Improving the quality of data entry in a low-budget head injury database.
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.


METHODS
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.


RESULTS
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.
Neurointensive Care Unit, IRCCS Ospedale S. Raffaele, Milano, Italy. beretta.luigi@hsr.it
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L
Beretta
V
V
Aldrovandi
E
E
Grandi
G
G
Citerio
N
N
Stocchetti
D001930:Brain Injuries / Q000628:therapy; D002017:Budgets; D003625:Data Collection / Q000592:standards*; D016208:Databases, Factual / Q000191:economics*; D006801:Humans; D007362:Intensive Care Units; D008330:Management Audit