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1.
J Med Econ ; 24(1): 620-627, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-33851571

RESUMO

AIMS AND OBJECTIVES: Patients diagnosed with post-transplant lymphoproliferative disease (PTLD) experience high mortality within the first 2 years of diagnosis; however, few data exist on the economic burden of PTLD in these patients. We determined the healthcare resource utilization (HRU) and cost burden of post-kidney transplant PTLD and evaluated how these differ by survival status. MATERIALS AND METHODS: Utilizing data from the United States Renal Data System and the Scientific Registry of Transplant Recipients, we identified 83,818 Medicare-covered kidney transplant recipients between 2007 and 2016, of which 347 had at least one Medicare claim during the first year after diagnosis of PTLD. We tabulated Medicare Part A and Part B and calculated per patient-year (PPY) costs. RESULTS: Patients diagnosed with PTLD in the first year post-transplant had Part A + B costs of $222,336 PPY, in contrast with $83,546 PPY in all kidney transplants. Post-transplant costs in the first year of PTLD diagnosis were similar regardless of the year of diagnosis. Cost burden for PTLD patients who died within 2 years of diagnosis was >3.3 times higher than PTLD patients still alive after 2 years. Of those who died within 2 years, the majority died within 6 months and costs were highest for these patients, with almost 7 times higher costs than PTLD patients who were still alive after 2 years. LIMITATIONS: Medicare costs were the only costs examined in this study and may not be representative of other costs incurred, nor be generalizable to other insured populations. Patients were only Medicare eligible for 3 years after transplant unless aged ≥62 years, therefore any costs after this cut-off were not included. CONCLUSIONS: PTLD represents a considerable HRU and cost burden following kidney transplant, and the burden is most pronounced in patients who die within 6 months.


Assuntos
Transplante de Rim , Transtornos Linfoproliferativos , Idoso , Humanos , Medicare , Sistema de Registros , Estudos Retrospectivos , Fatores de Risco , Estados Unidos
2.
Pediatr Transplant ; 23(3): e13379, 2019 05.
Artigo em Inglês | MEDLINE | ID: mdl-30793448

RESUMO

Database linkage is a common strategy to expand analytic possibilities. Our group recently completed a linkage between the SRTR and PHIS databases for pediatric heart transplant recipients. The aim of this project was to expand the linkage between SRTR and PHIS to include liver, kidney, lung, heart-lung, and small bowel transplants. All patients (<21 years) who underwent liver, kidney, lung, heart-lung, or small bowel transplant were identified from the PHIS database using APR-DRG codes (2002-2018). Linkage was performed in a stepwise approach using indirect identifiers. Hospital costs were estimated based on hospital charges and cost-to-charge ratios, inflated to 2018 dollars and described by transplant type. A total of 14 061 patients overlapped between databases. Of these, 13 388 (95.2%) were uniquely linked. Linkage success ranged from 92.6% to 97.8% by organ system. A total of 12 940 (92%) patients had complete cost data. Hospitalization costs were greatest for patients undergoing small bowel transplantation with a median cost of $734 454 (IQR $336 174 - $1 504 167), followed by heart $565 386 (IQR $352 813 - $999 216), heart-lung $471 573 (IQR $328 523 - 992 438), lung $303 536 (IQR $215 383 - $612 749), liver $200 448 (IQR $130 880 - $357 897), and kidney transplant $94 796 (IQR $73 157 -$131 040). We report a robust linkage between the SRTR and PHIS databases, providing an invaluable tool to assess resource utilization in solid organ transplant recipients. Our analysis provides contemporary cost data for pediatric solid organ transplantation from the largest US sample reported to date. It also provides a platform for expanded analyses in the pediatric transplant population.


Assuntos
Bases de Dados Factuais , Transplante de Órgãos/economia , Transplante de Órgãos/métodos , Sistema de Registros , Adolescente , Algoritmos , Criança , Pré-Escolar , Coleta de Dados , Feminino , Custos de Cuidados de Saúde , Recursos em Saúde/economia , Preços Hospitalares , Humanos , Lactente , Recém-Nascido , Masculino , Pediatria , Estados Unidos , Adulto Jovem
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