Impact of wellbeing and healthcare resources on deceased liver donation in Mexico
Donation and Transplant activities in Mexico occur in heterogeneous, changing, and adverse landscapes. States that have made efforts to increase their activities have accomplished their goal of increasing their donation rates. However, objective proof of this phenomenon is complex. Economic investment records of Mexico’s donations and transplants are not publicly available. Some States have made direct investments through their own Regulating Centers. However, the origin and mechanisms are different for each State, depending on whether their State Transplant Center is a centralized or non-centralized organization. Moreover, each Social Security hospital program’s transplant budget is administered federally by Social Security subsystems and not by the State. Therefore, the budget designated for Donation and Transplantation cannot be directly measured. Hence, for this study, we relied on economic indicators (GDPpc and percentage of GDP from healthcare expenditure) to assess the overall local investment in health.
The difference between States is notorious. After controlling for population, the DBD, DDL, and LDCR rates in Nuevo Leon, Puebla, and Chiapas were very different (similar population of 5–6 million inhabitants). The economic capacity of a geographic entity can be evaluated by using multiple indicators. These should be specific, explicit, and available for several different periods of time and relevant, timely, and understandable. We decided to use GDPpc as the main indicator because it is objective, positive, absolute, quantitative, and direct. Moreover, GDPpc is the most widely used economic marker in scientific areas outside economic science. Interestingly, GDPpc was not associated with panel data models for DBD pmp, DDL pmp, or LDCR rates. Other indicators used to analyze this phenomenon and its relationship with economic capacity detected that BPK was the only variable that had a significant impact on the changes observed over time after adjusting for covariates in all models; therefore, we analyzed its impact thoroughly in DBD, DDL, and LDCR. The differences observed were similar to those observed in countries with similar BPK values. To our surprise, the two analyses identified that DBD pmp activity in Mexico City, Jalisco, Coahuila, Chihuahua, Tamaulipas, and Durango has the capacity to increase based on the available BPK.
Historically, Jalisco and Chihuahua have had periods of higher DBD Pmp activity, which means that with the current installed capacity, they could achieve this goal. Queretaro is a notorious example because, despite having a low BPK rate, it has a relatively high DBD pmp rate. Because they have the largest BPK available, Mexico City, Nuevo León, and Sonora, which are already in the > 75th activity percentile, could potentially increase their activity by implementing strategies similar to those established by States such as Guanajuato (increasing the number of hospital donor coordinators, centralization of coordination, and logistics).
The referral of patients from other Mexican States to Mexico City and the overcrowding of tertiary centers in the city definitively modifies the expected donation activity observed. The population used to control this activity is limited to the reported habitants of Mexico City (around 8 million people) and not all the habitants of the Metropolitan Area of the Valley of Mexico (around 20 million people), which includes areas of Mexico State and a municipality of Hidalgo. The authors did not consider appropriate to apply a different geographical area exclusively for the Metropolitan Area of the Valley of Mexico and not to the remaining 30 Mexican States, but a limitation of our study is an underestimation of the control of population over Mexico City’s donation activity.
The centralization of healthcare services in Mexico City is an important factor in a country’s donation activities. This study shows that DBD pmp activity is lower than expected for GDPpc and BPK compared to countries with similar circumstances. The development of donation programs in States with low BPK capacity and adverse economic situations such as Veracruz, Guerrero, Oaxaca, and Chiapas represent a particular challenge, since it must be part of a larger expansion of healthcare access and not an isolated strategy.
The HDI is an indicator developed by the United Nations to measure a country or region’s progress. Unlike the GDPpc, which only measures income, the HDI also analyzes health and education. Health was measured using a minimum life expectancy value of 20 years and a maximum value of 83.57 years. Education is measured through years of education for adults and predicts school years for school-aged children. The income component was measured through the acquisition power capacity using a minimum value of 100 and a maximum of 87,478. The greater HDI, the greater life expectancy, educational level, and income are. We decided to use this index because the Global Observatory on Donation and Transplantation has incorporated HDI into its donation activity reports since 2011. This can be found in all States of Mexico and can be compared to other countries. However, we found no association between the HDI and DBD pmp, DDL pmp, or LDCR in Mexico.
