A Case Study on the Development of a Data Privacy Management Solution Based on Patient Information

Area of Science:

• Health Informatics
• Data Privacy
• Epidemiological Surveillance

Background:

• Infection diagnosis data is vital for public health and private sector applications, especially for contagious diseases.
• Sensitive health data, including symptoms and population displacement, necessitates robust data privacy measures for effective use.
• Internet of Things (IoT) devices in healthcare settings introduce significant data privacy concerns.

Purpose of the Study:

• To compare existing research on privacy in the health sector.
• To propose a taxonomy for controlling patient data privacy within hospital environments.
• To develop and implement a mobile application for analyzing privacy and security constraints related to COVID-19.

Main Methods:

• Comparative analysis of existing works on health data privacy.
• Development of a novel taxonomy for patient data privacy requirements in hospitals.
• Modeling and implementation of a mobile application for privacy and security analysis.

Main Results:

• The research provides a comparative overview of privacy issues in healthcare.
• A validated taxonomy aids in defining requirements for patient data privacy control.
• The developed mobile application demonstrates practical utility in assessing privacy and security constraints.

Conclusions:

• Effective data privacy strategies are crucial for large-scale infection surveillance and public health response.
• The proposed taxonomy offers a structured approach to managing patient data privacy in hospital settings.
• The mobile application serves as a valuable tool for evaluating and enhancing privacy and security measures, particularly in the context of pandemics like COVID-19.