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As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. Since writing my 1st article for Managing Organizational Complexity in 2004, much has happened to further our understanding of complexity in healthcare systems. The growth of new computational methods in the fields of data science and data analytics has allowed scientists to identify signals or patterns in large complex data sets (big data) that in the past were seemingly hidden. Rather than relying on historical statistical methods to infer outcomes, these advanced methods combined with increased computer processing power allow machines to learn the structure of data and create artificial intelligence (AI). In our ongoing efforts to find solutions for complex healthcare problems, AI is becoming more and more an accepted method. The purpose of this edition of Managing Organizational Complexity is to define AI and machine learning, discuss the recent resurgence of AI, and then provide examples of how AI can provide value to healthcare with an emphasis on nursing.
Thomas R. Clancy (Mon,) studied this question.