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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,215 @@ | ||
| #' Aggregate by CHI | ||
| #' | ||
| #' @description Aggregate episode file by CHI to convert into | ||
| #' individual file. | ||
| #' | ||
| #' @importFrom data.table .N | ||
| #' @importFrom data.table .SD | ||
| #' | ||
| #' @inheritParams create_individual_file | ||
| aggregate_by_chi_zihao <- function(episode_file) { | ||
| cli::cli_alert_info("Aggregate by CHI function started at {Sys.time()}") | ||
|
|
||
| # Convert to data.table | ||
| data.table::setDT(episode_file) | ||
|
|
||
| # Ensure all variable names are lowercase | ||
| data.table::setnames(episode_file, stringr::str_to_lower) | ||
|
|
||
| # Sort the data | ||
| data.table::setkeyv( | ||
| episode_file, | ||
| c( | ||
| "chi", | ||
| "record_keydate1", | ||
| "keytime1", | ||
| "record_keydate2", | ||
| "keytime2" | ||
| ) | ||
| ) | ||
|
|
||
| data.table::setnames( | ||
| episode_file, | ||
| c( | ||
| "ch_chi_cis", "cij_marker", "ooh_case_id" | ||
| # ,"hh_in_fy" | ||
| ), | ||
| c( | ||
| "ch_cis_episodes", "cij_total", "ooh_cases" | ||
| # ,"hl1_in_fy" | ||
| ) | ||
| ) | ||
|
|
||
| # column specification, grouped by chi | ||
| # columns to select last | ||
| cols2 <- c( | ||
| "postcode", | ||
| "dob", | ||
| "gpprac", | ||
| vars_start_with(episode_file, "sc_") | ||
| ) | ||
| # columns to count unique rows | ||
| cols3 <- c( | ||
| "ch_cis_episodes", | ||
| "cij_total", | ||
| "cij_el", | ||
| "cij_non_el", | ||
| "cij_mat", | ||
| "cij_delay", | ||
| "ooh_cases", | ||
| "preventable_admissions" | ||
| ) | ||
| # columns to sum up | ||
| cols4 <- c( | ||
| vars_end_with( | ||
| episode_file, | ||
| c( | ||
| "episodes", | ||
| "beddays", | ||
| "cost", | ||
| "attendances", | ||
| "attend", | ||
| "contacts", | ||
| "hours", | ||
| "alarms", | ||
| "telecare", | ||
| "paid_items", | ||
| "advice", | ||
| "homev", | ||
| "time", | ||
| "assessment", | ||
| "other", | ||
| "dn", | ||
| "nhs24", | ||
| "pcc", | ||
| "_dnas" | ||
| ) | ||
| ), | ||
| vars_start_with( | ||
| episode_file, | ||
| "sds_option" | ||
| ), | ||
| "health_net_cost_inc_dnas" | ||
| ) | ||
| cols4 <- cols4[!(cols4 %in% c("ch_cis_episodes"))] | ||
| # columns to select maximum | ||
| cols5 <- c("nsu", vars_contain(episode_file, c("hl1_in_fy"))) | ||
| data.table::setnafill(episode_file, fill = 0L, cols = cols5) | ||
| # compute | ||
| individual_file_cols1 <- episode_file[, | ||
| .(gender = mean(gender)), | ||
|
Check warning on line 100 in R/aggregate_by_chi_zihao.R
|
||
| by = "chi" | ||
| ] | ||
| individual_file_cols2 <- episode_file[, | ||
| .SD[.N], | ||
| .SDcols = cols2, | ||
| by = "chi" | ||
| ] | ||
| individual_file_cols3 <- episode_file[, | ||
| lapply(.SD, function(x) { | ||
| data.table::uniqueN(x, na.rm = TRUE) | ||
| }), | ||
| .SDcols = cols3, | ||
| by = "chi" | ||
| ] | ||
| individual_file_cols4 <- episode_file[, | ||
| lapply(.SD, function(x) { | ||
| sum(x, na.rm = TRUE) | ||
| }), | ||
| .SDcols = cols4, | ||
| by = "chi" | ||
| ] | ||
| individual_file_cols5 <- episode_file[, | ||
| lapply(.SD, function(x) max(x, na.rm = TRUE)), | ||
| .SDcols = cols5, | ||
| by = "chi" | ||
| ] | ||
