* removed chronic conditions functions, as their endpoints have disap…

…peared
andrewallenbruce · Jul 21, 2024 · ad6a8a8 · ad6a8a8
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -3,8 +3,8 @@ Package: provider
 Title: Access Public Healthcare Provider Data
 Version: 0.0.1
 Authors@R: 
-    person("Andrew", "Bruce", , "andrew.bruce@northstarrevenueintegrity.com", role = c("aut", "cre", "cph"))
-Maintainer: Andrew Bruce <andrew.bruce@northstarrevenueintegrity.com>
+    person("Andrew", "Bruce", , "andrewallenbruce@gmail.com", role = c("aut", "cre", "cph"))
+Maintainer: Andrew Bruce <andrewallenbruce@gmail.com>
 Description: Provides various features to facilitate easy access to
     publicly available healthcare provider data. Includes functions to
     tidy the data being accessed, whether for reporting purposes or
@@ -75,7 +75,6 @@ Remotes:
     github::andrewallenbruce/fuimus,
     github::anthonynorth/roxyglobals,
     github::nt-williams/rxnorm,
-    github::rstudio/gt,
     github::yutannihilation/ggsflabel
 Config/roxyglobals/filename: generated-globals.R
 Config/roxyglobals/unique: TRUE
@@ -86,4 +85,4 @@ Language: en-US
 LazyData: true
 Roxygen: list(markdown = TRUE, roclets = c("collate", "namespace", "rd",
     "roxyglobals::global_roclet"))
-RoxygenNote: 7.3.1
+RoxygenNote: 7.3.2
diff --git a/NAMESPACE b/NAMESPACE
@@ -5,13 +5,10 @@ export(affiliations)
 export(bene_years)
 export(beneficiaries)
 export(betos)
-export(cc_years)
 export(change)
 export(chg)
 export(clinicians)
-export(compare_conditions)
 export(compare_hcpcs)
-export(conditions)
 export(df2chr)
 export(display_long)
 export(duration_vec)

diff --git a/R/cms.R b/R/cms.R
@@ -1,12 +1,18 @@
 #' Update CMS.gov API distribution IDs
+#'
 #' @param api name of the api
+#'
 #' @param check `"base"`, `"id"`, or `"years"`, default is `"id"`
+#'
 #' @return A [tibble()] containing the updated ids.
+#'
 #' @examplesIf interactive()
 #' cms_update("Provider of Services File - Clinical Laboratories", "base")
 #' cms_update("Provider of Services File - Clinical Laboratories", "id")
 #' cms_update("Provider of Services File - Clinical Laboratories", "years")
+#'
 #' @autoglobal
+#'
 #' @noRd
 cms_update <- function(api, check = "id") {
 
@@ -239,8 +245,8 @@ api_years <- function(fn) {
                            "rxp" ~ "Medicare Part D Prescribers - by Provider",
                            "outps" ~ "Medicare Outpatient Hospitals - by Provider and Service",
                            "outgs" ~ "Medicare Outpatient Hospitals - by Geography and Service",
-                           "scc" ~ "Specific Chronic Conditions",
-                           "mcc" ~ "Multiple Chronic Conditions",
+                           # "scc" ~ "Specific Chronic Conditions",
+                           # "mcc" ~ "Multiple Chronic Conditions",
                            "qpp" ~ "Quality Payment Program Experience",
                            .default = NULL)
 

diff --git a/R/compare.R b/R/compare.R
@@ -1,26 +1,15 @@
 #' Compare Provider Performance
 #'
-#' @description
-#'
-#' + `compare_hcpcs()` allows the user to compare a provider's yearly HCPCS
+#' `compare_hcpcs()` allows the user to compare a provider's yearly HCPCS
 #' utilization data to state and national averages
 #'
-#' + `compare_conditions()` allows the user to compare the average yearly
-#' prevalence of chronic conditions among a provider's patient mix to state and
-#' national averages
-#'
-#' @return A [tibble][tibble::tibble-package] containing:
-#' + `compare_hcpcs()`
-#' + `compare_conditions()`
-#' @name compare
-NULL
-
 #' @param df < *tbl_df* > // **required**
 #'
-#' [tibble()] returned from `utilization(type = "Service")`
+#' [tibble][tibble::tibble-package] returned from `utilization(type = "Service")`
 #'
-#' @examplesIf interactive()
+#' @returns A [tibble][tibble::tibble-package]
 #'
+#' @examplesIf interactive()
 #' compare_hcpcs(utilization(year = 2018,
 #'                           type = "Service",
 #'                           npi = 1023076643))
@@ -30,8 +19,8 @@ NULL
 #'                                    type = "Service")) |>
 #' compare_hcpcs()
 #'
-#' @rdname compare
 #' @autoglobal
+#'
 #' @export
 compare_hcpcs <- function(df) {
 
