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Abstract Background In France, like in most developed countries, the number of road accident fatalities is estimated from police data. These estimates are considered to be good-quality, unlike estimates of road injuries admitted to hospital, and especially serious injuries. Methods The present study aimed to supply such data from French hospital medical information data-bases (PMSI). In the PMSI data-bases, road accident victims are identified by external causes of morbidity and mortality, which should be systematically recorded in case of injury, but are often missing. We therefore modeled presence/absence of external cause from the relevant subset of the medicine-surgery-obstetrics PMSI data-base using a logistic regression, and then weighting the results by inverse estimated probability. As ICD-10 coding does not include injury severity, we used the AAAM10 conversion instrument developed by the American Association for Automotive Medicine, originators of the Abbreviated Injury Scale, so as to conform to the European Commission’s definition of serious injury. Results The number of road-accident related hospital admissions is estimated to be about 100000 per year; serious injuries increased from about 18000 in 2010 to almost 20000 in 2017, with almost 17000 in 2012 and 2013, with a mean of one fatality per 5 serious injury admissions. Conclusions These serious injury estimates are close to those obtained by our team from other data and with a different estimation method. The present method has the advantage of using ICD codes for injured people admitted to hospital. This classification and data source (hospital discharge registry) are also used by most european countries reporting serious injury estimates to the Commission. It allows cost estimation of hospital care, and could be applied to other types of accidental injury.

INTRODUCTION:This study aimed to determine the sleepiness-related factors associated with road traffic accidents. METHODS:A population based case-control study was conducted in 2 French agglomerations. 272 road accident cases hospitalized in emergency units and 272 control drivers matched by time of day and randomly stopped by police forces were included in the study. Odds ratios were calculated for the risk of road traffic accidents. RESULTS:As expected, the main predictive factor for road traffic accidents was having a sleep episode at the wheel just before the accident (OR 9.97, CI 95%: 1.57-63.50, p