| individual_file_cols6 <- episode_file[, | ||
| .( | ||
| preventable_beddays = ifelse( | ||
| max(cij_ppa, na.rm = TRUE), | ||
| max(cij_end_date) - min(cij_start_date), | ||
|
Check warning on line 131 in R/aggregate_by_chi_zihao.R
|
||
| NA_real_ | ||
| ) | ||
| ), | ||
| # cij_marker has been renamed as cij_total | ||
| by = c("chi", "cij_total") | ||
| ] | ||
| individual_file_cols6 <- individual_file_cols6[, | ||
| .( | ||
| preventable_beddays = sum(preventable_beddays, na.rm = TRUE) | ||
| ), | ||
| by = "chi" | ||
| ] | ||
|
|
||
| individual_file <- dplyr::bind_cols( | ||
| individual_file_cols1, | ||
| individual_file_cols2[, chi := NULL], | ||
|
Check warning on line 147 in R/aggregate_by_chi_zihao.R
|
||
| individual_file_cols3[, chi := NULL], | ||
| individual_file_cols4[, chi := NULL], | ||
| individual_file_cols5[, chi := NULL], | ||
| individual_file_cols6[, chi := NULL] | ||
| ) | ||
|
|
||
| # convert back to tibble | ||
| return(dplyr::as_tibble(individual_file)) | ||
| } | ||
|
|
||
|
|
||
| #' select columns ending with some patterns | ||
| #' @describeIn select columns based on patterns | ||
| vars_end_with <- function(data, vars, ignore_case = FALSE) { | ||
| names(data)[stringr::str_ends( | ||
| names(data), | ||
| stringr::regex(paste(vars, collapse = "|"), | ||
| ignore_case = ignore_case | ||
| ) | ||
| )] | ||
| } | ||
|
|
||
| #' select columns starting with some patterns | ||
| #' @describeIn select columns based on patterns | ||
| vars_start_with <- function(data, vars, ignore_case = FALSE) { | ||
| names(data)[stringr::str_starts( | ||
| names(data), | ||
| stringr::regex(paste(vars, collapse = "|"), | ||
| ignore_case = ignore_case | ||
| ) | ||
| )] | ||
| } | ||
|
|
||
| #' select columns contains some characters | ||
| #' @describeIn select columns based on patterns | ||
| vars_contain <- function(data, vars, ignore_case = FALSE) { | ||
| names(data)[stringr::str_detect( | ||
| names(data), | ||
| stringr::regex(paste(vars, collapse = "|"), | ||
| ignore_case = ignore_case | ||
| ) | ||
| )] | ||
| } | ||
|
|
||
| #' Aggregate CIS episodes | ||
| #' | ||
| #' @description Aggregate CH variables by CHI and CIS. | ||
| #' | ||
| #' @inheritParams create_individual_file | ||
| aggregate_ch_episodes_zihao <- function(episode_file) { | ||
| cli::cli_alert_info("Aggregate ch episodes function started at {Sys.time()}") | ||
|
|
||
| # Convert to data.table | ||
| data.table::setDT(episode_file) | ||
|
|
||
| # Perform grouping and aggregation | ||
| episode_file <- episode_file[, `:=`( | ||
| ch_no_cost = max(ch_no_cost), | ||
| ch_ep_start = min(record_keydate1), | ||
| ch_ep_end = max(ch_ep_end), | ||
| ch_cost_per_day = mean(ch_cost_per_day) | ||
| ), by = c("chi", "ch_chi_cis")] | ||
|
|
||
| # Convert back to tibble if needed | ||
| episode_file <- tibble::as_tibble(episode_file) | ||
|
|
||
| return(episode_file) | ||
| } | ||
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@lizihao-anu I don't think we need the zoo package? I assume this was used in some of the 'original code'.
Can you confirm, and also remove
aggregate_ch_episodesandaggregate_by_chiand rename 'your' data.table versions to take their place as I think we're happy they work and do a better / faster job.