@@ -91,93 +80,3 @@ hcpcs_cols <- function(df) {
 
   df |> dplyr::select(dplyr::any_of(cols))
 }
-
-#' @param df < *tbl_df* > // **required** [tibble()] returned from `utilization(type = "Provider")`
-#'
-#' @param pivot < *boolean* > // __default:__ `FALSE` Pivot output
-#'
-#' @rdname compare
-#'
-#' @examplesIf interactive()
-#'
-#' compare_conditions(utilization(year = 2018,
-#'                                type = "Provider",
-#'                                npi = 1023076643))
-#'
-#' map_dfr(util_years(), ~utilization(year = .x,
-#'                                    npi = 1023076643,
-#'                                    type = "Provider")) |>
-#' compare_conditions()
-#'
-#' @autoglobal
-#' @export
-compare_conditions <- function(df, pivot = FALSE) {
-
-  if (!inherits(df, "utilization_provider")) {
-    cli::cli_abort(c(
-      "{.var df} must be of class {.cls 'utilization_provider'}.",
-      "x" = "{.var df} is of class {.cls {class(df)}}."))
-  }
-#########################
-  x <- dplyr::select(df, year, sublevel = state, conditions) |>
-    tidyr::unnest(conditions) |>
-    dplyr::mutate(hcc_risk_avg = NULL, level = "Provider", .after = year) |>
-    cnd_rename() |>
-    tidyr::pivot_longer(cols      = !c(year, level, sublevel),
-                        names_to  = "condition",
-                        values_to = "prevalence") |>
-    dplyr::filter(!is.na(prevalence), year %in% cc_years())
-
-  y <- dplyr::select(x, year, condition, sublevel)
-
-  y$set     <- "Specific"
-  y$demo    <- "All"
-  y$subdemo <- "All"
-  y$age     <- "All"
-  y
-  state             <- y
-  national          <- y
-  national$sublevel <- "National"
-
-  req <- vctrs::vec_rbind(state, national)
-
-  res <- furrr::future_pmap_dfr(req, conditions,
-                                .options = furrr::furrr_options(seed = NULL))
-
-  res <- dplyr::select(res, year, level, condition, prevalence)
-  x$sublevel <- NULL
-  results           <- vctrs::vec_rbind(x, res)
-  results$level     <- fct_level(results$level)
-  results$condition <- fct_cc(results$condition)
-#######################
-  if (pivot) {
-    results <- tidyr::pivot_wider(results,
-                                  names_from = c(year, level),
-                                  values_from = prevalence)
-  }
-  return(results)
-}
-
-#' @param df data frame
-#' @autoglobal
-#' @noRd
-cnd_rename <- function(df) {
-  cols <- c('Atrial Fibrillation'                         = 'cc_af',
-            "Alzheimer's Disease/Dementia"                = 'cc_alz',
-            'Asthma'                                      = 'cc_asth',
-            'Cancer'                                      = 'cc_canc',
-            'Heart Failure'                               = 'cc_chf',
-            'Chronic Kidney Disease'                      = 'cc_ckd',
-            'COPD'                                        = 'cc_copd',
-            'Depression'                                  = 'cc_dep',
-            'Diabetes'                                    = 'cc_diab',
-            'Hyperlipidemia'                              = 'cc_hplip',
-            'Hypertension'                                = 'cc_hpten',
-            'Ischemic Heart Disease'                      = 'cc_ihd',
-            'Osteoporosis'                                = 'cc_opo',
-            'Arthritis'                                   = 'cc_raoa',
-            'Schizophrenia and Other Psychotic Disorders' = 'cc_sz',
-            'Stroke'                                      = 'cc_strk')
-
-  df |> dplyr::rename(dplyr::any_of(cols))
-}
diff --git a/R/generated-globals.R b/R/generated-globals.R
@@ -134,8 +134,6 @@ utils::globalVariables(c(
   "cola",
   # <mips_2021>
   "collection_type",
-  # <compare_conditions>
-  "condition",
   # <laboratories>
   "confirmed",
   # <laboratories>
@@ -164,8 +162,6 @@ utils::globalVariables(c(
   "definition",
   # <gt_datadict>
   "Definition",
-  # <conditions>
-  "demographic",
   # <meta.json>
   "describedBy",
   # <cms_dataset_search>
@@ -225,7 +221,6 @@ utils::globalVariables(c(
   # <cms_update>
   # <meta.json>
   "distribution_title",
-  # <conditions>
   # <outpatient>
   # <prescribers>
   # <quality_payment>
@@ -323,7 +318,6 @@ utils::globalVariables(c(
   # <meta.json>
   "landingPage",
   # <compare_hcpcs>
-  # <compare_conditions>
   # <tidyup_geography.rx>
   # <tidyup_drug.rx>
   # <tidyup_service.util>
@@ -414,8 +408,6 @@ utils::globalVariables(c(
   "pos",
   # <nppes>
   "pr",
-  # <compare_conditions>
-  "prevalence",
   # <mips_2021>
   "prf_rate",
   # <rbcs_util>
@@ -481,7 +473,6 @@ utils::globalVariables(c(
   # <tidyup_service.util>
   "state",
   # <beneficiaries>
-  # <conditions>
   # <prescribers>
   # <utilization>
   # <fct_stabb>
@@ -507,8 +498,6 @@ utils::globalVariables(c(
   "subgroup_general",
   # <hospitals>
   "subgroup_other",
-  # <compare_conditions>
-  "sublevel",
   # <hospitals>
   "subtotal",
   # <medline>
@@ -569,7 +558,6 @@ utils::globalVariables(c(
   # <beneficiaries>
   # <betos>
   # <clinicians>
-  # <conditions>
   # <hospitals>
   # <laboratories>
   # <mips_2021>
@@ -592,7 +580,6 @@ utils::globalVariables(c(
   # <change_year>
   # <cms_update>
   # <compare_hcpcs>
-  # <compare_conditions>
   # <open_ids>
   # <cols_qelig>
   "year",