagnosed atrial fibrillation. The notifications not confirmed as newly-diagnosed involved patients with no recent electrocardiogram at our institution. Thirty-four of 125 high-risk patients (27%) received warfarin in the notification period, compared with 34 of 94 (36%) in the control period (odds ratio, 0.66 [95% CI, 0.37-1.17]; p = 0.16). Common reasons to not prescribe warfarin (identified from chart review of 151 patients) included upcoming surgical procedure, choice to use aspirin, and discrepancy between clinical notes and the medication record.

conclusionsAn automated system to identify newly-diagnosed atrial fibrillation, notify providers, and encourage access to management guidelines did not change provider behaviors.

Indexed as

Clinical AlarmsAgedAnticoagulantsAtrial FibrillationAutomationCohort StudiesDecision Support Systems, ClinicalDrug PrescriptionsFemaleHumansMaleOutcome Assessment, Health CareStrokeTertiary Health CareWarfarinAnticoagulantsWarfarin

Identifiers

PMID25849969
PMCPMC4388495
OpenAlexW2009734530

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.