A place-based approach to geographic disparities in lung transplant

Cleveland Clinic Lerner Com-Cwru, Cleveland OH

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Abstract

PROJECT SUMMARY 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 5.5 years which is only half the survival experienced by other organ transplant types. Unfortunately, this low survival is from the accelerated deterioration in lung function in the years after transplant and cannot be fully explained by transplant center practices, donor factors, or recipient factors. Troublingly, there is also disparate survival by geography which varies up to 39% depending on the region of the U.S. We hypothesize that place, defined as a social and environmental location with meaning to a person, impacts recipient health and in a mechanistic hypothesis these place-based factors cause subclinical micro-injuries to the lungs which accelerate lung function loss in the years after transplant. There is a gap in knowledge on how place-based factors exacerbate both the geographically disparate and poor survival of lung transplant recipients. In the absence of this knowledge, it is difficult to precisely risk stratify recipients and develop patient and policy level interventions. To address this gap, we leverage the Geographic Information Sciences, defined as the framework to measure, map, and model the effects of place. The scope of Aim 1 is to inform clinical decisions by geocoding a multicenter cohort to identify individual recipient level census tracts. This enables linkage to highly granular federal datasets with a wide array of social and environmental health measures followed by the application of multilevel models and established spatial cluster detection methods. This is significant as these results would enable us to pivot away from an existing one-size-fits-all clinical approach by screening earlier for worsening lung function or tailoring immunosuppression medications to prevent lung function loss for at risk patients. The scope of Aim 2 is to inform policy through mapping disparities across the U.S. and improving the accuracy of established clinical prediction models. We will merge the singular national transplant registry with highly valued federal data measuring social and environmental health factors, and test the inclusion of place-based factors on the performance of novel multilevel models and established clinical cox models. New maps and more accurate models would be a significant advance towards identifying and reducing geographic disparities and improving outcomes through targeted resource allocation. Our long-term goal is to improve the suboptimal lung transplant survival and ensure this improvement is achieved regardless of place. This project is impactful as we are the first in lung transplant to look beyond the walls of our hospitals to create unprecedented comprehensive data translatable towards patient and policy level interventions. This proposal is responsive to the Final Rule mandate by the U.S. Department of Health and Human Services that patient geography should have a minimal role in transplant outcomes, a mandate the field of transplantation has made little progress towards over the past two decades due, in large part, to gaps in knowledge that our proposal aims to fill.