Evidence map›Paper›PMID 39135173›Full record

ArticleInjury epidemiology2024

Implications of using administrative healthcare data to identify risk of motor vehicle crash-related injury: the importance of distinguishing crash from crash-related injury.

Nina R Joyce, Leah R Lombardi, Melissa R Pfeiffer, Allison E Curry, Seth A Margolis, Brian R Ott, Andrew R Zullo

Abstract read
In one paragraph

Article in Injury epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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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

7 authors.

Nina R JoyceDepartment of Epidemiology, Brown University School of Public Health, 121 South Main St., Box G-121-S2, Providence, RI, 02192, USA. Nina_Joyce@Brown.edu.
Leah R LombardiCenter for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Melissa R PfeifferCenter for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Allison E CurryCenter for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Seth A MargolisDepartment of Psychiatry, Rhode Island Hospital, Providence, RI, USA.
Brian R OttWarren Alpert Medical School of Brown University, Providence, RI, USA.
Andrew R ZulloDepartment of Epidemiology, Brown University School of Public Health, 121 South Main St., Box G-121-S2, Providence, RI, 02192, USA.

Funding

Science/Technical CoreP2CHD041020 · NICHD · BROWN UNIVERSITY · PI ZHENCHAO QIAN · 2016 to 2026
$7.6M
An integrated approach to establish the scientific foundation for driving among adolescents with autismR01HD096221 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI CURRY, ALLISON ELIZABETH · 2018 to 2022
$3.3M
The risks and consequences of a motor vehicle crash in older adults with Alzheimer's Disease and Related DementiasR01AG079295 · NIA · BROWN UNIVERSITY · PI JOYCE, NINA · 2022 to 2025
$3.0M
Medications and the Risk of Motor Vehicle Crashes in Older AdultsR01AG065722 · NIA · BROWN UNIVERSITY · PI ZULLO, ANDREW REIS · 2020 to 2023
$2.1M
Eunice Kennedy Shriver National Institute of Child Health and Human Development R01HD096221NIA NIH HHS R01 AG065722NIA NIH HHS R01AG065722NIA NIH HHS R01 AG079295NICHD NIH HHS P2C HD041020NICHD NIH HHS R01 HD096221
6 · The paper itself

Abstract

backgroundAdministrative healthcare databases, such as Medicare, are increasingly used to identify groups at risk of a crash. However, they only contain information on crash-related injuries, not all crashes. If the driver characteristics associated with crash and crash-related injury differ, conflating the two may result in ineffective or imprecise policy interventions.

methodsWe linked 10 years (2008-2017) of Medicare claims to New Jersey police crash reports to compare the demographics, clinical diagnoses, and prescription drug dispensings for crash-involved drivers ≥ 68 years with a police-reported crash to those with a claim for a crash-related injury. We calculated standardized mean differences to compare characteristics between groups.

resultsCrash-involved drivers with a Medicare claim for an injury were more likely than those with a police-reported crash to be female (62.4% vs. 51.8%, standardized mean difference [SMD] = 0.30), had more clinical diagnoses including Alzheimer's disease and related dementias (13.0% vs. 9.2%, SMD = 0.20) and rheumatoid arthritis/osteoarthritis (69.5% vs 61.4%, SMD = 0.20), and a higher rate of dispensing for opioids (33.8% vs 27.6%, SMD = 0.18) and antiepileptics (12.9% vs 9.6%, SMD = 0.14) prior to the crash. Despite documented inconsistencies in coding practices, findings were robust when restricted to claims indicating the injured party was the driver or was left unspecified.

conclusionsTo identify effective mechanisms for reducing morbidity and mortality from crashes, researchers should consider augmenting administrative datasets with information from police crash reports, and vice versa. When those data are not available, we caution researchers and policymakers against the tendency to conflate crash and crash-related injury when interpreting their findings.

Indexed as

Crash-related injuryInjuryMedicareMotor vehicle crashOlder driverPolice reported crash

Identifiers

PMID39135173
PMCPMC11318118

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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.