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Joel MayJoel May

Pediatric Growth Tracking for Healthcare Professionals

SaludNestJSChart.jsSQL Server
Z-scores calculated using LMS method on Fenton 2025 and OMS standards

The Challenge

  • LMS method implementation: Complex statistical calculation to normalize anthropometric measures
  • Automatic Fenton/OMS switching: Dynamic table selection based on patient age and condition
  • Corrected age for preterms: Growth curve adjustment based on weeks of prematurity
  • Growth curve visualization: Interactive charts with Chart.js for longitudinal tracking

Solution Architecture

REST/GraphQLCálculo Z-scoresReact + Chart.jsNestJS + PrismaSQL ServerLMS EngineTablas de Referencia
System architecture diagram showing nodes and connections

Frontend

React with Chart.js for growth curve visualization, interactive components for anthropometric data entry

Backend

NestJS with Prisma ORM, dedicated LMS calculation module, medical data validation

Database

SQL Server with LMS reference tables (Lambda, Mu, Sigma), Fenton 2025 and OMS percentile tables

Critical Fix

DECIMAL(3,2) → DECIMAL(5,2) for height values, allowing records up to 99.99cm

Results

0%

Z-score calculation errors

15min → 2min

Evaluation time

100%

Preterm support

ECLI - Pediatric Growth Tracking System | Joel May