Our world today moves much faster than ever before. Mobile devices keep us connected every moment of the day, and answers to many inquiries are just a click away. The role of data and analytics is becoming increasingly important in this fast-moving environment to provide quick, accurate answers with a positive experience.
Many health systems around the world are embracing ‘rapid-learning health systems’ approaches to drive improvements in people’s experiences and health outcomes while keeping costs manageable and health care providers engaged. Rapid learning health system approaches apply to all levels of health care (from clinical encounter up to program, organization and system) and across all parts of a system (from home care to primary and specialty care and public health).
There is a need to better harness characteristics of rapid learning health systems globally that include: patient and public engagement; timely sharing of data; timely synthesis of existing evidence and timely credible research; decision supports (such as guidelines and their decision support tools); aligned governance, financial and delivery arrangements; and a culture of rapid learning and improvement and competencies for rapid learning and improvement. Implementing these structures offer the potential to improve people’s experiences and outcomes while enabling data and evidence-informed transformations at all levels of a health system.
There is also growing evidence that through artificial intelligence, massive amounts of data can be analyzed at a much faster rate than previously. This may assist in with timely sharing of data. Machine learning can make the use of that data to improve accuracy in decision making. The credibility of the data and the outputs must be ensured. In addition, there are numerous issues that require resolution such as digital coverage, privacy, security, patient engagement and the validation of algorithms being only as good as AI’s access and availability to data are just the beginning.
This year’s Colloquium will explore Cochrane’s current strengths within the characteristics of rapid learning health systems, how we collaborate and partner together to support characteristics and the role of artificial intelligence and technology within the utilization of data to round out understandings of problems, to inform choices about policy options and to design implementation strategies as well as the role that artificial intelligence and technology can play in these systems.