Application of Place-Based Methods to Lung Transplant Medicine
Wayne M. Tsuang,
Maeve MacMurdo and
Jacqueline Curtis
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Wayne M. Tsuang: Respiratory Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
Maeve MacMurdo: Respiratory Institute, Cleveland Clinic, 9500 Euclid Avenue, Cleveland, OH 44195, USA
Jacqueline Curtis: GIS Health & Hazards Lab, Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA
IJERPH, 2022, vol. 19, issue 12, 1-9
Abstract:
Lung transplantation is an increasingly common lifesaving therapy for patients with fatal lung diseases, but this intervention has a critical limitation as median survival after LT is merely 5.5 years. Despite the profound impact of place-based factors on lung health, this has not been rigorously investigated in LT recipients—a vulnerable population due to the lifelong need for daily life-sustaining immunosuppression medications. There have also been longstanding methodological gaps in transplant medicine where both time and place have not been measured; gaps which could be filled by the geospatial sciences. As part of an exploratory analysis, we studied recipients transplanted at our center over a two-year period. The main outcome was at least one episode of rejection within the first year after transplant. We found recipients averaged 1.7 unique residential addresses, a modest relocation rate. Lung rejection was associated with census tracts of predominantly underrepresented minorities or where English was not the primary language as measured by the social vulnerability index. Census tracts likely play an important role in measuring and addressing geographic disparities in transplantation. In a future paradigm, patient spatial data could become an integrated part of real time clinical care to aid in personalized risk stratification and personalized delivery of healthcare.
Keywords: respiratory; medicine; neighborhood; census tract; organ transplant (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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