United States healthcare system capacity by provider

us_healthcare_capacity()

Value

a data.frame

Details

From the data providers:

Mapping existing and forecasted health system capacity gaps (beds, staffing, ventilators, supplies) to care for surging numbers of COVID19 patients (especially ICU-level care) at high spatiotemporal resolution (by facility, daily, all USA to start).

Examples

res = us_healthcare_capacity()
colnames(res)
#>  [1] "Name"                            "Hospital Type"                  
#>  [3] "Address"                         "Address_2"                      
#>  [5] "City"                            "State"                          
#>  [7] "Zipcode"                         "County"                         
#>  [9] "Latitude"                        "Longitude"                      
#> [11] "Staffed All Beds"                "Staffed ICU Beds"               
#> [13] "Licensed All Beds"               "All Bed Occupancy Rate"         
#> [15] "ICU Bed Occupancy Rate"          "Staffed All Beds - SOURCE"      
#> [17] "Staffed ICU Beds - SOURCE"       "Licensed All Beds - SOURCE"     
#> [19] "All Bed Occupancy Rate - SOURCE" "ICU Bed Occupancy Rate - SOURCE"
#> [21] "CCM_ID"                          "DH-ID"                          
#> [23] "HCRIS-ID"                        "HIFLD-ID"                       
dplyr::glimpse(res)
#> Rows: 7,154
#> Columns: 24
#> $ Name                              <chr> "IU HEALTH UNIVERSITY HOSPITAL", "HE…
#> $ `Hospital Type`                   <chr> "GENERAL ACUTE CARE", "REHABILITATIO…
#> $ Address                           <chr> "550 UNIVERSITY BLVD", "800 CUMMINGS…
#> $ Address_2                         <chr> "", "", "", "", "", "", "", "", "", …
#> $ City                              <chr> "INDIANAPOLIS", "BEVERLY", "HIGHLAND…
#> $ State                             <chr> "IN", "MA", "IL", "PR", "NJ", "NY", …
#> $ Zipcode                           <int> 46202, 1915, 62249, 676, 7701, 10993…
#> $ County                            <chr> "MARION", "ESSEX", "MADISON", "MOCA"…
#> $ Latitude                          <dbl> 39.77528, 42.56099, 38.75458, 18.390…
#> $ Longitude                         <dbl> -86.17656, -70.88724, -89.66760, -67…
#> $ `Staffed All Beds`                <dbl> NA, NA, NA, 106, 274, 155, NA, 161, …
#> $ `Staffed ICU Beds`                <dbl> NA, NA, NA, 7, 27, NA, NA, 11, 98, 0…
#> $ `Licensed All Beds`               <dbl> NA, 20, NA, 106, 468, 155, NA, 213, …
#> $ `All Bed Occupancy Rate`          <dbl> NA, NA, NA, 0.4900000, 0.5900000, NA…
#> $ `ICU Bed Occupancy Rate`          <dbl> NA, NA, NA, 0.73, 0.42, NA, NA, 0.52…
#> $ `Staffed All Beds - SOURCE`       <chr> "None", "None", "None", "HCRIS-Total…
#> $ `Staffed ICU Beds - SOURCE`       <chr> "None", "None", "None", "HCRIS-ICU T…
#> $ `Licensed All Beds - SOURCE`      <chr> "", "HIFLD-BEDS", "", "DH-NUM_LICENS…
#> $ `All Bed Occupancy Rate - SOURCE` <chr> "None", "None", "None", "HCRIS-Total…
#> $ `ICU Bed Occupancy Rate - SOURCE` <chr> "None", "None", "None", "HCRIS-ICU O…
#> $ CCM_ID                            <chr> "100", "10001915", "100062249", "100…
#> $ `DH-ID`                           <int> NA, NA, NA, 4294, 2512, 2695, 2705, …
#> $ `HCRIS-ID`                        <int> NA, NA, NA, 400111, 310034, 330405, …
#> $ `HIFLD-ID`                        <dbl> 100, 10001915, 100062249, 1000676, 1…