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A case study of how the organizational change process known as Positive Deviance was used to fight healthcare-associated infections at Maine Medical Center highlights the human and social aspects of leadership in a complex adaptive system. It illustrates that leadership can shape selforganization in a manner that facilitates creative, productive, desirable outcomes. We found influential roles of anxiety, attachment, and relationships in facilitating organizational leadership. We describe how the process of leadership permeated the Medical Center's hierarchies and networks and reflected emergent power dynamics, which included contemporizing some aspects of traditional managerial authority. The study contributes to the management literature by clarifying the dynamics and qualities associated with change in complex human systems and illuminating what constitutes complexity-informed leadership and how it can be practiced.

Background The purpose of this article is to describe neonatal intensive care unit clinician perceptions of a continuous predictive analytics technology and how those perceptions influenced clinician adoption. Adopting and integrating new technology into care is notoriously slow and difficult; realizing expected gains remain a challenge. Methods Semistructured interviews from a cross-section of neonatal physicians (n = 14) and nurses (n = 8) from a single U.S. medical center were collected 18 months following the conclusion of the predictive monitoring technology randomized control trial. Following qualitative descriptive analysis, innovation attributes from Diffusion of Innovation Theory-guided thematic development. Results Results suggest that the combination of physical location as well as lack of integration into work flow or methods of using data in care decisionmaking may have delayed clinicians from routinely paying attention to the data. Once data were routinely collected, documented, and reported during patient rounds and patient handoffs, clinicians came to view data as another vital sign. Through clinicians' observation of senior physicians and nurses, and ongoing dialogue about data trends and patient status, clinicians learned how to integrate these data in care decision making (e.g., differential diagnosis) and came to value the technology as beneficial to care delivery. Discussion The use of newly created predictive technologies that provide early warning of illness may require implementation strategies that acknowledge the risk–benefit of treatment clinicians must balance and take advantage of existing clinician training methods.