Clinlytix360 is a full-stack clinical analytics platform designed to simulate real-world healthcare data workflows. From raw Electronic Health Records (EHR) and Patient-Reported Outcomes (PRO/COA) to survival analysis, psychometric evaluation, and dashboard reporting, this project demonstrates the capabilities of modern data engineering and data science applied to clinical research and outcomes measurement.
The project aims to help researchers and clinicians transform disparate health data into actionable insights to support evidence-based decision-making, quality improvement, and patient engagement.
To emulate real clinical environments, synthetic datasets were created to resemble:
Challenges included ensuring data consistency between sources, managing missing data, and developing pipelines that could handle iterative updates without data leakage.
The pipeline was structured in modular stages:
Each step was containerized with Docker to ensure reproducibility across environments.
The pipeline produced validated survival models showing differences in survival across treatment cohorts and risk groups. Psychometric analyses identified reliable and interpretable latent factors within PRO/COA instruments. Dashboards enabled dynamic exploration of patient outcomes, model outputs, and survey results.
This approach demonstrates how modern analytics can support clinical research, improve patient care, and drive data-driven decision-making.