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app.R
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app.R
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# Shiny app for aggregate distributional cost-effectiveness analysis tool
#
# Created by:
# James Love-Koh
# 22/10/2020
# Adapted by:
# Paul Schneider
# 22/09/2022
# Loading packages
library(shiny)
library(shinydashboard)
library(shinyWidgets)
library(shinybusy)
library(rintrojs)
library(tidyverse)
library(ggrepel)
library(highcharter)
library(DT)
library(knitr)
library(markdown)
library(shinyjs)
library(shinycssloaders)
# Source functions
source("functions_revised.R")
source("ui_elements.R")
source("report_functions.R")
# Toggle DEV_MODE
HIDE_LOADING_SCREEN = F
# rename highchart donwload btn
lang <- getOption("highcharter.lang")
lang$contextButtonTitle <- "Download"
options(highcharter.lang = lang)
# IMD 1-5 color pallette
imdCols = function(){
viridis_pal(begin = 0.3, end = 0.8,option = "magma")(5)
}
# UI -------
ui = dashboardPage(
# HEADER ----
dashboardHeader(
# left header title
title = div(
tags$img(src="york_mini.png",width="35px"), # Uni logo
"Health Equity Impact Calculator",
),
titleWidth = "320px",
# right header menu
tags$li(
class = "dropdown pe-5 text-white fw-bold d-flex",
div(
class = "me-3",
icon("info-circle", verify_fa = FALSE),
actionLink("showAbout","About",class="text-white")
),
div(
class = "me-3",
icon("book"),
actionLink("showReferences","References",class="text-white")
),
# tags$div(
# icon("question-circle", verify_fa = FALSE),
# actionLink("tutorial_start","Watch the tutorial",class="text-white")
# )
)
),
# SIDEBAR ----
dashboardSidebar(
width = "300px",
collapsed = F,
sidebarMenu(
id = "tabs",
# *tab 1: Intervention -----
menuItem(
tabName = "intervention",
"Intervention",
startExpanded=T,
textInput("intName1", "Intervention",NULL,placeholder = "E.g. Smoking prevention"),
textInput("compName1", "Comparator",NULL,placeholder = "E.g. No intervention"),
selectInput(
"intervention_type","Population type",
c("Risk factor population","Disease population")
),
conditionalPanel(
condition="input.intervention_type=='Disease population'",
selectizeInput(
"intICD", "ICD code(s)",
choices = NULL,
multiple=TRUE
),
sliderInput(
"age_range","Recipient age range",
value = c(0, 100),
step=1, min = 0, max = 100
),
),
conditionalPanel(
condition="input.intervention_type=='Risk factor population'",
checkboxGroupInput(
"intRF",
div(class="mb-2", "Risk factor(s)"),
unique(distRF$risk_factor),
selected = "Smoking"
)
),
shinyWidgets::autonumericInput(
inputId = "intPop_c1",
label = div(tip("Target population size",tipId = "elig_pop_text"),class="mb-1"),
value = 10,
decimalPlaces = 0,
),
shinyWidgets::prettySwitch(
"enable_intPop_c1",
label = span(class ="small", "Set custom population size"),
value = F,status = "warning"
)
),
# *tab 2: CEA inputs -----
menuItem(
tabName = "cea",
id = "cea-tab",
introBox("CEA inputs",
data.step = 4, data.intro = "Fourth step of the intro",data.position = "right"
),
autonumericInput("incQALYs_c1", "Inc. QALYs per recipient", 0.02, currencySymbol = "",decimalPlaces = 5),
autonumericInput("incCost_c1", "Inc. costs per recipient", 200, currencySymbol = "£",decimalPlaces = 0),
div(
class = "px-3 mt-3",
introBox(
div(
class = "mb-1",
"Resulting ICER:",
),
data.step = 5, data.intro = "Fifth step of the intro", data.position = "right"
),
div(
class = "text-dark w-100 card px-2 py-2 text-center fw-bold",
style = "cursor: not-allowed; background-color: #aaaaaa",
textOutput("icer_text",inline = T))
)
),
# *tab 3: Eligiblity -------
menuItem(
tabName = "eligiblity",
id = "eligiblity-tab",
"Eligiblity",
introBox(
data.step = 6, data.intro = "Sixth step of the intro", data.position = "right",
div(
class = "no-lab-sliders-group mb-3",
