R Under development (unstable) (2025-11-21 r89046 ucrt) -- "Unsuffered Consequences"
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> ################################################################################
> # file: test-vs-ahrq.R
> #
> # objective:
> #
> #   compare medicalcoder::comorbidities(..., method = "elixhauser_ahrqYYYY")
> #   against the official AHRQ SAS mapping results when fixtures are available.
> #
> # Note: using stats::reshape instead of data.table::melt so that this test can
> # run when no-suggests is TRUE.
> #
> ################################################################################
> library(medicalcoder)
> source('utilities.R')
> 
> # ahrq results
> ahrq_results <- readRDS("expected-ahrq-results.rds")
> 
> codes <-
+   stats::reshape(
+     data = ahrq_results,
+     direction = "long",
+     idvar = c("CMR_VERSION", "PATID"),
+     varying = list(
+       grep("^I10_DX", names(ahrq_results), value = TRUE),
+       grep("^DXPOA",  names(ahrq_results), value = TRUE)
+       ),
+     v.names = c("code", "poa"),
+     times = seq_along(grep("^I10_DX", names(ahrq_results)))
+   )
> 
> codes[["primarydx"]] <- as.integer(codes[["time"]] == "1")
> codes[["poa"]] <- as.integer(codes[["poa"]] == "Y")
> 
> 
> 
> # apply medicalcoder::comorbidities
> common_args <-
+   list(
+     icd.codes = "code",
+     id.vars = c("CMR_VERSION", "PATID"),
+     dx = 1,
+     icdv = 10,
+     poa.var = "poa",
+     primarydx.var = "primarydx",
+     flag.method = "current"
+   )
> 
> mdcr_2022 <- do.call(comorbidities, c(common_args, list(data = subset(codes, CMR_VERSION == 2022.1), method = "elixhauser_ahrq2022")))
> mdcr_2023 <- do.call(comorbidities, c(common_args, list(data = subset(codes, CMR_VERSION == 2023.1), method = "elixhauser_ahrq2023")))
> mdcr_2024 <- do.call(comorbidities, c(common_args, list(data = subset(codes, CMR_VERSION == 2024.1), method = "elixhauser_ahrq2024")))
> mdcr_2025 <- do.call(comorbidities, c(common_args, list(data = subset(codes, CMR_VERSION == 2025.1), method = "elixhauser_ahrq2025")))
> 
> mdcr_vs_ahrq_2022 <- merge(x = mdcr_2022, y = ahrq_results, all.x = TRUE, by = c("CMR_VERSION", "PATID"))
> mdcr_vs_ahrq_2023 <- merge(x = mdcr_2023, y = ahrq_results, all.x = TRUE, by = c("CMR_VERSION", "PATID"))
> mdcr_vs_ahrq_2024 <- merge(x = mdcr_2024, y = ahrq_results, all.x = TRUE, by = c("CMR_VERSION", "PATID"))
> mdcr_vs_ahrq_2025 <- merge(x = mdcr_2025, y = ahrq_results, all.x = TRUE, by = c("CMR_VERSION", "PATID"))
> 
> stopifnot("same number of rows" = nrow(mdcr_2022) == nrow(subset(ahrq_results, CMR_VERSION == 2022.1)) & nrow(mdcr_2022) == nrow(mdcr_vs_ahrq_2022))
> stopifnot("same number of rows" = nrow(mdcr_2023) == nrow(subset(ahrq_results, CMR_VERSION == 2022.1)) & nrow(mdcr_2023) == nrow(mdcr_vs_ahrq_2023))
> stopifnot("same number of rows" = nrow(mdcr_2024) == nrow(subset(ahrq_results, CMR_VERSION == 2022.1)) & nrow(mdcr_2024) == nrow(mdcr_vs_ahrq_2024))
