A Systematic Review of Algorithms for Identifying Pediatric Neurodevelopmental Outcomes.

This study looked at how researchers identify autism and other developmental conditions in medical databases. They reviewed 156 studies and found that most focused on autism (66%) and ADHD (46%). The way conditions are identified varies greatly between countries - Nordic countries can use simple methods while the US needs more complex approaches. Only 18 studies checked if their methods were accurate.

This systematic review examined 156 publications to identify algorithms used to define neurodevelopmental outcomes in electronic healthcare data studies. The review focused on studies from 2010-2025 that used secondary data to investigate pediatric neurodevelopmental conditions. Most studies examined autism spectrum disorder (65.6%) and ADHD (45.9%). Only 18 studies validated their outcome definitions.

The review found that Nordic countries achieved high positive predictive values using single diagnostic codes, while US data required more complex algorithms. The authors recommend presenting individual neurodevelopmental outcomes rather than composite measures and emphasize the importance of clearly defining assessment timeframes for valid epidemiological estimates.

Researchers should prioritize validation of diagnostic algorithms when using electronic health records. Healthcare systems may need different approaches based on their coding practices. Individual neurodevelopmental outcomes should be reported separately rather than as composite measures to improve research quality and clinical interpretation.

The abstract does not specify inclusion/exclusion criteria, search databases used, or methodological quality assessment procedures. Sample size characteristics and validation study details are not provided. Geographic representation and potential publication bias are not addressed.

Investigating pediatric neurodevelopmental outcomes (NDO) in studies using secondary data is often challenging due to heterogeneous clinical definitions and medical coding systems. This study aims to identify the algorithms used to define NDO in studies using electronic healthcare data through a systematic literature review. A search strategy was developed to identify studies on NDO that describe phenotype algorithms from January 1, 2010, to March 10, 2025. The search strategy included terms to identify studies containing algorithms for NDO as an outcome, routinely collected healthcare data, epidemiologic designs likely to incorporate algorithms, and pregnant individuals and/or infants/children.

Two independent reviewers assessed eligibility criteria and performed data extraction, with inconsistencies reviewed by a third reviewer. Descriptive statistics were used to summarize categorical and continuous variables appropriately. The review included 156 publications that implemented algorithms for NDO, with 18 of these studies validating the outcomes. Most publications studied autism spectrum disorder (ASD) (n = 103, 65.6%) and attention deficit hyperactivity disorder (ADHD) (n = 72, 45.9%) either as a single outcome or as a composite.

Instead of presenting NDO as a composite outcome, it is recommended to present multiple single outcomes. Validated outcomes in data from Nordic countries demonstrate a high positive predictive value when using one code for diagnoses, while more complex algorithms are required for US data. Clearly detailing and establishing the time of assessment for each NDO is critical to inform valid epidemiological estimates.