Construcción heurística en la salud digital de la plataforma del sistema de aplicación de técnicas para el diagnóstico metabólico (Sistema ATDM)

Objective: We reviewed how the phases and stages of programming the Big Data Digital Platform of the System for Applying Techniques for Metabolic Diagnosis (ATDM System) were carried out, and its use in clinical practice and research to evaluate and monitor metabolism. Methodology: A qualitative, propositional, descriptive, and documentary study was conducted, grounded in the iterative nature of the ATDM System, which organized the implementation into three phases: user-centered design (UCD), extract–load–transform (ELT), and knowledge discovery in databases (KDD). Results: A web platform with an enterprise architecture (.NET Core 7, Angular 16, and SQL) was documented, along with six evolutionary stages that consolidated patient/user registration with role-based access control, evaluation data capture (medical history, bioimpedance, and capillaroscopy), report generation, recommendations and campaigns, digital communication of results, dashboards with statistics and telemedicine components, and extraction of outputs for research. Conclusions: It was established that phased development strengthened traceability, continuous improvement, and data-driven decision support; moreover, by being conceived as an aid (not a substitute) for clinical judgment, the system provided a replicable framework for digital metabolic health initiatives and for future predictive analytical models.