부산대학교 도서관

Summary: Physicians have the unique opportunity to look beyond the walls of our hospitals and use non-clinical health determinants to improve our understanding of individual patient outcomes. To do so requires translational collaboration between the spatial and medical sciences and could lead to granular knowledge that helps our most vulnerable patients. Our central hypothesis was that health was impacted by place, defined as where patients spend their daily lives at home and in the community. To test this hypothesis we focused on our lung transplant recipient population. While lung transplant is a lifesaving surgery for patients with fatal lung diseases, there remains a critical limitation as median post-transplant survival is merely 6 years --less than half the survival of other organ transplant types. Unfortunately, this low survival stems from an accelerated deterioration in lung function in the years following transplant.We leveraged the Geographic Information Sciences, defined as the framework to measure, map, and model the effects of place. We took advantage of our electronic health record to geocode our patients at the census tract and block group levels followed by multivariate modeling and a novel description of residential relocations. Though we did not identify a significant association between a patient's most recent neighborhood level socioeconomic conditions as measured by the Area Deprivation Index (ADI) and acute lung rejection or posttransplant survival, we noted our cohort included patients from a wide range of ADIs. In describing residential relocations, we observed a range of upwards and downwards mobility using another common measure of socioeconomic conditions, the Social Vulnerability Index (SVI), and observed the most recent SVI poorly captured a patient's lived history. Among patients with >1 address, the most recent SVI was the same as the oldest SVI in only 15.4% (58/374) of patients. These findings raise awareness of the need for geographically-enhanced databases with residential histories which would better inform medical care.Our long-term goal is to build impactful spatial-clinical transdisciplinary methods applicable beyond lung transplant which could lead to the identification of new disease subtypes based on place-based risk factors and shift the medical field towards personalized patient-centric care.