Data Classification Methodology: The Way Forward to Data-Enabled Healthcare in Egypt

Area of Science:

• Health Informatics
• Data Science
• Healthcare Management

Background:

• Healthcare generates vast amounts of data, necessitating robust management systems for effective utilization.
• Data significantly impacts decision-making at all levels within healthcare organizations.
• Differentiating data management (activities) from data governance (strategic framework) is key.

Purpose of the Study:

• To propose a data classification methodology roadmap for the Egyptian healthcare system.
• To focus on the initial step of data classification: categorizing diverse healthcare data types.
• To enhance data-driven decision-making through structured data management.

Main Methods:

• Reviewing existing data management and governance principles.
• Developing a framework for data classification within the healthcare context.
• Identifying and categorizing data types from various Egyptian healthcare ecosystems.

Main Results:

• A proposed roadmap for data classification in Egyptian healthcare.
• Identification of key data categories within the healthcare system.
• Foundation laid for implementing executable data management policies.

Conclusions:

• A systematic approach to data classification is vital for healthcare data management.
• The proposed roadmap provides a structured first step for Egyptian healthcare data initiatives.
• Improved data classification will support better data governance and decision-making.