Health insurance and kidney transplantation outcomes in the United States: a systematic review and AI-driven analysis of disparities in access and survival

作者：Oscar A. Garcia Valencia, Supawadee Suppadungsuk, Charat Thongprayoon, Yuh‐Shan Ho, Noppachai Siranart, Wannasit Wathanavasin, Caroline C. Jadlowiec, Shennen A. Mao, Napat Leeaphorn, Karim Soliman, Hatem Kaies Ibrahim Elsayed Ali, Pooja Budhiraja, Jing Miao, Wisit Cheungpasitporn · 发表于：Renal Failure · 年份：2025 · DOI：10.1080/0886022x.2025.2513007 · 被引用次数：6 · 研究领域：Renal Transplantation Outcomes and Treatments、Transplantation: Methods and Outcomes、Organ Donation and Transplantation

BACKGROUND: Kidney transplantation is the preferred treatment for end-stage kidney disease (ESKD) in the United States, yet access and outcomes vary by insurance type, race, and socioeconomic status. This systematic review synthesizes U.S.-based evidence on how insurance coverage influences transplant waitlisting, access, and outcomes. AI-assisted analysis was used to quantify disparities and propose policy recommendations. METHODS: A systematic review of MEDLINE, EMBASE, and the Cochrane Database (through November 2024) was conducted to identify studies on insurance-related disparities in U.S. kidney transplantation (PROSPERO: CRD42023484733). AI-assisted synthesis using o3-mini-high (2025) was employed to identify patterns and guide policy development. RESULTS: Among 2,163 records, 14 studies met inclusion criteria. Patients with Medicare or Medicaid-particularly racial and ethnic minorities-had lower referral rates and higher transplant waitlist rejection compared to those with private insurance. Socioeconomic barriers such as low income and limited education further impaired access and worsened post-transplant outcomes. Publicly insured recipients had higher post-transplant mortality and graft failure rates. Loss of Medicare after 36 months was associated with reduced immunosuppressant adherence and increased rejection. Disparities were amplified by Medicaid expansion variability and inconsistent transplant center policies. AI-assisted analysis confirmed these disparities...