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Small for Gestational Age Coded Diagnoses in Aotearoa New Zealand's Administrative Health Datasets: A Validation

Mei-Ling Blank1, Sarah Donald1,2, Lianne Parkin1,2

  • 1Department of Preventive and Social Medicine (Te Tari Hauora Tūmatanui) University of Otago (Ōtākou Whakaihu Waka) Dunedin New Zealand.

Health Science Reports
|May 1, 2025
PubMed

Insights

Routinely collected health data inaccurately codes small for gestational age (SGA) infants. Researchers should use birthweight calculators instead of ICD-10-AM codes for accurate SGA research in New Zealand.

Area of Science:

  • Medical Informatics
  • Neonatal Research
  • Public Health Data Analysis

Background:

  • Accurate identification of small for gestational age (SGA) infants is crucial for research utilizing routinely collected health data.
  • Inconsistent coding practices for SGA infants can significantly impact the validity and reliability of research findings.
  • This study addresses the implications of inaccurate SGA coding in New Zealand's health data.

Purpose of the Study:

  • To estimate the sensitivity and specificity of coded SGA diagnoses in New Zealand's hospitalisation and mortality data.
  • To determine if coding accuracy for SGA varies based on infant, pregnancy, and maternal characteristics.
  • To provide recommendations for improving SGA data accuracy in population-level research.

Main Methods:

  • Utilized New Zealand national health data (2005-2020) for 887,871 infants.
  • Estimated birthweight centiles using Fenton and GROW calculators.
  • Compared calculator-derived SGA status with ICD-10-AM coded SGA diagnoses (P051).
  • Employed generalized linear models to calculate sensitivity and specificity ratios, adjusting for covariates.

Main Results:

  • Coded SGA diagnoses showed low sensitivity (13.1% vs. Fenton, 9.8% vs. GROW) but high specificity (99.3% vs. Fenton, 99.7% vs. GROW).
  • Significant discrepancies exist between coded SGA diagnoses and calculator-derived classifications.
  • The proportion of SGA infants identified by calculators (9.1%-15.6%) far exceeded those with coded diagnoses (1.8%).

Conclusions:

  • Relying on ICD-10-AM coded SGA diagnoses in New Zealand health data is unreliable for research.
  • Population-level research on SGA should utilize validated birthweight calculators for accurate infant classification.
  • Improved data ascertainment methods are needed to ensure the integrity of SGA research.
Abstract

Keywords:
ICD‐10birthweightsensitivitysmall for gestational agespecificityvalidation

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