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Value Health ; 25(1): 84-90, 2022 01.
Artículo en Inglés | MEDLINE | ID: mdl-35031103

RESUMEN

OBJECTIVES: Living donor kidney transplantation (LTx) is the preferred treatment for patients with end-stage renal disease. Kidney exchange programs (KEPs) promote LTx by facilitating exchange of donors among patients who are not compatible with their donors. We analyze and maximize the efficacy and effectiveness of KEPS from a health value perspective and the health value of altruistic donation in KEPs. METHODS: We developed a Markov model for the health outcomes of patients, which was embedded in a discrete event simulation model to assess the effectiveness of allocation policies in KEPs. A new allocation policy to maximize health value was developed on the basis of integer programing techniques. The evidence-based transition probabilities in the Markov model were based on data from the Dutch KEP using a variety of econometric models. Scenarios analysis was presented to improve robustness. RESULTS: The efficacy of the Dutch KEP without altruistic donation is reflected by the increase in expected discounted quality-adjusted life-years (QALYs) by 3.23 from 6.42 to 9.65. The present Dutch policy and the policy to maximize the number of transplants achieve 63% of the potential efficacy gain (2.11 discounted QALYs). The new policy achieves 69% of this gain (2.33 discounted QALYs). When systematically enrolling altruistic donors in the KEP, the new policy increased expected discounted QALYs by 4.05 to 10.27 and reduced inequities for patients with blood type O. CONCLUSIONS: The Dutch KEP can increase health value for patients by more than half. An allocation policy that maximizes health outcomes and maximally allows altruistic donation can yield significant further improvements.


Asunto(s)
Trasplante de Riñón/métodos , Años de Vida Ajustados por Calidad de Vida , Obtención de Tejidos y Órganos/organización & administración , Adolescente , Adulto , Anciano , Altruismo , Humanos , Fallo Renal Crónico/cirugía , Donadores Vivos , Cadenas de Markov , Persona de Mediana Edad , Países Bajos , Estudios Retrospectivos , Adulto Joven
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