Evidence map›Paper›PMID 27437061›Full record

ArticleApplied clinical informatics2016

Validation of Test Performance and Clinical Time Zero for an Electronic Health Record Embedded Severe Sepsis Alert.

Joshua Rolnick, N Lance Downing, John Shepard, Weihan Chu, Julia Tam, Alexander Wessels, Ron Li, Brian Dietrich, Michael Rudy, Leon Castaneda and 1 more

Open access · bronzeAbstract readValidation Study
In one paragraph

Article in Applied clinical informatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 16 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

11 authors at 3 institutions in 1 country.

Joshua RolnickSanta Clara Valley Medical Center.
N Lance DowningStanford Hospital & Clinics.
John ShepardStanford Hospital & Clinics.
Weihan ChuStanford School of Medicine.
Julia TamStanford Hospital & Clinics.
Alexander WesselsSagacious Consultants.
Ron LiStanford Hospital & Clinics.
Brian DietrichStanford Hospital & Clinics.
Michael RudyStanford Hospital & Clinics.
Leon CastanedaStanford Hospital & Clinics.
Lisa ShiehStanford School of Medicine.
Stanford Health Care · USStanford Medicine · USSanta Clara Valley Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

bachgroundIncreasing use of EHRs has generated interest in the potential of computerized clinical decision support to improve treatment of sepsis. Electronic sepsis alerts have had mixed results due to poor test characteristics, the inability to detect sepsis in a timely fashion and the use of outside software limiting widespread adoption. We describe the development, evaluation and validation of an accurate and timely severe sepsis alert with the potential to impact sepsis management.

objectiveTo develop, evaluate, and validate an accurate and timely severe sepsis alert embedded in a commercial EHR.

methodsThe sepsis alert was developed by identifying the most common severe sepsis criteria among a cohort of patients with ICD 9 codes indicating a diagnosis of sepsis. This alert requires criteria in three categories: indicators of a systemic inflammatory response, evidence of suspected infection from physician orders, and markers of organ dysfunction. Chart review was used to evaluate test performance and the ability to detect clinical time zero, the point in time when a patient develops severe sepsis.

resultsTwo physicians reviewed 100 positive cases and 75 negative cases. Based on this review, sensitivity was 74.5%, specificity was 86.0%, the positive predictive value was 50.3%, and the negative predictive value was 94.7%. The most common source of end-organ dysfunction was MAP less than 70 mm/Hg (59%). The alert was triggered at clinical time zero in 41% of cases and within three hours in 53.6% of cases. 96% of alerts triggered before a manual nurse screen.

conclusionWe are the first to report the time between a sepsis alert and physician chart-review clinical time zero. Incorporating physician orders in the alert criteria improves specificity while maintaining sensitivity, which is important to reduce alert fatigue. By leveraging standard EHR functionality, this alert could be implemented by other healthcare systems.

Indexed as

Decision Support Systems, ClinicalElectronic Health RecordsHumansPhysiciansSepsisTime Factorsclinical decision supportinpatient caremedicineperformance improvementTesting and evaluation

Identifiers

PMID27437061
PMCPMC4941860
OpenAlexW2474234325

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.