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

Epidemiol Prev. 2016 Mar-Apr;40(2):124-30. doi: 10.19191/EP16.2.P124.067.
[Article in Italian]

Abstract

Objectives: 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.

Design: 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.

Setting and participants: 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.

Publication types

  • Validation Study

MeSH terms

  • Algorithms*
  • Birth Certificates
  • Congenital Abnormalities / epidemiology*
  • Hospital Records / statistics & numerical data*
  • Humans
  • Infant
  • Infant, Newborn
  • Italy / epidemiology
  • Patient Discharge / statistics & numerical data*
  • Public Health
  • Registries / statistics & numerical data
  • Reproducibility of Results