div(class="d-flex align-items-end pe-3", sliderInput("prevQ1", "IMD 1 (Most deprived)",0.5,min=0,max=1,step=0.01,ticks = F),div(class="pb-1 fw-bold text-decoration-underline",textOutput("prevQ1Compt"))),
div(class="d-flex align-items-end pe-3", sliderInput("prevQ2", "IMD2",0.5,min=0,max=1,step=0.01,ticks = F),div(class="pb-1 fw-bold text-decoration-underline",textOutput("prevQ2Compt"))),
div(class="d-flex align-items-end pe-3", sliderInput("prevQ3", "IMD3",0.5,min=0,max=1,step=0.01,ticks = F),div(class="pb-1 fw-bold text-decoration-underline",textOutput("prevQ3Compt"))),
div(class="d-flex align-items-end pe-3", sliderInput("prevQ4", "IMD4",0.5,min=0,max=1,step=0.01,ticks = F),div(class="pb-1 fw-bold text-decoration-underline",textOutput("prevQ4Compt"))),
div(class="d-flex align-items-end pe-3", sliderInput("prevQ5", "IMD5 (Least deprived)",0.5,min=0,max=1,step=0.01,ticks = F),div(class="pb-1 fw-bold text-decoration-underline",textOutput("prevQ5Compt"))),
shinyWidgets::prettySwitch("choiceRecPop",label = span(class ="small", "Set custom population shares"),value = F,status = "warning"),
)
)
),
# *tab 4: Distributional inputs tab ----
menuItem(
tabName = "uptake",
"Uptake",
div(
id="util-sliders-group",
class = "no-lab-sliders-group",
div(
class="d-flex align-items-end pe-1",
sliderInput("util1Q1", "IMD 1 (Most deprived)",100,min=0,step=0.1,max=100,ticks = F),
div(class="no-padding w-50",autonumericInput("util1Q1_num",NULL,100,minimumValue = 0, maximumValue = 100,currencySymbol = "%",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("util1Q2", "IMD 2",100,min=0,step=0.1,max=100,ticks = F),
div(class="no-padding w-50",autonumericInput("util1Q2_num",NULL,100,minimumValue = 0, maximumValue = 100,currencySymbol = "%",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("util1Q3", "IMD 3",100,min=0,step=0.1,max=100,ticks = F),
div(class="no-padding w-50",autonumericInput("util1Q3_num",NULL,100,minimumValue = 0, maximumValue = 100,currencySymbol = "%",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("util1Q4", "IMD 4",100,min=0,step=0.1,max=100,ticks = F),
div(class="no-padding w-50",autonumericInput("util1Q4_num",NULL,100,minimumValue = 0, maximumValue = 100,currencySymbol = "%",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("util1Q5", "IMD 5 (Least deprived)",100,min=0,step=0.1,max=100,ticks = F),
div(class="no-padding w-50",autonumericInput("util1Q5_num",NULL,100,minimumValue = 0, maximumValue = 100,currencySymbol = "%",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class = "px-3 mt-3",
div(
class = "mb-1",
"Total uptake:", ),
div(
class = "text-dark w-100 card px-2 py-2 text-center fw-bold",
style = "cursor: not-allowed; background-color: #aaaaaa",
textOutput("rec_pop_text1",inline = T))
),
div(class="text-center pe-2 small text-secondary",
textOutput("rec_pop_text2",inline = T)
)
)
),
# *tab 5: health effect tab -----
menuItem(
tabName = "effectiveness",
"Effectiveness",
div(
class = "no-lab-sliders-group",
div(
class="d-flex align-items-end pe-1",
sliderInput("qaly1Q1", "IMD 1 (Most deprived)",1,min=0,step=0.25,max=5,ticks = F),
div(class="no-padding w-50",autonumericInput("qaly1Q1_num",NULL,1,minimumValue = 0, maximumValue = 5,currencySymbol = "x",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("qaly1Q2", "IMD 2",1,min=0,step=0.1,max=5,ticks = F),
div(class="no-padding w-50",autonumericInput("qaly1Q2_num",NULL,1,minimumValue = 0, maximumValue = 5,currencySymbol = "x",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("qaly1Q3", "IMD 3",1,min=0,step=0.1,max=5,ticks = F),
div(class="no-padding w-50",autonumericInput("qaly1Q3_num",NULL,1,minimumValue = 0, maximumValue = 5,currencySymbol = "x",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("qaly1Q4", "IMD 4",1,min=0,step=0.1,max=5,ticks = F),
div(class="no-padding w-50",autonumericInput("qaly1Q4_num",NULL,1,minimumValue = 0, maximumValue = 5,currencySymbol = "x",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
