Development and validation of a simple algorithm to estimate common gestational age categories using standard administrative birth record data in Ontario, Canada.
Algorithms
Biomedical Research
/ methods
Birth Certificates
Canada
/ epidemiology
Data Accuracy
Database Management Systems
/ organization & administration
Databases, Factual
/ standards
Female
Gestational Age
Humans
Infant Health
/ standards
Infant, Newborn
Male
Maternal Health
/ standards
Pregnancy
Pregnancy Outcome
/ epidemiology
Quality Improvement
Registries
/ standards
Sex Distribution
MOMBABY database
Ontario
algorithm
routine
sex-specific
Journal
Journal of obstetrics and gynaecology : the journal of the Institute of Obstetrics and Gynaecology
ISSN: 1364-6893
Titre abrégé: J Obstet Gynaecol
Pays: England
ID NLM: 8309140
Informations de publication
Date de publication:
Feb 2021
Feb 2021
Historique:
pubmed:
28
6
2020
medline:
2
10
2021
entrez:
28
6
2020
Statut:
ppublish
Résumé
Gestational age is often incompletely recorded in administrative records, despite being critical to paediatric and maternal health research. Several algorithms exist to estimate gestational age using administrative databases; however, many have not been validated or use complicated methods that are not readily adaptable. We developed a simple algorithm to estimate common gestational age categories from routine administrative data. We leveraged a population-based registry of all hospital births occurring in Ontario, Canada over 2002-2016 including 1.8 million birth records. In this sample, this simple algorithm had excellent performance compared to a verified measure of gestational age; 87.61% agreement (95% CI: 87.49, 87.74). The accuracy of the algorithm exceeded 98% for all of the gestational age categories. Agreement notably increased over time and was greatest among singleton births and infants born at 2500-2999 g. This study provides a straight-forward algorithm for accurately estimating common gestational age categories that is easily adaptable for use in other countries.Impact Statement
Identifiants
pubmed: 32590915
doi: 10.1080/01443615.2020.1726304
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM