Availability smoking cessation products.R

# ScotPHO indicators: Availability of smoking cessation products

#   Part 1 - Create basefile
#   Part 2 - Run analysis functions

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## Packages/Filepaths/Functions ----
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source("1.indicator_analysis.R") #Normal indicator functions

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## Part 1 - Create basefile ----
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#Reading data provided by Prescribing team
data_products <- read_excel(paste0(data_folder, "Received Data/IR2022-00878_smoking_products.xlsx"), 
                            sheet = "Output", range = cell_limits(c(8, 2), c(NA, 10))) %>% 
  janitor::clean_names()

# Bringing code information for LA.
ca_lookup <- readRDS(paste0(data_folder, "Lookups/Geography/CAdictionary.rds"))

data_products <- left_join(data_products, ca_lookup, #Merging both
                           by = c("dispensing_council_area" = "areaname")) %>% 
  filter(!(is.na(code))) #excluding values without a valid ca

# aggregate to get total DDDs for each datazone/year.
data_products <- data_products %>% rename(year = financial_year, ca = code) %>% 
  group_by(ca, year) %>% summarize(numerator = sum(defined_daily_doses, na.rm = T)) %>%  
  mutate(numerator = numerator/365) %>%  # value is defined daily doses, so needs to be divided by 365.
  ungroup() %>% select(ca, year, numerator) 

saveRDS(data_products, file=paste0(data_folder, 'Prepared Data/cessation_products_raw.rds'))

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## Part 3 - Run analysis functions ----
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analyze_first(filename = "cessation_products", geography = "council", measure = "crude", hscp = T,
              yearstart = 2002, yearend = 2021, time_agg = 1, pop="CA_pop_12+")

analyze_second(filename = "cessation_products", measure = "crude", time_agg = 1,
               crude_rate = 1000, ind_id = 1544, year_type = "financial")

##END