Evidence map›Paper›PMID 23806535›Full record

ArticleGeneral hospital psychiatry

The development of a population-based automated screening procedure for PTSD in acutely injured hospitalized trauma survivors.

Joan Russo, Wayne Katon, Douglas Zatzick

Abstract read
In one paragraph

Article in General hospital psychiatry. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 2 pooled it
7.8field-weighted citation impact, top 3% 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

50 citing papers in PubMed, 2 syntheses or guidelines pooled it, 96 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

3 authors at 2 institutions in 1 country.

Joan RussoDepartment of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA 98104, USA.
Wayne Katon
Douglas Zatzick
University of Washington · USHarborview Injury Prevention and Research Center · US

Funding

Disseminating Organizational SBI Services (DO-SBIS) at Trauma CentersR01AA016102 · NIAAA · UNIVERSITY OF WASHINGTON · PI ZATZICK, DOUGLAS F · 2007 to 2011
$3.2M
Early Combined Intervention After Traumatic InjuryR01MH073613 · NIMH · UNIVERSITY OF WASHINGTON · PI ZATZICK, DOUGLAS F · 2005 to 2010
$2.7M
Research, Mentoring & Dissemination for PTSD Intervention in Acute Care SettingsK24MH086814 · NIMH · UNIVERSITY OF WASHINGTON · PI ZATZICK, DOUGLAS F · 2010 to 2014
$867k
NIAAA NIH HHS R01 AA016102NIMH NIH HHS K24 MH086814NIMH NIH HHS R01 MH073613NIMH NIH HHS R01MH073613-05S1
6 · The paper itself

Abstract

objectiveThis investigation aimed to advance posttraumatic stress disorder (PTSD) risk prediction among hospitalized injury survivors by developing a population-based automated screening tool derived from data elements available in the electronic medical record (EMR).

methodPotential EMR-derived PTSD risk factors with the greatest predictive utilities were identified for 878 randomly selected injured trauma survivors. Risk factors were assessed using logistic regression, sensitivity, specificity, predictive values and receiver operator characteristic (ROC) curve analyses.

resultsTen EMR data elements contributed to the optimal PTSD risk prediction model including International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) PTSD diagnosis, other ICD-9-CM psychiatric diagnosis, other ICD-9-CM substance use diagnosis or positive blood alcohol on admission, tobacco use, female gender, non-White ethnicity, uninsured, public or veteran insurance status, E-code identified intentional injury, intensive care unit admission and EMR documentation of any prior trauma center visits. The 10-item automated screen demonstrated good area under the ROC curve (0.72), sensitivity (0.71) and specificity (0.66).

conclusionsAutomated EMR screening can be used to efficiently and accurately triage injury survivors at risk for the development of PTSD. Automated EMR procedures could be combined with stepped care protocols to optimize the sustainable implementation of PTSD screening and intervention at trauma centers nationwide.

Indexed as

AdultElectronic Health RecordsFemaleHumansInjury Severity ScoreMaleMass ScreeningRisk FactorsSensitivity and SpecificitySex FactorsStress Disorders, Post-TraumaticSubstance-Related DisordersWounds and InjuriesEMRInformation technologyInjuryPTSDScreening

Identifiers

PMID23806535
PMCPMC3784242
OpenAlexW2087203915

What OpenQuestion holds

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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.