- ICD-10 diagnostic codes alone are insufficient to identify paediatric physical abuse; only 1 of 53 confirmed abuse cases used an abuse-specific code.
- Combining X-ray and fundus examinations improved detection: 73.6% sensitivity and 85.7% specificity in under-10s; 80.9% sensitivity and 79.1% specificity in under-6s.
- Machine learning models including Lasso, random forest, and CART produced consistent findings, supporting procedure-based algorithms for epidemiological surveillance.
Pediatr Int. 2026 Jan-Dec;68(1):e70430. doi: 10.1111/ped.70430.
ABSTRACT
BACKGROUND: Many countries lack comprehensive systems or standardized use of diagnostic codes to track child abuse. This study evaluated the validity of the International Classification of Diseases, 10th Revision (ICD-10) diagnostic codes and developed algorithms to identify physical abuse using administrative data.
METHODS: We analyzed children under 10 years hospitalized for injuries between April 2013 and March 2023 at a children’s hospital in Japan. Child protection team records notifying local services were used as the reference standard. We assessed diagnostic, procedure, and medication codes using machine learning.
RESULTS: Among 1375 injury cases, 53 involved physical abuse, but only one used an abuse-specific ICD-10 code, indicating limited reliability. Combining X-ray and fundus examinations achieved 73.6% sensitivity (95% CI, 59.7-84.7) and 85.7% specificity (95% CI, 83.7-87.5) among children aged < 10 years and 80.9% sensitivity (95% CI, 66.7-90.9) and 79.1% specificity (95% CI, 76.2-81.7) among children aged < 6 years. Several machine learning approaches, including Lasso regression, random forest, and bootstrap classification-and-regression-tree models, yielded broadly consistent findings.
CONCLUSIONS: ICD-10 codes alone are insufficient for identifying physical abuse combining specific procedures may improve case identification for future epidemiological surveillance.
PMID:42186413 | DOI:10.1111/ped.70430
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