> stopifnot("same number of rows" = nrow(mdcr_2025) == nrow(subset(ahrq_results, CMR_VERSION == 2022.1)) & nrow(mdcr_2025) == nrow(mdcr_vs_ahrq_2025))
> 
> # check each condition - this can change year to year
> cnds_2022 <- subset(get_elixhauser_index_scores(), !is.na(elixhauser_ahrq2022), select = "condition", drop = TRUE)
> cnds_2022 <- unique(cnds_2022)
> 
> cnds_2023 <- subset(get_elixhauser_index_scores(), !is.na(elixhauser_ahrq2023), select = "condition", drop = TRUE)
> cnds_2023 <- unique(cnds_2023)
> 
> cnds_2024 <- subset(get_elixhauser_index_scores(), !is.na(elixhauser_ahrq2024), select = "condition", drop = TRUE)
> cnds_2024 <- unique(cnds_2024)
> 
> cnds_2025 <- subset(get_elixhauser_index_scores(), !is.na(elixhauser_ahrq2025), select = "condition", drop = TRUE)
> cnds_2025 <- unique(cnds_2025)
> 
> for (j in cnds_2022) {
+   t <- identical(mdcr_vs_ahrq_2022[[j]], mdcr_vs_ahrq_2022[[paste0("CMR_", j)]])
+   if (!t) {# & !(j %in% c("CBVD", "HF"))) {
+     stop(sprintf('identical(mdcr_vs_ahrq_2022[["%s"]], mdcr_vs_ahrq_2022[["%s"]]) is not true', j, paste0("CMR_", j)))
+   }
+ }
> 
> for (j in cnds_2023) {
+   t <- identical(mdcr_vs_ahrq_2023[[j]], mdcr_vs_ahrq_2023[[paste0("CMR_", j)]])
+   if (!t) {
+     stop(sprintf('identical(mdcr_vs_ahrq_2023[["%s"]], mdcr_vs_ahrq_2023[["%s"]]) is not true', j, paste0("CMR_", j)))
+   }
+ }
> 
> for (j in cnds_2024) {
+   t <- identical(mdcr_vs_ahrq_2024[[j]], mdcr_vs_ahrq_2024[[paste0("CMR_", j)]])
+   if (!t) {
+     stop(sprintf('identical(mdcr_vs_ahrq_2024[["%s"]], mdcr_vs_ahrq_2024[["%s"]]) is not true', j, paste0("CMR_", j)))
+   }
+ }
> 
> for (j in cnds_2025) {
+   t <- identical(mdcr_vs_ahrq_2025[[j]], mdcr_vs_ahrq_2025[[paste0("CMR_", j)]])
+   if (!t) {
+     stop(sprintf('identical(mdcr_vs_ahrq_2025[["%s"]], mdcr_vs_ahrq_2025[["%s"]]) is not true', j, paste0("CMR_", j)))
+   }
+ }
> 
> stopifnot(mdcr_vs_ahrq_2022[["mortality_index"]]   == mdcr_vs_ahrq_2022[["CMR_Index_Mortality"]])
> stopifnot(mdcr_vs_ahrq_2022[["readmission_index"]] == mdcr_vs_ahrq_2022[["CMR_Index_Readmission"]])
> 
> stopifnot(mdcr_vs_ahrq_2023[["mortality_index"]]   == mdcr_vs_ahrq_2023[["CMR_Index_Mortality"]])
> stopifnot(mdcr_vs_ahrq_2023[["readmission_index"]] == mdcr_vs_ahrq_2023[["CMR_Index_Readmission"]])
> 
> stopifnot(mdcr_vs_ahrq_2024[["mortality_index"]]   == mdcr_vs_ahrq_2024[["CMR_Index_Mortality"]])
> stopifnot(mdcr_vs_ahrq_2024[["readmission_index"]] == mdcr_vs_ahrq_2024[["CMR_Index_Readmission"]])
> 
> stopifnot(mdcr_vs_ahrq_2025[["mortality_index"]]   == mdcr_vs_ahrq_2025[["CMR_Index_Mortality"]])
> stopifnot(mdcr_vs_ahrq_2025[["readmission_index"]] == mdcr_vs_ahrq_2025[["CMR_Index_Readmission"]])
> 
> ################################################################################
> #                                 End of File                                  #
> ################################################################################
> 
> proc.time()
   user  system elapsed 
   3.32    0.31    3.62