Investigation of bias after data linkage of hospital admissions data to police road traffic crash reports.
OBJECTIVE
Does a database of hospital admission data linked to police road traffic accident (RTA) reports produce less biased information for the injury prevention policymaker, planner, and practitioner than police RTA reports alone?


METHODS
Data linkage study.


METHODS
Non-fatal injury victims of road traffic crashes in southern England who were admitted to hospital.


METHODS
Hospital admissions and police RTA reports.


METHODS
The estimated proportion of road traffic crashes admitted to hospital that were included on the linked database; distributions by age, sex, and road user groups: (A) for all RTA injury admissions and (B) for RTA serious injury admissions defined by length of stay or by nature of injury.


RESULTS
An estimated 50% of RTA injury admissions were included on the linked database. When assessing bias, admissions data were regarded as the "gold standard". The distributions of casualties by age, sex, and type of road user showed major differences between the admissions data and the police RTA injury data of comparable severity. The linked data showed smaller differences when compared with admissions data. For RTA serious injury admissions, the distributions by age and sex were approximately the same for the linked data compared with admissions data, and there were small but statistically significant differences between the distributions across road user group for the linked data compared with hospital admissions.


CONCLUSIONS
These results suggest that investigators could be misinformed if they base their analysis solely on police RTA data, and that information derived from the linked database is less biased than that from police RTA data alone. A national linked dataset of road traffic crash data should be produced from hospital admissions and police RTA data for use by policymakers, planners and practitioners.
Cryer
P C
PC
Centre for Health Services Studies, University of Kent, Canterbury, UK. P.C.Cryer@ukc.ac.uk
Westrup
S
S
Cook
A C
AC
Ashwell
V
V
Bridger
P
P
Clarke
C
C
D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000368:Aged; D015982:Bias; D016009:Chi-Square Distribution; D005260:Female; D006760:Hospitalization; D006801:Humans; D007231:Infant, Newborn; D008297:Male; D008499:Medical Records; D008875:Middle Aged; D016495:Police