[Validation of an algorithm for identifying cases with congenital malformations by using hospital discharge records]

to evaluate and validate the use of an algorithm designed to identify in hospital discharge records (SDO) cases with congenital malformations (MC) at birth and/or reported in hospitalizations within the first year of life using as gold standard the Congenital malformation Registry of the Local Health Unit of Mantova, Northern Italy, (RMC-MN), which controls all the medical records of infants born to mothers living in the province.

an algorithm designed for the identification of malformed cases in the SDO database using two modules, one for identification of cases potentially malformed and one for their validation was used. A comparison of the results with those observed by the RMC-MN was then conducted.

data of the SDO and the RMC-MN for the period 2010-2011 relative to those detected in newborns within the first year of life in the resident population in the province.

of 8,042 infants born to mothers residing in the province of Mantova, 7,367 were excluded by the algorithm as malformed with the exception of only one false negative (negative predictive value - NPV: 99.99%); in the remaining 675 cases (8.4%) there was at least one code of congenital malformation. The algorithm has also included 396 cases (4.9%) with isolated minor malformations or diseases considered not malformations, of which 23 were false negatives (NPV: 94.2%). In the remaining 279 cases potentially malformed the algorithm considered as validated 169 cases (60.6%), including 11 false positives (positive predictive value - PPV: 93.5%). In the remaining 110 cases to evaluate, 46 were true positives (PPV: 41.8%).

the proposed instrument has identified correctly SDO in 89.4% of cases registered by the RMC-MN to produce a small number of false positives among the validated cases (6.5%) and effectively exclude inappropriate cases (94.2%). The authors suggest a judicious use of the instrument, which should be led by experts of SDO, clinical and epidemiology of congenital malformations.