Notifiable Diseases Surveillance System with a Data Architecture Approach: a Systematic Review.

Introduction: The wide range of notifiable diseases and the need for immediate reporting complicate the management of these diseases. Developing a surveillance system using precise architectural principles could ease the management of these diseases.

Aim: The present study reviews the data architecture of notifiable diseases surveillance systems to provide a basis for developing such systems.

Methods: A systematic review was conducted on the literature focused on data architecture of notifiable diseases surveillance systems. The searches for relevant English language articles were conducted based on the paper keywords, as well as the words Mesh and EMTREE.

Results: The findings were categorized into five groups, including organizations involved in the generation and monitoring of notifiable diseases' data. The databases in the present study were relational and used a centralized architecture for information sharing. The minimum dataset was determined in two information categories. The data standards were categorized into three main groups. The key approaches for data quality control included checking the completeness, timeliness, accuracy, consistency, adequacy, and validity of the data.

Conclusion: Developing a notifiable diseases surveillance based on data architecture principles could lay the foundation for better management of such diseases through eliminating the obstacles experienced during data generation, data processing, and data sharing.