div(
class="d-flex align-items-end pe-1",
sliderInput("qaly1Q5", "IMD 5 (Least deprived)",1,min=0,step=0.1,max=5,ticks = F),
div(class="no-padding w-50",autonumericInput("qaly1Q5_num",NULL,1,minimumValue = 0, maximumValue = 5,currencySymbol = "x",decimalPlaces = 1, currencySymbolPlacement = "s", width = "100%")),
),
),
div(
class = "px-3 mt-3",
div(
class = "mb-1",
"Average QALY gain/recipient:", ),
div(
class = "text-dark w-100 card px-2 py-2 text-center fw-bold",
style = "cursor: not-allowed; background-color: #aaaaaa",
textOutput("wt_qaly_text1",inline = T))
),
div(class="text-start pe-2 small text-secondary text-wrap lh-1 pt-2 ps-3 pe-4",
textOutput("wt_qaly_text2",inline = T)
)
),
# *tab 6: opportunity costs tab -----
menuItem(
tabName = "opportunity",
"Opportunity costs",
autonumericInput(
inputId = "ratioHOC",
label = tip("Marginal productivity (£/QALY)",tip = "Marginal cost of producing a QALY from alternative resource use"),
value = 15000,
min=0,
currencySymbol = "£",
decimalPlaces = 0
),
selectInput(
"choiceHOC", "Health opportunity gradient:",
c("Flat" = "flat","Moderate gradient" = "moderate","Steep gradient" = "steep")
),
div(class="pe-3", highchartOutput("disthoc_plot",height="200px",width="100%")),
div(
class= "pe-3 ps-2 pt-1 text-wrap text-secondary lh-1",
style = "font-size: 80%",
textOutput("hoc_user_warning",inline = T),)
),
hr(),
# *run btn ------
actionButton("run","Run Scenario",class="btn btn-custom px-5 mx-auto mt-3 fs-5 "),
# *download btn ------
div(
class = "px-5",
# proxy triggers download (avoids some bugs)
actionButton("report_download_proxy","Download Report",icon = shiny::icon("download"), class = "btn-custom mt-2 fs-6 py-1"),
# hidden download button
downloadButton("report_download","", icon = NULL, style = "width: 0; height:1; position: absolute !important; z-index: -1 !important; top:-10px;"),
)
)
),
# BODY -----
dashboardBody(
# *misc ui and styling ----
# use bootstrap 5 sintead of shiny default 4
suppressDependencies("bootstrap"),
tags$script(
src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js",
integrity="sha384-MrcW6ZMFYlzcLA8Nl+NtUVF0sA7MsXsP1UyJoMp4YLEuNSfAP+JcXn/tWtIaxVXM",
crossorigin="anonymous"
),
tags$link(
href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css",
rel="stylesheet",
integrity="sha384-EVSTQN3/azprG1Anm3QDgpJLIm9Nao0Yz1ztcQTwFspd3yD65VohhpuuCOmLASjC",
crossorigin="anonymous"
),
tags$link(
href="https://cdn.datatables.net/1.12.1/css/jquery.dataTables.min.css",
rel="stylesheet",
crossorigin="anonymous"
),
# g-tag
if(file.exists("www/google_analytics.html")){tags$head(tags$head(includeHTML("www/google_analytics.html")))},
# add york favicon
tags$head(tags$link(rel="shortcut icon", href="york_mini.png")),
# add custom styling css
includeCSS("style.css"),
# use shinyjs
useShinyjs(),
# loading spinner while report is being built
use_busy_spinner(
spin_id = "report_spinner",
spin = "self-building-square",
color = "#cb3e72",
position = "full-page",
width = "250px"
),
# loading screen
if(!HIDE_LOADING_SCREEN){
loadingScreenUi()
},
# *Main ----
fluidRow(
column(
width = 12,
class = "d-flex flex-wrap flex-sm-wrap flex-md-wrap flex-lg-wrap flex-xl-nowrap justify-content-center align-items-start mx-auto px-3",
style = "max-width: 1500px;",
# not ran yet? -> hide cards, show prompts
conditionalPanel(
"input.run===0",
id="click-prompt",
class = "d-flex",
style = "position: absolute; height: 75vh; width: calc(100vw - 300px);",
div(
class = "d-flex flex-column justify-content-center mx-auto my-auto",
div(
class="w-100 text-secondary fw-bold fs-4 px-5 mx-auto text-start my-auto pb-5",
tags$p("1 Click 'Run Scenario' to assess the health equity impact."),
tags$p("2 Update input parameters."),
tags$p("3 Click on 'Run Scenario' again to see updated results.")
