Harnessing Health Statistics for Predictive Analytics: Transforming Healthcare Outcomes and Personalized Medicine - Rahim, Ali Malik Faleh Abdul; Kalil, Fatima Saad Hamid; Mahmoud, Abeer Mohamed; jasim, Huda Ghazwan Ali; Mohamed, Wiaam Adham Hashem (American Journal of Biodiversity, 2025)
Technology has enabled us to track, capture, and analyze more data than ever before—and this data is growing at an exponential rate. Data in the healthcare domain can be used to transform healthcare outcomes to deliver personalized medicine. This is due to the appearance of connected health infrastructure, in which a variety of medical devices comfortably coexist with traditional computing and storage devices such that healthcare services can be provided at any time and in any place. A central component of connected health is the individual and doctor-centric approach of telemedicine services that can monitor and analyze a person's medical condition without the need of physically entering a doctor's office. Long-term monitoring services create the need for distributed approaches that would allow remote analysis of health data collected from the various monitoring devices. Thus, the collection and analysis of health statistics is becoming faster and easier, and it is expanding rapidly. Harnessing health statistics provides the opportunity to reduce healthcare costs and delivers treatment more effectively. Moreover, it has the potential to enhance personal treatment, as well as enable early diagnosis which can be crucial for the treatment of severe diseases. The increasing interest in analyzing health statistics creates a new range of challenges. One of the key challenges is the privacy of health statistics. Patient’s health statistics can represent sensitive information, and therefore they must be stored and processed securely, not only to protect patient privacy as demanded by the law, but in addition to protect the commercial interests of healthcare providers. Healthcare providers store and analyze patient health statistics, and represent a source of internal threats and hazards. On the other hand, wearable sensors became popular among patients. Off-the-shelf mobile devices have integrated sensors that can monitor a set of health statistics. The resultant data has obvious privacy concerns when being collected and analyzed by third party services that can run on the same device.