Police and hospital data linkage for traffic injury surveillance: A systematic review

Ali Soltani; James Edward Harrison; Courtney Ryder; Joanne Flavel; Angela Watson

doi:10.1016/j.aap.2023.107426

Police and hospital data linkage for traffic injury surveillance: A systematic review

Accid Anal Prev. 2024 Mar:197:107426. doi: 10.1016/j.aap.2023.107426. Epub 2024 Jan 5.

Authors

Ali Soltani¹, James Edward Harrison², Courtney Ryder³, Joanne Flavel⁴, Angela Watson⁵

Affiliations

¹ Injury Studies, FHMRI, Bedford Park, Flinders University, SA 5042, Australia; Urban Planning Department, Shiraz University, Shiraz, Iran. Electronic address: ali.soltani@flinders.edu.au.
² Injury Studies, FHMRI, Bedford Park, Flinders University, SA 5042, Australia. Electronic address: james.harrison@flinders.edu.au.
³ Injury Studies, FHMRI, Bedford Park, Flinders University, SA 5042, Australia; George Institute for Global Health, Newtown, NSW 2042, Australia; School of Population Health, UNSW, Kensington, NSW 2052, Australia. Electronic address: Courtney.ryder@flinders.edu.au.
⁴ Injury Studies, FHMRI, Bedford Park, Flinders University, SA 5042, Australia; Stretton Institute, University of Adelaide, SA 5005, Australia. Electronic address: joanne.flavel@adelaide.edu.au.
⁵ The Australian Centre for Health Services Innovation (AusHSI), Queensland University of Technology, Qld 4000, Australia; School of Public Health & Social Work, Queensland University of Technology, Qld 4000, Australia. Electronic address: angela.watson@qut.edu.au.

PMID: 38183692
DOI: 10.1016/j.aap.2023.107426

Abstract

This systematic review examines studies of traffic injury that involved linkage of police crash data and hospital data and were published from 1994 to 2023 worldwide in English. Inclusion and exclusion criteria were the basis for selecting papers from PubMed, Web of Science, and Scopus, and for identifying additional relevant papers using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) and supplementary snowballing (n = 60). The selected papers were reviewed in terms of research objectives, data items and sample size included, temporal and spatial coverage, linkage methods and software tools, as well as linkage rates and most significant findings. Many studies found that the number of clinically significant road injury cases was much higher according to hospital data than crash data. Under-estimation of cases in crash data differs by road user type, pedestrian cases commonly being highly under-counted. A limited number of the papers were from low- and middle-income countries. The papers reviewed lack consistency in what was reported and how, which limited comparability.

Keywords: Data linkage; Injury; PRISMA; Systematic review; Traffic crash.

Publication types

Systematic Review

MeSH terms

Accidents, Traffic* / statistics & numerical data
Data Accuracy
Hospitals
Humans
Information Sources
Pedestrians
Police
Wounds and Injuries* / epidemiology