Modern medical care has one of the most complex organizational structures in society, with many non-linear work processes and intricate networks of professional relationships of people who often have interdependent individual and collective responsibilities. Healthcare organizations share many attributes with those in other safety–critical domains that are science-based and information-intensive, and therefore the initiative to improve the quality and safety of care has often been informed by interventions that proved to be effective in those industries. At the same time, many important features of care delivery do not have corresponding examples elsewhere. Researchers analyzing clinical workflows must often do so without the benefit of models that can be readily adapted from other fields, as standard models can describe such extensive and complex work environments only to a limited degree. The ability to reliably assess and model work processes is crucial for developing safe and effective health information technology that needs to be tightly integrated into workflows without adding extraneous complexity and cognitive effort. However, studies have historically investigated primarily the business process of care, and today many workflow analyses show conflicting results and may lack sufficient rigor. Work organization and processes in a socio-natural system that has many non-linear and non-additive functions that characterize healthcare are difficult to model and predict because complex systems are non-reducible to their constituent parts. This chapter discusses several analytic and explanatory frameworks that can guide studies that model workflows and cognitive processes associated with decision making that is often done with incomplete or unreliable information and where goals and priorities often need to be rearranged in response to dynamically changing circumstances. The application of artificial intelligence to the areas of care where they can have a sizeable effect is also reviewed. Patient care can be greatly advanced by the careful harnessing of powerful new forms of information technology into a collaborative environment where complex reasoning and ethics are the exclusive responsibilities of clinicians.