)
),
),
# *card 1 -----
div(
id="card-1",
class = "card shadow-lg mx-1 mx-sm-1 mx-md-1 mx-lg-3 my-2",
style ="min-width: 400px; max-width: 750px; width: 100%;",
div(
class = "card-header text-white card-title fs-5",
style = "background-color: var(--primary)",
"Distributional health impact",
),
div(
class = "d-flex flex-column card-body",
div(
class = "d-flex flex-column",
div(
class ="d-flex mt-1 mb-4 border-bottom px-2 pb-3 fs-5",
div(
class="fw-bold me-3 ms-1",
tip(
str = "Net health inequality",
tip = "The impact on the inequality gap in healthy years lived between the most and least
deprived fifths of the English population. More specifically, the value represents the
modelled difference in net QALY benefit between the most and least deprived IMD group
at population level. The measure differs from the observed gap by
incorporating information on the net QALY benefits of IMD2-IMD4 using
a simple linear regression model. The current English health inequality gap is about
130 million healthy years (based on an average gap in health-adjusted life expectancy of
about 13 times a population of about 10 million)."),
"benefit:"),
div(
class = "fw-bold text-center custom-col",
textOutput("sii",inline = T), "QALYs")
),
div(
class="d-flex",
div(class="ms-auto pe-2 fw-bold flex-shrink-0 align-bottom","Select plot:"),
selectInput(
"netbenefit_plot_type",
label = NULL,
width = "100%",
choices = c(
"Eligible population",
"Uptake rate",
"Incremental QALYs/recipient",
"Share of opportunity costs",
"Proportion of recipients",
"Number of recipients",
"Intervention benefit",
"Intervention opportunity costs",
"Net health benefit"
),
selected = "Net health benefit"
)
),
shinycssloaders::withSpinner(
type = 2,
color.background = "white",
color = "#cb3e72",
highchartOutput("netbenefit_plot"),
),
),
div(
style="overflow-x: scroll;",
shinycssloaders::withSpinner(
type = 2,
color.background = "white",
color = "#cb3e72",
dataTableOutput("netbenefit_table",)
)
),
),
),
# *card 2 -----
div(
id="card-2",
class = "card shadow-lg mx-1 mx-sm-1 mx-md-1 mx-lg-3 my-2",
style ="min-width: 400px; max-width: 750px; width: 100%;",
div(
class = "card-header text-white card-title fs-5",
style = "background-color: var(--primary)",
"Equity & efficiency",
),
div(
class = "d-flex flex-column card-body",
style = "min-width: 350px; flex-start: 48%; max-width: 750px;",
div(class="w-100 border-bottom mb-3 pb-3 d-flex",
div(
class="px-1 mx-auto w-100", style = "max-width: 600px;",
tags$table(
class = "equity-table ",
tags$colgroup(
tags$col(span=1, width = "70%"),
tags$col(span=1, width = "30%"),
),
tags$tr(
tags$td(tip("Decision threshold","Threshold cost per QALY gained for considering the intervention cost-effective")),
tags$td(
div(
class="d-flex px-3 mx-auto align-items-center justify-content-center",
actionButton("eip_threshold_minus","-",class="btn-custom-outline"),
autonumericInput(
"eip_threshold",label = NULL,
value = 30000, min = 0, max = 500000,
step = 1000, width = "80px",
currencySymbol = "£", decimalPlaces = 0
),
actionButton("eip_threshold_plus","+",class="btn-custom-outline"),
)
)
),
tags$tr(
tags$td(tip("Atkinson inequality aversion", tipId = "implicit_weight")),
tags$td(
div(
class="d-flex px-3 mx-auto align-items-center justify-content-center",
actionButton("eip_aversion_minus","-",class="btn-custom-outline"),
autonumericInput(
"eip_aversion",label = NULL,
value = 10, min = 0, max = 20,
step = 0.5, width = "80px",
readOnly = T
),
actionButton("eip_aversion_plus","+",class="btn-custom-outline"),
),
)),
tags$tr(
style = "height: 20px;",
tags$td(class="fw-bold", "Naive estimates:")
),
tags$tr(
tags$td(class="ps-4",tip("ICER", "Incremental cost-effectiveness ratio")),
tags$td(class = "text-center", textOutput("icer_text2",inline = T))
),
tags$tr(
tags$td(class="ps-4",tip("INMB/recipient:", "Incremental net monetary benefit per recipient")),
tags$td(class = "text-center", textOutput("inmb_text",inline = T))
),
tags$tr(
tags$td(class="ps-4",tip(
str = "INHB",
tip = "Incremental Net Health Benefit (INHB) - the total gain in healthy years across the whole English population."
