Coverage and redistribution of Colombian Health System

The Colombian healthcare system is currently undergoing a profound crisis, influenced by several factors. The National Government has considered, without a deep technical examination and guided by political and ideological interests, that the system must be transformed. Consequently, the system faces the following challenges:

1. The Colombian Congress is currently debating Bill 339/2023 in the Chamber of Representatives, which aims to overhaul the processes of care, public resource management, and actor responsibilities, ushering in a completely new healthcare system. Unfortunately, the focus is not on improving the current system but rather on developing one that disregards the advancements already in place.

2. The flow of financial resources to the current healthcare system has been slowed and sometimes frozen, leading to significant consequences in the delivery of healthcare services, which have had to be scaled back due to resource shortages.

In this context, I have analyzed the municipal coverage levels of the system and the geographic distribution of resources, closely examining the functioning of each regime: subsidized (without contributions) and contributory (with contributions). It is evident that the Colombian healthcare system is an effective social policy, redistributing resources to ensure access to healthcare services for the population without the means to pay.

The map of Contributory Regime Coverage (in blue) highlights high proportions of enrolled population, especially in major cities, which due to demographic and economic dynamics generate more employment and have higher population densities. Conversely, coverage is lower in the rest of the country.

The map of Subsidized Regime Coverage (in red) shows the opposite trend. In municipalities that are not necessarily economically dynamic, the enrollment rate in the regime exceeds 50% of the total population. This is achieved through contributions from the contributory regime and significant redistributive effects.

Healthcare reform is unlikely to guarantee the same level of healthcare services and equitable distribution of resources that have enabled the development of infrastructure and service capacity. Contributions may be lost within a system that encourages corruption.

I have constructed these maps using Ggplot in R and provide example code detailing each of their characteristics.

titletxt = 'Distribución Cobertura del Régimen Subsidiado de Salud'
subtitletxt = 'Proporción afiliados en población, 2022'
legendtxt = "Por Municipio" 
captiontxt = paste("Fuente: Elaboración Andrés Camargo, datos MinSalud & DANE.")

map_subsidiado = ggplot(data = total_data, aes(fill=fct_relevel(cat_reg_subs, c("0%-25%", "26%-50%","51%-75%",">75%")))) +
  geom_sf(color=NA) +
  geom_sf(data = total_data %>% group_by(DEPARTAMENTO) %>% summarise(), color = "white", fill = NA) + 
  scale_fill_manual(values = c("#ffcdbd","#f39d85","#e16c52","#cc3223")) +
  ggtitle(titletxt) +
  labs(caption = captiontxt, subtitle = subtitletxt, fill=legendtxt) +
  scale_x_continuous(limits = c(-66, -80)) +
  theme_void() +
  guides(fill = guide_legend(
    title.position = "top",
    label.position = "right"
  )) +
  theme(
    text = element_text(family="PT Sans"),
    plot.title = element_text(face = "bold", hjust = 0, size= 48, vjust = 3),
    plot.subtitle = element_text(size = 44),
    
    legend.title = element_text(face = "bold", size = 40),
    legend.text = element_text(size = 38),
    legend.position = c(0,0.98),
    legend.justification = c("left", "top"),
    legend.key.size = unit(0.6, 'cm'),
    legend.spacing.x = unit(0.05, 'cm'),
    
    plot.caption = element_text(hjust = 0, color ="#454545", size = 22, vjust = 19,margin = margin(t = 0, r = 0, b = 0, l = 0)),
    plot.margin = unit(c(5,1,1,1), 'pt'),
    axis.title.x = element_blank(),  
    axis.text.x = element_blank(),   
    axis.ticks.x = element_blank() 
  )