Bug - Tidy commhosp variable

NEWS.md

@@ -1,3 +1,8 @@
+# March 2025 Update - Unreleased
+* 24/25 files have been updated, containing data up to December 2024.
+* 17/18 - 23/24 files have been updated.
+* The variable `commhosp` has been tidied up - now shows Y/N for all available datasets
+
 # December 2024 Update - released 10-Dec-24
 * 24/25 files have been updated, containing data up to September 2024.
 * 17/18 - 23/24 files have been updated.
@@ -83,7 +88,7 @@
   * Homelessness Flags.
 * Bug fixes: 
   * Blank `datazone` in A&E. This has been fixed and was due to PC8 postcode format matching onto SLF pc lookup. 
   * Large increase in preventable beddays. This was caused due to an SPSS vs R logic difference. Uses SPSS logic which 
     brings the difference down to `3.3%`. 
   * Issue with `locality` which showed `locality` in each row instead of its true `locality`. This has now been fixed. 
   * Duplicated CHI in the individual file. The issue was identified when trying to include HRIs. This has now been corrected. 
@@ -102,7 +107,7 @@
 * Removal of `keydate1_dateformat` and `keydate2_dateformat`.
 * `dd_responsible_lca` – This variable now uses CA2019 codes instead of the 2-digit ‘old’ LCA code.
 * Preventable beddays - not able to calculate these correctly. * Death fixes not included.
 * Variables not ordered in R like they used to be in SPSS.
 * End of HHG.
 * New variable `ch_postcode`.
 * rename of variables `cost_total_net_incdnas`, `ooh_outcome.1`, `ooh_outcome.2`, `ooh_outcome.3`, `ooh_outcome.4`, `totalnodncontacts`. 
@@ -163,7 +168,7 @@
 * Fixed a bug where CH costs was not referring to end of year. 
   * e.g. 2018 costs relates to 2017/18
 * The changes to Homelessness described in the March update have been properly implemented.
 * We now use [`{haven}`](https://haven.tidyverse.org/news/index.html) to compress the SPSS files which compresses them better than SPSS does 🤷
 ♂️
 * `cij_marker` is now a numeric instead of a string which changes empty strings to missing instead of blank using sysmis.
   * Check code of the form `cij_marker = "x"`. `x` now needs to be a numeric.

R/process_extract_ae.R

@@ -65,7 +65,9 @@ process_extract_ae <- function(data, year, write_to_disk = TRUE) {
       smrtype = add_smrtype(.data$recid)
     ) %>%
     # Allocate the costs to the correct month
-    create_day_episode_costs(.data$record_keydate1, .data$cost_total_net)
+    create_day_episode_costs(.data$record_keydate1, .data$cost_total_net) %>%
+    # clean up commhosp values
+    dplyr::mutate(commhosp = dplyr::if_else(.data$commhosp == 1L, "Y", "N"))
 
 
   # Factors ---------------------------------------------------

R/process_extract_outpatients.R

@@ -36,7 +36,9 @@ process_extract_outpatients <- function(data, year, write_to_disk = TRUE) {
     # Allocate the costs to the correct month
     create_day_episode_costs(.data$record_keydate1, .data$cost_total_net) %>%
     # sort by chi record_keydate1
-    dplyr::arrange(.data$chi, .data$record_keydate1)
+    dplyr::arrange(.data$chi, .data$record_keydate1) %>%
+    # clean up commhosp values
+    dplyr::mutate(commhosp = dplyr::if_else(.data$commhosp == 1L, "Y", "N"))
 
   # Factors ---------------------------------------
   outpatients_clean <- outpatients_clean %>%

R/read_extract_ae.R

@@ -43,7 +43,8 @@ read_extract_ae <- function(
       "Total Net Costs" = readr::col_double(),
       "Age at Midpoint of Financial Year" = readr::col_double(),
       "Case Reference Number" = readr::col_character(),
-      "Significant Facility Code" = readr::col_character()
+      "Significant Facility Code" = readr::col_character(),
+      "Community Hospital Flag" = readr::col_character(),
     )
   ) %>%
     # rename variables