)),
tags$td(class = "text-center", textOutput("nhb",inline = T), "QALYs")
),
tags$tr(
style = "height: 20px;",
tags$td(class="fw-bold", "Equity-weighted estimates:")
),
tags$tr(
tags$td(class="ps-4",tip("Weighted ICER", "Equity-weighted incremental cost-effectiveness ratio")),
tags$td(class = "text-center", textOutput("weighted_icer",inline = T))
),
tags$tr(
tags$td(class="ps-4",tip("Weighted INMB/recipient:", "Equity-weighted incremental net monetary benefit per recipient")),
tags$td(class = "text-center", textOutput("weighted_inmb", inline = T))
),
tags$tr(
tags$td(class="ps-4",tip("Weighted INHB:", "Equity-weighted population-level incremental net health benefit")),
tags$td(class = "text-center", textOutput("weighted_inhb", inline = T))
),
),
),
),
div(
class="d-flex",
div(class="ms-auto pe-2 fw-bold flex-shrink-0 align-bottom","Select plot:"),
selectInput(
"icer_plane_type",
label = NULL,width = "100%",
choices = c(
"Equity - ICER trade-off " = "icer_equityimpact_plot",
"Equity - net health impact trade-off" = "equityimpact_plot",
"CE-plane " = "ce_plane"
),
selected = "icer_equityimpact_plot"
),
),
shinycssloaders::withSpinner(
type = 2,
color.background = "white",
color = "#cb3e72",
highchartOutput("plane_plot",height = "500px"),
),
textOutput("raw_icer_text"),
),
),
),
),
),
title = "DCEA app"
)
# _ -----
server = function(input, output, session){
# JS UI SETUP -----
# *circle progress bar ----
update_progress(shiny_id = "progress-circle",value = 1)
runjs("setTimeout(()=>{
let el = document.querySelector('#landing-div');
if(el === null) return;
el.style.opacity = 0;
setTimeout(() => {
el.parentNode.removeChild(el);
}, 1000);
},3200)")
# *hide cards at start if no model is ran -----
runjs("
document.querySelector('#card-1').style.visibility = 'hidden';
document.querySelector('#card-2').style.visibility = 'hidden';
")
# *activate tooltips -----
runjs("
var tooltipTriggerList = [].slice.call(document.querySelectorAll('[data-bs-toggle=\"tooltip\"]'))
var tooltipList = tooltipTriggerList.map(function (tooltipTriggerEl) {
return new bootstrap.Tooltip(tooltipTriggerEl)
})")
# *download button for highcharter ----
runjs("
Highcharts.SVGRenderer.prototype.symbols.download = (x, y, w, h) => {
return ['M', x + w * 0.5, y,'L', x + w * 0.5, y + h * 0.7,'M', x + w * 0.3, y + h * 0.5,'L', x + w * 0.5, y + h * 0.7,'L', x + w * 0.7, y + h * 0.5,'M', x, y + h * 0.9,'L', x, y + h,'L', x + w, y + h,'L', x + w, y + h * 0.9];
};
")
