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ITS_var.R
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ITS_var.R
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#####################################################################################
##### This script is for preparing the variable for ITS #####
##### The outcome variables includes broad spectrum and group by infection type #####
#####################################################################################
library("dplyr")
library("tidyverse")
library("lubridate")
rm(list=ls())
setwd(here::here("output", "measures"))
df.19 <- read_rds("abtype_2019.rds") %>% select(date,type,infection)
df.20 <- read_rds("abtype_2020.rds") %>% select(date,type,infection)
df.21 <- read_rds("abtype_2021.rds") %>% select(date,type,infection)
df_raw <- bind_rows(df.19,df.20,df.21)
df_raw$date = as.Date(df_raw$date)
df_raw$infection=recode(df_raw$infection,
asthma ="Asthma",
cold="Cold",
cough="Cough",
copd="COPD",
pneumonia="Pneumonia",
renal="Renal",
sepsis="Sepsis",
throat="Sore throat",
uti = "UTI",
lrti = "LRTI",
urti = "URTI",
sinusits = "Sinusitis",
otmedia = "Otitis media",
ot_externa = "Otitis externa")
df_raw$infection[df_raw$infection == ""] <- NA
df_raw$indication <- ifelse(is.na(df_raw$infection),0,1)
df_raw <- df_raw %>% filter(!is.na(date))
### prepare var ### URL:https://www.opencodelists.org/codelist/opensafely/co-amoxiclav-cephalosporins-and-quinolones/0d299a50/ ###
broadtype <- c("Co-amoxiclav","Cefaclor","Cefadroxil","Cefixime","Cefotaxime","Ceftriaxone",
"Ceftazidime","Cefuroxime","Cefalexin","Cefradine","Ciprofloxacin","Levofloxacin",
"Moxifloxacin","Nalidixic acid","Norfloxacin","Ofloxacin")
start_covid = as.Date("2020-04-01")
covid_adjustment_period_from = as.Date("2020-03-01")
### Prepare the data frame for Interrupted time-series analysis ###
### Transfer df into numOutcome / numEligible version
df_raw$cal_year <- year(df_raw$date)
df_raw$cal_mon <- month(df_raw$date)
df_raw$time <- as.numeric(df_raw$cal_mon+(df_raw$cal_year-2019)*12)
### Select coded prescription
df_raw <- df_raw %>% filter (indication == 1)
### Interrupted time-series analysis ###
### UTI
df <- df_raw %>% filter (infection == "UTI")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype)
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_uti.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### Cold
df <- df_raw %>% filter (infection == "Cold")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_cold.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### Cough
df <- df_raw %>% filter (infection == "Cough")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_cough.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### COPD
df <- df_raw %>% filter (infection == "COPD")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_copd.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### Sore throat
df <- df_raw %>% filter (infection == "Sore throat")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_throat.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### LRTI
df <- df_raw %>% filter (infection == "LRTI")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_lrti.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### URTI
df <- df_raw %>% filter (infection == "URTI")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_urti.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### Sinusitis
df <- df_raw %>% filter (infection == "Sinusitis")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_sinusitis.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### Otitis media
df <- df_raw %>% filter (infection == "Otitis media")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_ot_media.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
### Otitis externa
df <- df_raw %>% filter (infection == "Otitis externa")
### Transfer df into numOutcome / numEligible version
df.broad <- df %>% filter(type %in% broadtype )
df.broad_total <- df.broad %>% group_by(time) %>% summarise(
numOutcome = n(),
)
df.all <- df %>% group_by(time) %>% summarise(
numEligible = n(),
)
df.model <- merge(df.broad_total,df.all,by="time")
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
df.model$monPlot <- as.Date(with(df.model,paste(year,mon,day,sep="-")),"%Y-%m-%d")
df.model <- df.model %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
write_csv(df.model, here::here("output", "mon_ot_externa.csv"))
rm(df,df.all,df.broad,df.broad_total,df.model)
rm(DF)
col_spec <-cols_only( broad_ab_count = col_number(),
antibiotic_count = col_number(),
date = col_date(format = "")
)
df <- read_csv("measure_broad-spectrum-ratio.csv",
col_types = col_spec)
names(df) <- c("numOutcome","numEligible","monPlot")
df.model <- df %>%
mutate(pre_covid = ifelse(monPlot < covid_adjustment_period_from , 1, 0),
during_covid = ifelse(monPlot >= start_covid , 1, 0)) %>%
mutate(covid = ifelse(pre_covid == 1 , 0,
ifelse (during_covid == 1, 1,
NA)))
df.model$cal_year <- year(df.model$monPlot)
df.model$cal_mon <- month(df.model$monPlot)
df.model$time <- as.numeric(df.model$cal_mon+(df.model$cal_year-2019)*12)
df.model <- df.model %>% mutate(mon = case_when(time>=1 & time<=12 ~ time,
time>=13 & time<=24 ~ time-12,
time>=24 & time<=36 ~ time-24,
time>36 ~ time-36)) %>%
mutate(year = case_when(time>=1 & time<=12 ~ 2019,
time>=13 & time<=24 ~ 2020,
time>=24 & time<=36 ~ 2021,
time>36 ~ 2022)) %>%
mutate(day = 1)
write_csv(df.model, here::here("output", "mon_all.csv"))