Evidence map›Paper›PMID 27438027›Full record

ArticleEmergency radiology2016

Privately insured medical patients are more likely to have a head CT.

Emily M Fortin, Jerry Fisher, Sheng Qiu, Charlene Irvin Babcock

Abstract read
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In one paragraph

Article in Emergency radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
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.

Emily M FortinCentral Michigan University College of Medicine, Mt. Pleasant, MI, USA. fortinem@gmail.com.
Jerry FisherDepartment of Emergency Medicine, St. John Hospital and Medical Center, Detroit, MI, USA.
Sheng QiuDepartment of Biostatistics, University of Michigan, Ann Arbor, MI, USA.
Charlene Irvin BabcockDepartment of Emergency Medicine, St. John Hospital and Medical Center, Detroit, MI, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Previous studies suggest overuse disparity of head computed tomography (CT) in white pediatric trauma patients with minor head injuries. Our study is meant to determine if race or insurance status impacts the probability of obtaining head CT in patients with a Glasgow Coma Scale (GCS) = 15. Using the 2008-2010 National Hospital Ambulatory Medical Care Survey for Emergency Departments (NHAMCS) database, the following variables were analyzed: race, emergency medical services (EMS) arrival, triage category, admission status, gender, age, and insurance status. Patients with injuries were excluded. All patients included had GCS = 15. In univariate analysis, head CT is more likely to be obtained for patients in the following categories: Medicare insured, private insurance, Medicaid insured, and self-pay, EMS arrival, triage category immediate, and age >75 years. In logistic regression, race (white vs. black) was no longer significant, but there was disparity based on insurance status with privately insured patients more likely to receive a head CT (OR = 1.683, 95 % CI = 1.255-2.259). After controlling for the above inclusion variables and focusing on patients less likely to need CT (non-traumatic with GCS = 15), privately insured patients were more likely to receive a head CT compared with uninsured. Race alone was not associated with an increased probability of receiving a head CT.

Indexed as

Insurance CoverageAdolescentAdultAgedCraniocerebral TraumaEmergency Service, HospitalFemaleGlasgow Coma ScaleHealthcare DisparitiesHumansMaleMiddle AgedTomography, X-Ray ComputedUnited StatesClinical decision makingCTDisparityInsuranceRadiation

Identifiers

What OpenQuestion holds

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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.