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Background. To assess the efficacy of a centralised review of a voluntary low-budget head injury database with a retrospective analysis of data before and after a centralised review. Method. A computerised data collection (Neurolink) on traumatic brain injury cases admitted to three neuro-intensive care units in Milan (Italy): analysis of a three-year period (1999–2001). Data from 499 patients (epidemiology, type of lesion, clinical course, monitoring, treatment, complications and outcome). The audit involved a review of forms relating to patients enrolled in the three-year period, with the aim of improving the quality of data entry. Missing data in all empty fields were identified; evident errors and contradictory data were identified and corrected; missing and final data were analysed to test the efficacy of the review. Findings. The total post-review missing data rate was significantly lower than the paired pre-review missing data rate ( p = 0.001). The same was confirmed for each of the 3 years ( p = 0.001 for each year). The missing data rate significantly improved over the three-year period ( p = 0.001). Data for the pre-hospitalisation period had the highest missing rates; data regarding the ICU stay showed the greatest improvement after the review. A total of 407 items (0.44%) were identified as errors. Conclusions. Data quality is fundamental to avoid information bias in database analysis. This study indicates that it is possible to generate a serious data collection without significant resources. Audit seems to be an important tool before the final data is used for scientific projects. [ABSTRACT FROM AUTHOR]