440 Uncovering Biases in Patient Selection of a Neurosurgeon

INTRODUCTION: The physician-patient relationship is increasingly emphasizing patient autonomy and active participation, which boosts health outcomes, survival, and satisfaction. This study investigates the attributes patients consider when selecting a neurosurgeon, exploring how factors like neurosurgeon's reputation, experience, online presence, and the patient's socioeconomic background influence their choices. METHODS: An anonymous survey was distributed to 300 patients presenting to the neurosurgery clinic at UC San Diego Health. The survey consisted of two sections. The first assessed demographics of the study population. The second evaluated patient preferences and perceptions when choosing a neurosurgeon. The results generated from the questionnaire were entered and analyzed using SPSS 23.0. Descriptive analysis was first performed, followed by an association analysis using the Chi-square test. RESULTS: The patient cohort had a balanced gender distribution (49.3% female, 50.7% male) and was predominantly Caucasian (47.3%). Findings revealed significant associations between patient gender and surgeon gender preference (p < 0.001), with males showing less preference for surgeon gender than females. Female respondents expressed strong preference for male neurosurgeons (81.8 %, p < 0.001) while males expressed no specific gender preference (36.8%, p < 0.001). Higher education levels correlated with increased gender bias, and higher income was significantly linked to a preference for male neurosurgeons (p < 0.007). The neurosurgeon attributes most significantly valued were board certification, sub-specialization, online patient satisfaction ratings and physical appearance, several of these demonstrated significant gender bias. CONCLUSIONS: While objective qualifications such as board certification and sub-specialization were most highly valued, neurosurgeon selection was also significantly influenced by gender, physical appearance, and online ratings. These data highlight the need for awareness of underlying unconscious biases in patient healthcare decision-making to facilitate optimal surgeon selection and patient outcomes.