For more than 30 years, the National Council of Population has used the MI as an objective estimate of inequality in public policy planning in Mexico. Unfortunately, this indicator is not used outside our country, which limits its comparison with other countries. We found a positive correlation between the MI and DBD pmp rates. When analyzing its components separately and controlling for the effect of additional variables, we found that the percentage of the uninsured population was negatively correlated with DDL pmp and LDCR.
One of the most notable findings of this study is that Mexico has one of the lowest LDCR reported in the literature. Although several countries have reported a discard rate of 10–20%, our country exhibited a 64% rate during the study period. The LDCR was very low in some States with high DBD pmp activity, and an expected linear correlation with DDL pmp did not exist. The variables associated with the low LDCR rate in this study were the number of BPK and the percentage of the uninsured population, which indicates that the limited capacity of healthcare resources and marginalization of the population are elements that modify the use of DDL. However, the low coefficient of determination of our model indicates that other unavailable variables can play an important role in the observed changes. In the analysis reported by CENATRA in 2018, only 245 DDL were offered through coordination by CENATRA from 558 DBD, whereas 45 DDL were offered and transplanted without CENATRA’s coordination19. This shows that 268 DDL (48%) were not offered to transplant centers in that year, and hence, the absence of DDL offers is the main variable that explains low LDCR rates.
Implementation of online traceability applications is urgently needed to analyze case-by-case scenarios and improve the allocation system. Some factors that can affect this phenomenon include geographic accessibility, distance, and availability of local procurement teams, which occur in Sonora, San Luis Potosi, and Yucatan, where local teams oversee DDL recovery and send DDL to transplant centers20. Our group has shown that the availability of local recovery teams in Mexico drastically increases the LDCR rate, as is evident in Chihuahua, which is a traditionally low-LDCR State owing to its large territorial extension and difficulties in transportation logistics21. Some States such as Aguascalientes and Guanajuato, have DBD pmp rates of > 75th percentile and are in the center of the country, which should facilitate a larger LDCR than observed. The factors associated with the low LDCR rates in these States require further study.
A major limiting factor in the LDCR is the cost of Organ Recovery, as they are mostly absorbed by public hospitals, which may deter them from offering the DDL to hospitals outside their subsystem. Beyond direct costs, indirect costs such as brain death confirmation tests, intensive care unit bed use, and donor maintenance cost need to be addressed22. One of the most complex situations is the availability of intensive care unit beds in the State and the time-consuming process of the current allocation system. The resilience and positivity of Donation Coordinators are key elements in achieving conversion of DBD into DDL; however, this is not a sustainable model.
One of the largest contrasts detected in this study was the DBD pmp and DDL pmp activity in Mexico City and Mexico State. Our group has previously analyzed DBD pmp and DDL pmp activity in Mexico State within and outside the metropolitan area of the Valley of Mexico23. This proves that the LDCR is higher in areas of Mexico State outside of the Metropolitan Area than inside, where the greatest number of liver transplantations in the country are performed.
Limitations
The limitations of this study were related to the retrospective nature of data analysis. The analyzed variables were limited to those available in the datasets. For example, federally reported out-of-pocket expenses in healthcare have been associated with DBD pmp rates in other studies, but they are not available by the State. Other variables that could potentially explain the observed changes not available by State include the number of brain deaths per year, a rate that has only been reported in death certificates since 2022. Other variables included the number of ICU beds, the number of donation hospital coordinators, and the number of transit accidents. The models created for this study present a low determination coefficient, suggesting that they only partially explain the changes observed in States over time. Other factors may include overlapping service areas across States within the same healthcare subsystem and, tertiary healthcare facility clustering in large Metropolitan areas.
link
