Linking emergency medical department and road traffic police casualty data: a tool in assessing the burden of injuries in less resourced countries.
OBJECTIVE
The study aimed to (1) assess the magnitude of road traffic injuries in a country missing a formal linkage system of police with hospital data, (2) quantify the underreporting, and (3) produce a convenient algorithm exploring its constituent components.


METHODS
Linkage of disaggregate (individual) data collected by the road traffic police (RTP) with those by the Emergency Department Injury Surveillance System (EDISS) on the Greek island of Corfu and coded with different classification systems was carried out. The applied four-step methodology, also comprising the calculation of underreporting coefficients of the variation by basic demographic variables, mode of transport, and injury outcome, led to the identification of the overall underreporting from either registry.


RESULTS
RTP data captured 96.6% (coefficient: 1.035), whereas EDISS captured only 54.4% of total fatalities (overall concordance: 51.1%). On the contrary, EDISS captured 94.6% of nonfatal injuries, whereas RTP only captured 16% (coefficient: 6.238), resulting in a low overall concordance (10.6%). Considering severity of injury assessed by EDISS, by using the ISS as the gold standard, RTP data misclassified 20.3% of severe injuries as less severe, and a statistically significant difference in the underreporting by gender was also noted.


CONCLUSIONS
Relatively simple methodologies can provide essential coefficients to assess the actual numbers, severity, and components of road casualties by complementing routinely collected RTP with sentinel emergency department reporting systems.
Petridou
Eleni Th
ET
Department of Hygiene, Epidemiology and Medical Statistics, Athens University Medical School, Athens, Greece. epetrid@med.uoa.gr
Yannis
George
G
Terzidis
Agapios
A
Dessypris
Nick
N
Germeni
Evi
E
Evgenikos
Petros
P
Tselenti
Natalia
N
Chaziris
Antonis
A
Skalkidis
Ilias
I
D000063:Accidents, Traffic / Q000706:statistics & numerical data*; D000293:Adolescent; D000328:Adult; D000368:Aged; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D004632:Emergency Medical Services / Q000706:statistics & numerical data*; D005260:Female; D006115:Greece / Q000453:epidemiology; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D015601:Injury Severity Score; D008297:Male; D008498:Medical Record Linkage / Q000379:methods*; D008875:Middle Aged; D016495:Police / Q000706:statistics & numerical data*; D018571:Sentinel Surveillance; D014947:Wounds and Injuries / Q000453:epidemiology*