Development of an Expert System Calculator for Pediatric Blood Draw: A Conceptual Study

Abstract

This study demonstrates the feasibility and potential clinical value of a rule-based expert system for optimizing blood collection in pediatric patients, a population uniquely susceptible to iatrogenic anemia due to limited circulating blood volume and frequent laboratory testing. By systematically mapping ordered laboratory tests to tube-specific analytical and dead-volume requirements and applying patient-specific safety constraints based on weight and hematocrit, the system provides quantitative decision support at the time of test ordering. Evaluation using a simulated pediatric cohort (n = 20) representative of endocrine testing workflows showed that blood draw volumes were maintained within established safety thresholds in 16 of 20 cases (80%). Across the cohort, the optimized strategy achieved a mean reduction of 9.36 mL in total blood volume compared with standard collection practices. In the remaining cases, where optimization was not feasible due to extensive test panels or severely limited allowable blood volume, the system appropriately identified threshold violations and generated warning outputs rather than unsafe recommendations. These results highlight the system’s ability to both reduce unnecessary phlebotomy and reliably flag high-risk scenarios. Overall, this work establishes a transparent and reproducible technical framework for expert system–based optimization of pediatric blood draws and supports its future integration into clinical laboratory workflows to enhance patient safety and reduce avoidable blood loss.

Received: 22 November 2025 | Revised: 4 January 2026| Accepted: 21 January 2026

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

Data Availability Statement

Data are available from the corresponding author upon reasonable request.

Author Contribution Statement

Sihe Wang: Conceptualization, Methodology, Software, Investigation, Resources, Data curation, Writing – review & editing, Visualization, Supervision, Project administration. Richard Desatnik: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review &; editing, Visualization. Motaz Hassan: Validation, Formal analysis, Writing – original draft, Writing – review &; editing, Visualization. Amanpreet Singh Wasir: Validation, Formal analysis, Writing – original draft, Writing – review &; editing, Visualization. Ajay Mahajan: Conceptualization, Methodology, Software, Investigation, Resources, Data curation, Writing – review & editing, Visualization, Supervision, Project administration.