Disease Registry Data Management: Program Overview, Universities, Careers & Salaries

Program Overview

Specializing in the systematic collection and analysis of health data, this program equips students with the expertise to manage comprehensive disease registry information within healthcare systems. Focused on accuracy, compliance, and data integrity, it prepares professionals to support public health initiatives, clinical research, and policy development through rigorous data stewardship.

• Anatomy: In-depth study of human body structures, providing foundational knowledge for interpreting medical records and diagnostic data.
• Data Management: Techniques for organizing, storing, retrieving, and securing health information using modern database systems and digital platforms.
• Disease Registry Organization and Operations: Understanding the structure, workflows, and administrative functions of disease registries across public and private healthcare sectors.
• Epidemiology: Principles of disease occurrence, distribution, and determinants within populations, enabling evidence-based analysis of health trends.
• Ethics in Health Data: Exploration of privacy standards, informed consent, and regulatory obligations in handling sensitive patient information.
• Disease Coding and Staging: Training in standardized classification systems such as ICD and TNM to accurately document disease progression and treatment outcomes.
• Medical Terminology: Mastery of precise language used in clinical documentation, essential for clear and consistent data entry and communication.
• Pathophysiology: Study of disease mechanisms and their impact on normal physiological processes, critical for accurate data interpretation.
• Pharmacology: Knowledge of drug classifications, mechanisms of action, and therapeutic applications relevant to patient treatment tracking.
• Physiology: Understanding normal bodily functions to contextualize abnormal findings and support comprehensive health data analysis.
• Quality Management: Implementation of standards and continuous improvement strategies to ensure data reliability, accuracy, and regulatory compliance.
• Statistics: Application of quantitative methods to analyze health data, identify patterns, and support decision-making in public health and clinical settings.