Abstract

227 Background: Shared decision-making (SDM) occurs when both patient and provider are involved in the treatment decision-making process. SDM allows patients to understand the pros and cons of different treatments while also helping them select the one that aligns with their care goals when multiple options are available. This qualitative study sought to understand different factors that influence early-stage breast cancer (EBC) patients’ approach in selecting treatment. Methods: This cross-sectional study included women with stage I-III EBC receiving treatment at the University of Alabama at Birmingham from 2017-2018. To understand SDM preferences, patients completed the Control Preferences Scale and a short demographic questionnaire. To understand patient’s values when choosing treatment, semi-structured interviews were conducted to capture patient preferences for making treatment decisions, including surgery, radiation, or systemic treatments. Interviews were audio-recorded, transcribed, and analyzed using NVivo. Two coders analyzed transcripts using a constant comparative method to identify major themes related to decision-making preferences. Results: Amongst the 33 women, the majority of patients (52%) desired shared responsibility in treatment decisions. 52% of patients were age 75+ and 48% of patients were age 65-74, with an average age of 74 (4.2 SD). 21% of patients were African American and 79% were Caucasian. Interviews revealed 19 recurrent treatment decision-making themes, including effectiveness, disease prognosis, physician and others’ opinions, side effects, logistics, personal responsibilites, ability to accomplish daily activities or larger goals, and spirituality. EBC patient preferences varied widely in regards to treatment decision-making. Conclusions: The variety of themes identified in the analysis indicate that there is a large amount of variability to what preferences are most crucial to patients. Providers should consider individual patient needs and desires rather than using a “one size fits all” approach when making treatment decisions. Findings from this study could aid in future SDM implementations.

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