Healthcare Data Security and Privacy
Pawan Shankar Majre, Nikhita Chambhare · 2024
Precision health utilizes data from multiple sources, such as social media, health information, insurance claims, economics, and lifestyle, to provide tailored care, early detection and prediction of disease, and targeted treatments. It makes extensive use of computations (like machine learning), communication (like the interaction between the health data centres), and sensing technologies (like electronic health monitoring devices). Care must always be taken because sensitive personal information can be found in health data, such as the patient's name, the identity of the caregiver, and the patient's health issues. The revelation of these personal details can have a variety of negative effects on a person's life, such as harassment, increased insurance costs, and losing one's work because of a medical history. Consequently, the confidentiality, security, and reliability of the information are essential. Furthermore, ethics committees and government laws require that medical data be secure and private. Furthermore, the public, which is the source of the data, constantly demands the security, privacy, and confidence of their information. If not, they are able to refrain from providing their data to the precision health system. Consequently, precision health becomes less effective since the general public is the system's intended beneficiary.