R6 class storing health statistics for a single hospital.

R6 class storing health statistics for a single hospital.

R6 class storing health statistics for a single hospital.

Details

This R6 class is designed to store bed occupancy statistics for a single hospital location. This class can be used to plot summary statistics and create shiny UI/server objects.

Super class

HealthDataScotland::health_unit -> hospital

Methods

Public methods

• hospital$available_plots()

• hospital$plot()

• hospital$plot_data()

• hospital$plot_info()

• hospital$ui()

• hospital$server()

• hospital$clone()

Inherited methods

• HealthDataScotland::health_unit$ID()
• HealthDataScotland::health_unit$address()
• HealthDataScotland::health_unit$combine_data()
• HealthDataScotland::health_unit$data()
• HealthDataScotland::health_unit$health_board()
• HealthDataScotland::health_unit$initialize()
• HealthDataScotland::health_unit$metadata()
• HealthDataScotland::health_unit$popup_modal()
• HealthDataScotland::health_unit$title()
• HealthDataScotland::health_unit$validate()

---

Method available_plots()

Get character vector of available plots for hospital grp

Usage

hospital$available_plots()

---

Method plot()

Plot hospital unit.

Usage

hospital$plot(type, ...)

Arguments

type

(character(1))
Character specifying plot type. See available_plots for options.

...

Passed to plot functions.

Examples

x <- example_hospital_unit()
x[["plot"]](type = "specialty_line", data_type = "annual")

---

Method plot_data()

Generate plot data for hospital unit.

Usage

hospital$plot_data(type, ...)

Arguments

type

(character(1))
Character specifying plot type. See available_plots for options.

...

Passed to plot data functions.

Examples

x <- example_hospital_unit()
x[["plot_data"]](type = "specialty_line", data_type = "annual")

---

Method plot_info()

Get plot info for hospital unit.

Usage

hospital$plot_info(type, ...)

Arguments

type

(character(1))
Character specifying plot type. See available_plots for options.

...

Passed to plot info functions.

Examples

x <- example_hospital_unit()
x[["plot_info"]](type = "specialty_line", data_type = "annual")

---

Method ui()

Create UI for hospital object.

Usage

hospital$ui(ns)

Arguments

ns

Namespace of shiny application page.

---

Method server()

Create server for hospital object.

Usage

hospital$server()

---

Method clone()

The objects of this class are cloneable with this method.

Usage

hospital$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

library(dplyr)
meta <- HealthDataScotland::example_hospital_metadata |>
  rename("ID" = "HospitalCode", "HBName" = "HealthBoard") |>
  filter(.data[["ID"]] == "A101H")
data <- HealthDataScotland::example_hospital_data |>
  rename("ID" = "Location") |>
  filter(.data[["ID"]] == "A101H")
x <- hospital[["new"]](meta, data)
x[["ID"]]()
#> [1] "A101H"
x[["title"]]()
#> [1] "Arran War Memorial Hospital"
x[["address"]]()
#> [1] "Lamlash, Isle of Arran, KA278LF"
x[["health_board"]]()
#> [1] "S08000015"
x[["metadata"]]()
#> # A tibble: 1 × 16
#>   datasetID          ID    HospitalName AddressLine1 AddressLine2 AddressLine2QF
#>   <chr>              <chr> <chr>        <chr>        <chr>        <chr>         
#> 1 c698f450-eeed-41a… A101H Arran War M… Lamlash      Isle of Arr… NA            
#> # ℹ 10 more variables: AddressLine3 <chr>, AddressLine3QF <chr>,
#> #   AddressLine4 <chr>, AddressLine4QF <chr>, Postcode <chr>, HBName <chr>,
#> #   HSCP <chr>, CouncilArea <chr>, IntermediateZone <chr>, DataZone <chr>
x[["data"]]()
#> # A tibble: 21 × 23
#>    datasetID          FinancialYear FinancialYearQF HB    HBQF  ID    LocationQF
#>    <chr>              <chr>         <chr>           <chr> <chr> <chr> <chr>     
#>  1 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  2 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  3 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  4 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  5 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  6 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  7 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  8 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#>  9 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#> 10 d719af13-5fb3-430… 2022/23       NA              S080… NA    A101H NA        
#> # ℹ 11 more rows
#> # ℹ 16 more variables: Specialty <chr>, SpecialtyQF <chr>, SpecialtyName <chr>,
#> #   SpecialtyNameQF <chr>, SpecialtyGrouping <chr>, SpecialtyGroupingQF <chr>,
#> #   AverageAvailableStaffedBeds <dbl>, AverageAvailableStaffedBedsQF <chr>,
#> #   PercentageOccupancy <dbl>, PercentageOccupancyQF <chr>,
#> #   AllStaffedBeds <dbl>, AllStaffedBedsQF <chr>, AverageOccupiedBeds <dbl>,
#> #   AverageOccupiedBedsQF <chr>, TotalOccupiedBeds <dbl>, …
x[["plot"]](type = "specialty_line")

  

  

    

      

      
  
x[["plot_data"]](type = "specialty_line")
#> # A tibble: 4 × 7
#>   ID    FinancialYear HospitalName SpecialtyName PercentageOccupancy name  value
#>   <chr> <chr>         <chr>        <chr>                       <dbl> <chr> <dbl>
#> 1 A101H 2022/23       Arran War M… All Specialt…                77.4 Annu…  3263
#> 2 A101H 2022/23       Arran War M… All Specialt…                77.4 Annu…  2526
#> 3 A101H 2023/24       Arran War M… All Specialt…                68.5 Annu…  3631
#> 4 A101H 2023/24       Arran War M… All Specialt…                68.5 Annu…  2488
x[["plot_info"]](type = "specialty_line")
#> [1] "This line chart shows the annual number of\n                    available staffed beds and the number occupied (y-axis)\n                    across time (x-axis). Settings can be used to show data for\n                    different specialties (default is all specialities)."
if (FALSE) { # \dontrun{
x[["ui"]]()
x[["server"]]()
} # }

## ------------------------------------------------
## Method `hospital$plot`
## ------------------------------------------------

x <- example_hospital_unit()
x[["plot"]](type = "specialty_line", data_type = "annual")

  

  

    

      

      
  

## ------------------------------------------------
## Method `hospital$plot_data`
## ------------------------------------------------

x <- example_hospital_unit()
x[["plot_data"]](type = "specialty_line", data_type = "annual")
#> # A tibble: 4 × 7
#>   ID    FinancialYear HospitalName SpecialtyName PercentageOccupancy name  value
#>   <chr> <chr>         <chr>        <chr>                       <dbl> <chr> <dbl>
#> 1 A101H 2022/23       Arran War M… All Specialt…                77.4 Annu…  3263
#> 2 A101H 2022/23       Arran War M… All Specialt…                77.4 Annu…  2526
#> 3 A101H 2023/24       Arran War M… All Specialt…                68.5 Annu…  3631
#> 4 A101H 2023/24       Arran War M… All Specialt…                68.5 Annu…  2488

## ------------------------------------------------
## Method `hospital$plot_info`
## ------------------------------------------------

x <- example_hospital_unit()
x[["plot_info"]](type = "specialty_line", data_type = "annual")
#> [1] "This line chart shows the annual number of\n                    available staffed beds and the number occupied (y-axis)\n                    across time (x-axis). Settings can be used to show data for\n                    different specialties (default is all specialities)."