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healthyR.data

CRAN_Status_Badge Lifecycle: stable PRs Welcome

The goal of the { healthyR.data } package is to provide a simple yet feature rich administrative data-set allowing for the testing of functions inside of the { healthyR } package. It can be used to test its functions or any function you create.

Installation

You can install the released version of healthyR.data from CRAN with:

install.packages("healthyR.data")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("spsanderson/healthyR.data")

Example

This is a basic example which shows you how to solve a common problem:

library(healthyR.data)
library(dplyr)

df <- healthyR_data

glimpse(df)
#> Rows: 187,721
#> Columns: 17
#> $ mrn                      <chr> "86069614", "60856527", "80673110", "55897373…
#> $ visit_id                 <chr> "3519249247", "3602225015", "3125290892", "38…
#> $ visit_start_date_time    <dttm> 2010-01-04 05:00:00, 2010-01-04 05:00:00, 20…
#> $ visit_end_date_time      <dttm> 2010-01-04, 2010-01-04, 2010-01-04, 2010-01-…
#> $ total_charge_amount      <dbl> 25983.88, 22774.05, 10690.45, 8788.02, 7325.1…
#> $ total_amount_due         <dbl> 0.00, 0.00, 0.00, 0.00, 0.00, 201.52, 20.00, …
#> $ total_adjustment_amount  <dbl> -20799.61, -12978.37, -7596.09, -7663.57, -60…
#> $ payer_grouping           <chr> "Medicare B", "Medicare HMO", "HMO", "Medicar…
#> $ total_payment_amount     <dbl> -5184.27, -9795.68, -3094.36, -1124.45, -1269…
#> $ ip_op_flag               <chr> "O", "O", "O", "O", "O", "O", "O", "O", "O", …
#> $ service_line             <chr> "General Outpatient", "General Outpatient", "…
#> $ length_of_stay           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ expected_length_of_stay  <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
#> $ length_of_stay_threshold <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…
#> $ los_outlier_flag         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ readmit_flag             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
#> $ readmit_expectation      <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, N…

df %>% 
    count(ip_op_flag, service_line) %>%
    arrange(ip_op_flag, desc(n)) %>%
    rename(count = n)
#> # A tibble: 30 × 3
#>    ip_op_flag service_line                                 count
#>    <chr>      <chr>                                        <int>
#>  1 I          Medical                                      64435
#>  2 I          Surgical                                     14916
#>  3 I          COPD                                          4398
#>  4 I          CHF                                           3871
#>  5 I          Pneumonia                                     3323
#>  6 I          Cellulitis                                    3311
#>  7 I          Major Depression/Bipolar Affective Disorders  2866
#>  8 I          Chest Pain                                    2766
#>  9 I          GI Hemorrhage                                 2404
#> 10 I          MI                                            2253
#> # ℹ 20 more rows

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.