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


METHODS
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.


METHODS
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.


RESULTS
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%).


CONCLUSIONS
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.
Registro indagini sulle malformazioni congenite in Emilia-Romagna (IMER), Dipartimento di scienze biomediche e chirurgico-specialistiche, Università di Ferrara.
Gianni
G
Astolfi
Registro delle malformazioni congenite, Osservatorio epidemiologico, ASL Mantova.
Paolo
P
Ricci
Registro indagini sulle malformazioni congenite in Emilia-Romagna (IMER), Azienda ospedaliera di Ferrara.
Elisa
E
Calzolari
Registro indagini sulle malformazioni congenite in Emilia-Romagna (IMER), Azienda ospedaliera di Ferrara.
Amanda
A
Neville
Registro delle malformazioni congenite, Osservatorio epidemiologico, ASL Mantova.
Vanda
V
Pironi
Unità di epidemiologia ambientale e registri di patologia, Istituto di fisiologia clinica, Consiglio nazionale delle ricerche, Pisa.
Michele
M
Santoro
Unità di epidemiologia ambientale e registri di patologia, Istituto di fisiologia clinica, Consiglio nazionale delle ricerche, Pisa.
Fabrizio
F
Bianchi
D000465:Algorithms; D001719:Birth Certificates; D000013:Congenital Abnormalities / Q000453:epidemiology*; D006753:Hospital Records / Q000706:statistics & numerical data*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007558:Italy / Q000453:epidemiology; D010351:Patient Discharge / Q000706:statistics & numerical data*; D011634:Public Health; D012042:Registries / Q000706:statistics & numerical data; D015203:Reproducibility of Results