Geospatial Analysis of Organ Transplant Referral Regions.

IMPORTANCE: System and center-level interventions to improve health equity in organ transplantation benefit from robust characterization of the referral population served by each transplant center. Transplant referral regions (TRRs) define geographic catchment areas for transplant centers in the US, but accurately characterizing the demographics of populations within TRRs using US Census data poses a challenge. OBJECTIVE: To compare 2 methods of linking US Census data with TRRs-a geospatial intersection method and a zip code cross-reference method. DESIGN, SETTING, AND PARTICIPANTS: This cohort study compared spatial congruence of spatial intersection and zip code cross-reference methods of characterizing TRRs at the census block level. Data included adults aged 18 years and older on the waiting list for kidney transplant from 2008 through 2018. EXPOSURES: End-stage kidney disease. MAIN OUTCOMES AND MEASURES: Multiple assignments, where a census tract or block group crossed the boundary between 2 hospital referral regions and was assigned to multiple different TRRs; misassigned area, the portion of census tracts or block groups assigned to a TRR using either method but fall outside of the TRR boundary. RESULTS: In total, 102 TRRs were defined for 238 transplant centers. The zip code cross-reference method resulted in 4627 multiple-assigned census block groups (representing 18% of US land area assigned to TRRs), while the spatial intersection method eliminated this problem. Furthermore, the spatial method resulted in a mean and median reduction in misassigned area of 65% and 83% across all TRRs, respectively, compared with the zip code cross-reference method. CONCLUSIONS AND RELEVANCE: In this study, characterizing populations within TRRs with census block groups provided high spatial resolution, complete coverage of the country, and balanced population counts. A spatial intersection approach avoided errors due to duplicative and incorrect assignments, and allowed more detailed and accurate characterization of the sociodemographics of populations within TRRs; this approach can enrich transplant center knowledge of local referral populations, assist researchers in understanding how social determinants of health may factor into access to transplant, and inform interventions to improve heath equity.

Duke Scholars

Author Jane Frances Pendergast Biostatistics & Bioinformatics, Division of Biostatistics

Author L. Ebony Boulware Medicine, General Internal Medicine

Author Lisa M McElroy Surgery, Abdominal Transplant Surgery

Author Sarah Peskoe Biostatistics & Bioinformatics, Division of Biostatistics

Author Tyler Schappe  

Author Nrupen Bhavsar Surgery, Surgical Sciences