Peer-reviewed article
The pediatric AI readiness framework: bridging evidence to practice in pediatric artificial intelligence.
Sezgin E, Boch S ·
Summary
Written by AI, not yet AICS's view · claude-haiku-4-5-20251001This document presents the Pediatric AI Readiness (PAIR) Framework, a checklist designed to guide the implementation of artificial intelligence tools in pediatric healthcare settings. The framework addresses seven domains including ethics, data representation, validation, workflow integration, economics, adaptability to low-resource settings, and reporting transparency. While the document discusses the importance of AI for pediatric healthcare, it is a methodological tool rather than a study evaluating child well-being outcomes.
Key points
- The PAIR Framework organizes AI readiness across seven domains: ethics and governance, population and data representativeness, validation and testing, workflow integration, economic and sustainability analysis, low-resource adaptability, and transparent reporting
- The framework emphasizes child-centric design and the need for specialized approaches to AI integration due to children's unique developmental, physiological, and ethical considerations
- PAIR is intended for use by clinicians, health system leaders, regulators, and developers planning, evaluating, and operationalizing AI tools
Limitations
This document describes a framework and implementation tool rather than evaluating actual health or well-being outcomes for children. It does not provide empirical evidence of whether AI implementation following this framework improves child health, survival, development, protection, or participation.
Abstract
Artificial intelligence (AI) presents a transformative opportunity for pediatric healthcare, promising advancements in early diagnosis, personalized treatment, and operational efficiency. However, the unique developmental, physiological, and ethical considerations inherent to children necessitate a specialized approach to AI integration. This study introduces the Pediatric AI Readiness (PAIR) Framework-a pediatric-focused implementation-readiness checklist intended to support clinicians, health system leaders, regulators, and developers as they plan, evaluate, and operationalize AI tools in pediatric settings. PAIR complements existing AI development, evaluation, and reporting guidance by focusing on institutional and workflow readiness for real-world use. It organizes readiness considerations across seven domains: ethics and governance, population and data representativeness, validation and testing, workflow integration, economic and sustainability analysis, low-resource adaptability, and transparent reporting. By prioritizing child-centric design, rigorous validation, and collaborative governance, the PAIR framework aims to bridge the critical gap between AI innovation and its responsible application, fostering improved design and healthier futures for children.