Letalidade neonatal em hospitais de Cuiabá e Várzea Grande, MT

#---------- Pacotes

library(tidyverse)
library(microdatasus)
library(kableExtra)

#---------- Download

RD <- fetch_datasus(information_system = "SIH-RD", 
                    year_start = 2019, year_end = 2023, 
                    month_start = 1, month_end = 12, uf = "MT",
                    vars = c("N_AIH", "NASC", "DT_INTER", "DT_SAIDA", "MORTE", "CNES", "MARCA_UTI"))


RJ <- fetch_datasus(information_system = "SIH-RJ", 
                    year_start = 2019, year_end = 2023, 
                    month_start = 1, month_end = 12, uf = "MT",
                    vars = c("N_AIH", "NASC", "DT_INTER", "DT_SAIDA", "MORTE", "CNES", "MARCA_UTI"))

#---------- Aprovados + Glosados

a <- RJ |> 
  distinct(N_AIH, .keep_all = TRUE) |> 
  anti_join(RD, by = "N_AIH")


b <- RD |> 
  inner_join(RJ, by = "N_AIH", suffix = c("",".r")) |> 
  select(N_AIH, NASC, DT_INTER, DT_SAIDA, MORTE, CNES, MARCA_UTI)


c <- RD |> 
  anti_join(RJ, by = "N_AIH")


SIH <- rbind(a, b, c)
rm(a, b, c, RJ, RD)

#---------- Processamento

SIH <- SIH |> 
  filter(CNES %in% c("2311682", "2655411",
                     "2659107", "2391635")) |> 
  mutate(NASC = ymd(NASC),
         DT_INTER = ymd(DT_INTER),
         DT_SAIDA = ymd(DT_SAIDA),
         IDADE = as.numeric(DT_INTER - NASC),
         ANO = year(DT_SAIDA),
         MES = month(DT_SAIDA, label = TRUE, abbr = TRUE),
         UTI = case_when(MARCA_UTI == "00" ~ "Não", TRUE ~ "Sim"),
         CNES = case_when(CNES == "2311682" ~ "HSH",
                          CNES == "2655411" ~ "HUJM",
                          CNES == "2659107" ~ "HG", 
                          CNES == "2391635" ~ "PSMVG")) |> 
  filter(IDADE <= 28,
         DT_INTER >= "2019-01-01")

SIH |> 
  group_by(CNES) |> 
  summarise(n = n()) |> 
  arrange(desc(n)) |>
  rename(Hospital = CNES,
         `Internações` = n) |> 
  mutate(Hospital = case_when(Hospital == "HG" ~ "Hospital Geral - HG",
                              Hospital == "HSH" ~ "Hospital Santa Helena - HSH",
                              Hospital == "PSMVG" ~ "Pronto Socorro de Várzea Grande - PSMVG",
                              Hospital == "HUJM" ~ "Hospital Universitário Julio Muller - HUJM"),
         `%` = round(`Internações` / sum(`Internações`) * 100, digits = 1)) |> 
  kbl() |> 
  kable_styling(html_font = "Fira Sans",
                bootstrap_options = "striped") |> 
  row_spec(0, background = "darkorange", color = "black")

SIH |> 
  filter(DT_INTER >= "2020-01-01") |> 
  group_by(ANO, MES) |> 
  summarise(letalidade = length(MORTE[MORTE == "1"])/length(MORTE)*100) |> 
  ggplot(aes(y = letalidade, x = MES)) +
  geom_col(fill = "darkorange", alpha = 0.8) +
  geom_text(aes(label = round(letalidade, 0)), color = "black", vjust = 1.3) +
  hrbrthemes::theme_ipsum_ps() +
  scale_y_continuous(limits = c(0,NA)) +
  labs(subtitle = str_glue("Fonte: SIH-DATASUS | {n_distinct(SIH$CNES)} unidades hospitalares"),
       y = "Letalidade (%)",
       x = "Mês do óbito") +
  theme(plot.title = element_text(size = 15),
        plot.subtitle = element_text(size = 11),
        panel.grid.minor.x = element_blank(),
        panel.grid.minor.y = element_blank(),
        panel.grid.major.x = element_blank()) +
  facet_wrap(~ ANO)

SIH |>
  filter(DT_INTER >= "2020-01-01") |> 
  group_by(CNES, ANO) |> 
  summarise(letalidade = length(MORTE[MORTE == "1"])/length(MORTE)*100) |> 
  ggplot(aes(y = letalidade, x = reorder(CNES, +letalidade))) +
  geom_col(fill = "darkorange", alpha = 0.8) +
  geom_text(aes(label = round(letalidade, 1)), color = "black", hjust = 1.2) +
  hrbrthemes::theme_ipsum_pub() +
  labs(subtitle = str_glue("Fonte: SIH-DATASUS | {n_distinct(SIH$CNES)} unidades hospitalares"),
       y = "Letalidade (%)",
       x = "Hospital") +
  theme(plot.title = element_text(size = 15),
        plot.subtitle = element_text(size = 11),
        panel.grid.minor.x = element_blank(),
        panel.grid.minor.y = element_blank(),
        panel.grid.major.y = element_blank()) +
  coord_flip() +
  facet_wrap(~ ANO) +
  scale_y_continuous(n.breaks = 4)

SIH |> 
  group_by(CNES) |> 
  summarise(let2022 = length(MORTE[MORTE == "1" & ANO == 2022])/length(MORTE[ANO == 2022])*100,
            let2023 = length(MORTE[MORTE == "1" & ANO == 2023])/length(MORTE[ANO == 2023])*100,
            var = (let2023 - let2022) / let2022 * 100) |> 
  ggplot(aes(y = var, x = reorder(CNES, var))) +
  geom_col(fill = "darkorange", alpha = 0.8) +
  geom_text(aes(label = round(var, 1)), color = "black", vjust = 1.3) +
  hrbrthemes::theme_ipsum_pub() +
  labs(y = "Variação (%)",
       x = "Hospital") +
  theme(plot.title = element_text(size = 15),
        plot.subtitle = element_text(size = 11),
        panel.grid.minor.x = element_blank(),
        panel.grid.minor.y = element_blank(),
        panel.grid.major.x = element_blank()) +
  scale_y_continuous(n.breaks = 8)