Data from healthcare systems can be used to improve patient care, resource allocation, preventive strategies and medical research. It emphasises the need for coordinated European healthcare data policies and learning from Canada’s population-based approach.
Data generated by healthcare systems can be mobilised to inform four different aspects of public health and health care policy making, including supporting patient-centered evaluation of healthcare services, adapting care supply to population needs, developing targeted prevention policies, and forming healthcare research
Data-driven policy making: a key step for the healthcare system
Through the emergence of AI-driven healthcare, 80% of physicians’ diagnostic, prescription and monitoring tasks could be automated in the future. (Ren, 2018)
(PDF) The role of data-driven initiatives in enhancing healthcare delivery and patient retention
Reviews how big data is transforming diagnostics, predictive analysis, patient engagement, and operational efficiency. It also discusses privacy and bias challenges.
This study focuses on how AI can help improve preventive healthcare in the U.S., where only 8% of Americans undergo routine screenings. The authors advocate for machine learning models to detect patterns in clinical data and improve preventive care policies.