| dc.description.abstract | Bariatric surgery require effective pre-, intra-, and post-surgery care coordination to optimize patient outcomes and minimize complications. Assessing care coordination structures of the healthcare teams for these patients is crucial to identify areas for improvement and address disparities. However, a significant challenge lies in the lack of metrics to quantify care coordination structures in terms of communication, adaptability, and role clarity. To address this challenge, our study creates care coordination networks based on electronic health records to reflect patient transitions throughout the course of treatment. We develop a set of network-based metrics, including degree, density, diameter, average shortest path length, closeness, betweenness, cluster coefficient, reciprocity, transitivity, and homophily, to quantify care coordination structures. We leverage these metrics to analyze care coordination structures across different races, ethnicities, genders, and surgery types, allowing for a comprehensive understanding of disparities in care coordination. Our results, presented through radar graphs, highlight the differences in care coordination structures between pre-, intra-, and post-surgery stages, as well as among patients with varying race/ethnicity, gender, and surgery type. We notice significant difference in surgical outcome between white and black patients and identify a set of network metrics that are also different between the two groups. This suggests that there is disparity across bariatric surgery patients from different races, and there may be associations between network metrics and bariatric surgery outcomes. This novel approach to quantifying care coordination structures offers valuable insights for healthcare professionals and policymakers seeking to enhance care quality and address disparities in bariatric surgery care. | |
