R/btbv4_path_fac_only.R

In utah-osa/hcctools2: OSA's Health Care Compare Tool package

#' btbv4_path_fac_only
#'
#' @param df
#'
#' @return
#' @export
#'
#' @examples
btbv4_path_fac_only<- function(df){
  df[,`:=`(
    cleaned_names =       pmap(.l=list(surg_sp_name_clean=path_sp_name_clean,
                                       surg_bp_name_clean=path_bp_name_clean,
                                       faci_sp_name_clean = faci_sp_name_clean,
                                       faci_bp_name_clean = faci_bp_name_clean,
                                       surg_sp_npi = path_sp_npi,
                                       surg_bp_npi = path_bp_npi,
                                       faci_sp_npi = faci_sp_npi,
                                       faci_bp_npi = faci_bp_npi
    ),
    .f=create_clean_sp_bp_names)
  )] %>%
    .[,`:=`(
      doctor_str = cleaned_names %>% map_chr(~.[[1]]),
      facility_str = cleaned_names %>% map_chr(~.[[2]]),
      doctor_npi_str = cleaned_names %>% map_chr(~.[[3]]),
      facility_npi_str = cleaned_names %>% map_chr(~.[[4]])

    )] %>%
    .[,.(
      tp_med_surg = median(surg_bun_sum_med),
      tp_med_medi = median(medi_bun_sum_med),
      tp_med_radi = median(radi_bun_sum_med),
      tp_med_path = median(path_bun_sum_med),
      tp_med_anes = median(anes_bun_sum_med),
      tp_med_faci = median(faci_bun_sum_med),

      tp_med_med = median(tp_med),
      tp_cnt_cnt = sum(cnt)
    ),by=c("facility_str", "facility_npi_str")] %>%
    .[, `:=`(
      num_fac = facility_str %>% map_int(count_number_provider),
      hospital_detects = facility_str %>% map_int(filter_strange_hosp_combo)
    )] %>%
    .[ hospital_detects < 2 ] %>%
    .[,most_important_fac := facility_str%>% map_chr(filter_out_most_important_facility)] %>%
    .[,most_important_fac_npi := pmap_chr(.l=list(most_important_fac, facility_str, facility_npi_str),
                                          .f=get_most_important_facility_npi)] %>%
    .[most_important_fac!="UNEVEN NPI-NAME SET"] %>%
    .[,most_important_fac_npi:= fifelse(most_important_fac_npi=="NOT SPECIFIED",
                                        "0",
                                        most_important_fac_npi) %>% as.numeric()
      ]%>%

    .[,`:=`(
      most_important_fac = most_important_fac %>% stri_trim_both(),
      most_important_fac_npi = most_important_fac_npi %>% stri_trim_both())] %>%
    .[,.(tp_med_med=median(tp_med_med),
         tp_med_surg = median(tp_med_surg),
         tp_med_medi = median(tp_med_medi),
         tp_med_radi = median(tp_med_radi),
         tp_med_path = median(tp_med_path),
         tp_med_anes = median(tp_med_anes),
         tp_med_faci = median(tp_med_faci),
         tp_cnt_cnt=sum(tp_cnt_cnt),
         most_important_fac_npi=max(most_important_fac_npi)
    ),
    by=list(
      most_important_fac
    )] %>%
    unique()

}