Evidence map›Paper›PMID 22278302›Full record

Trial reportJournal of general internal medicine2012

Impact of automated alerts on follow-up of post-discharge microbiology results: a cluster randomized controlled trial.

Robert El-Kareh, Christopher Roy, Deborah H Williams, Eric G Poon

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of general internal medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  18. Clinical microbiology informatics.Clinical microbiology reviews · 2014
    Review
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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

4 authors.

Robert El-KarehDivision of Biomedical Informatics, University of California San Diego, 9500 Gilman Dr., no. 0505, La Jolla, San Diego, CA 92093-0505, USA, relkareh@ucsd.edu
Christopher Roy
Deborah H Williams
Eric G Poon

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
NLM NIH HHS 2T15 LM 007092-17NLM NIH HHS T15 LM007092
6 · The paper itself

Abstract

backgroundFailure to follow up microbiology results pending at the time of hospital discharge can delay diagnosis and treatment of important infections, harm patients, and increase the risk of litigation. Current systems to track pending tests are often inadequate.

objectiveTo design, implement, and evaluate an automated system to improve follow-up of microbiology results that return after hospitalized patients are discharged.

designCluster randomized controlled trial. SUBJECTS: Inpatient and outpatient physicians caring for adult patients hospitalized at a large academic hospital from February 2009 to June 2010 with positive and untreated or undertreated blood, urine, sputum, or cerebral spinal fluid cultures returning post-discharge.

interventionAn automated e-mail-based system alerting inpatient and outpatient physicians to positive post-discharge culture results not adequately treated with an antibiotic at the time of discharge. MAIN MEASURES: Our primary outcome was documented follow-up of results within 3 days. Secondary outcomes included physician awareness and assessment of result urgency, impact on clinical assessments and plans, and preferred alerting scenarios. KEY

resultsWe evaluated the follow-up of 157 post-discharge microbiology results from patients of 121 physicians. We found documented follow-up in 27/97 (28%) results in the intervention group and 8/60 (13%) in the control group [aOR 3.2, (95% CI 1.3-8.4); p=0.01]. Of all inpatient physician respondents, 32/82 (39%) were previously aware of the results, 45/77 (58%) felt the results changed their assessments and plans, 43/77 (56%) felt the results required urgent action, and 67/70 (96%) preferred alerts for current or broader scenarios.

conclusionOur alerting system improved the proportion of important post-discharge microbiology results with documented follow-up, though the proportion remained low. The alerts were well received and may be expanded in the future.

Indexed as

AdultAgedAged, 80 and overAutomationCluster AnalysisContinuity of Patient CareDiagnostic Tests, RoutineElectronic MailFollow-Up StudiesHumansMedical Order Entry SystemsMiddle AgedPatient DischargeProspective Studies

Identifiers

PMID22278302
PMCPMC3445692

What OpenQuestion holds

Textmetadata
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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.