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Published on: April 26, 2015
Development of an Explanatory Model of Resuscitation Preference Decision Making
Mark Goldszmidt1, Rachelle Lassaline2, Kristen A Bishop3
1Division of General Internal Medicine (M.G.), Department of Medicine, Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada; London Health Sciences Centre, London, Ontario, Canada; Centre for Education Research and Innovation (CERI), Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Context:
Establishing resuscitation preferences prior to a medical emergency is a well-recognized component of hospital practice. When done effectively, these help to ensure that care received aligns with patient wishes. In practice however, these conversations can be challenging and influences on choice are not well understood.
Objectives:
Objectives: The purpose of this study was to identify influences on patient resuscitation preferences and their relationship to each other, with the aim of developing an explanatory model.
Methods:
Constructivist grounded theory was used to analyze 107 clinical notes from a dataset of detail-rich resuscitation preference conversation narratives. Sampling was purposeful and focused on maximum variation. Iterative data collection and analysis and constant comparison was used to enhance rigor as was the incorporation, in later stages of the analysis, of existing theories and models.
Results:
Twenty-seven coding categories were developed and integrated into the resuscitation preferences conversation model that described the interaction and relationship between influences. Within the model, three categories (Ability to Engage in Meaningful Activity, Trajectory, and Perceptions and Beliefs) informed patient and Substitute Decision Maker (SDM) preferences, while an additional two categories (Social and Knowing, and Experiences) informed substitute decision maker choice.
Conclusions:
The developed model builds on prior work and helps explain the relationship between influences and preferences. The integration of both patient and substitute decision maker perspective into the model shows the complexity of the substitute decision maker role in decision-making. The model should be used in conjunction with existing conversation guides to support effective resuscitation preference conversations.
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