Mapping Complex Influences on Aggressiveness of End of Life Cancer Care

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Patients with advanced cancer continue to receive aggressive care (new chemotherapy, intravenous chemotherapy, intensive care unit stays) despite the absence of evidence that such care at end of life (EOL) is associated with better outcomes. Recent research has shown that the rise in use of chemotherapy within the last 30 days of life is associated with poor outcomes such as few hospice days and lower quality EOL care. These poor outcomes, coupled with the increased symptom burden associated with such treatments often leads to financial and personal costs for patients at the EOL. Too many patients with advanced cancer die in- hospital away from family and meaningful supports that are essential for quality EOL care. Decision making for these patients is difficult-especially the decision whether or not and when to transition to a goal of comfort-orient care. This decision requires understanding of complex medical information and nuances in communication with the healthcare team. In an effort to understand factors that influence aggressive treatment decisions at EOL, research has focused on only one side of the complex phenomena of decision making--either MD input or patient decision. Yet this is not reflective of "real life" decision making in the clinical setting. If we are to understand the nuances involved in aggressive treatment decisions at EOL, we need a major re-conceptualization in how to effectively incorporate the complex processes involved in making these difficult treatment and care decisions. This must be accomplished if we are to facilitate provision of essential palliative and EOL care to these vulnerable patients. The proposed study will be the first to apply the principles of complexity science in examining the processes that lead to EOL treatment decisions (ranging from maximizing survival to maximizing quality of life) for patients with advanced care. The research questions are: (1) How is aggressiveness of EOL care influenced by the focus of care (oncologist, patient, and dyad) over time?; (2) How is focus of care (oncologist, patient, and dyad) influenced by clinical triggers, EOL preferences, and evaluation of treatment effectiveness over time?; (3) How is evaluation of treatment effectiveness influenced by EOL preferences, clinical triggers, and focus of care (oncologist, patient) over time?; (4) Are EOL preferences influenced by evaluation of treatment effectiveness over time?; (5) Are EOL preferences influenced by characteristics (oncologist, patient)? The results of this novel approach to examining complex processes in EOL decision making can provide information that will allow the design and testing of tailored support strategies for patients with advanced cancer. In addition to clinical application, if new strategies can be developed that can provide meaningful support to these patients and their caregivers, then the potential to facilitate meaningful decisions about EOL care and to potentially reduce the personal and financial impact of the use of ineffective aggressive treatments will benefit not only patients but society as well.