Implementing And Scaling Artificial Intelligence Solutions: Considerations For Policy Makers And Decision Makers

As reported in recent issues of Health Affairs, the New England Journal of Medicine, Harvard Business Review and other publications, Artificial Intelligence (AI) and Machine Learning can achieve breakthroughs in improving patient safety and health and reducing waste. AI infers patterns, relationships, and rules directly from large volumes of data in ways that can exceed human cognitive capabilities. As we previously described, opportunities for greater digitalization and deployment of AI in health/health care are made possible by increased electronic data availability from mobile devices, sensors, cameras, and electronic health records (EHRs); faster data processing capabilities; and newly developed computing techniques. While AI solutions are still only used sparingly in health/health care organizations, those organizations able to increase their AI capabilities will likely be better positioned for the transition to value-based care and achieving desired results with greater efficiency. We offer considerations for policy makers as well as decision makers in health organizations to rapidly scale up responsible implementation of AI solutions that have the potential to improve health and reduce inefficiencies.