# *avoid line break in sidebar slider input label ----
# for some reason css setting has no effect on label?
runjs("document.querySelector('#util1Q5-label').style.whiteSpace = 'nowrap'")
runjs("document.querySelector('#qaly1Q5-label').style.whiteSpace = 'nowrap'")
# *server side rendering of selectize ----
updateSelectizeInput(
session,
'intICD',
choices = icd10_input_labs,
server = TRUE,
)
observe({
popR = sum(recipients_table_raw1()$recipients_util)
popRfrmt = formatC(popR, digits = 0, format = "f", big.mark = ",")
popE = sum(resCEA()$pop)
popEfrmt = formatC(popE, digits = 0, format = "f", big.mark = ",")
output$rec_pop_text1 <- renderText({
paste0(round((popR/popE)*100,0) ,"%")
})
output$rec_pop_text2 <- renderText({
paste0("(",popRfrmt," / ",popEfrmt,")")
})
})
# Input summary table ------------------------------------------------------
distIncQALY <- reactive({
qaly_dist(resCEA(),distQALYeffect())
})
# Non-output version for Markdown report
input_summary_table <- reactive({
table_inputSummary(distPrev(),distUtil1(),distIncQALY(),distHOC())
})
# Recipient distribution tables and plots ---------------------------------
# Raw tables for each uptake scenario
recipients_table_raw1 = reactive({
table_recipients_raw(distPrev(),distUtil1(),resCEA())
})
recipients_table_raw2 = reactive({
table_recipients_raw(distPrev(),distUtil2(),resCEA())
})
# _-----
# RUN { -----
netbenefit_table_raw1 = eventReactive(input$run, ignoreNULL = F, {
isolate(table_netbenefit_raw(recipients_table_raw1(),distHOC(),input$ratioHOC,
distQALYeffect(),resCEA()))
})
netbenefit_table_raw2 = eventReactive(input$run, ignoreNULL = F, {
isolate(table_netbenefit_raw(recipients_table_raw2(),distHOC(),input$ratioHOC,
distQALYeffect(),resCEA()))
})
weightedicer_raw = eventReactive(input$run, ignoreNULL = F, {
table_weightedicer_raw(netbenefit_table_raw1(),netbenefit_table_raw2(),
input$ratioHOC,imp_AtWeights_full)
})
healthdistribution_table_raw1 = eventReactive(input$run, ignoreNULL = F, {
table_healthdistribution_raw(netbenefit_table_raw1())
})
healthdistribution_table_raw2 = eventReactive(input$run, ignoreNULL = F, {
table_healthdistribution_raw(netbenefit_table_raw2())
})
inequality_table_raw1 = eventReactive(input$run, ignoreNULL = F, {
table_inequality_raw(healthdistribution_table_raw1(),
resCEA(),input$ratioHOC)
})
inequality_table_raw2 = eventReactive(input$run, ignoreNULL = F, {
table_inequality_raw(healthdistribution_table_raw2(),
resCEA(),input$ratioHOC)
})
inequality_table1 = eventReactive(input$run, ignoreNULL = F, {
table_inequality(inequality_table_raw1())
})
inequality_table2 = eventReactive(input$run, ignoreNULL = F, {
table_inequality(inequality_table_raw2())
})
intName = eventReactive(input$run, ignoreNULL = F, {
if(input$intName1 == ""){"Smoking Prevention"} else {input$intName1}
})
compName = eventReactive(input$run, ignoreNULL = F, {
if(input$compName1 == ""){"No Intervention"} else {input$compName1}
})
observeEvent(input$run, ignoreNULL = F, priority = 4,{
# checks fun if running os allowed
if(input$run>0){
runjs("
document.querySelector('#card-1').style.visibility = 'visible';
document.querySelector('#card-2').style.visibility = 'visible';
document.querySelector('#click-prompt').remove();
")
}
R$scenario = "" # isolate(input$scenario_counter)
output$intName_txt = renderText(intName())
output$noEIP_text <- renderText({
if(indicatorICER()==1) { paste0("",sep="") }
else { paste0("This plot is only produced when the incremental QALYs
and costs for an intervention are positive.") }
})
# Raw ICER warning
output$raw_icer_text <- renderText({
if(baseICER()=="dominant") {
paste0("Warning: Interpret the ICER with caution as the intervention dominates the comparator")
} else if(baseICER()=="dominated") {
paste0("Warning: Interpret the ICER with caution as the intervention is dominated by the comparator")
} else {
paste0("")
}
})
output$nhb = renderText({
nhb = isolate(table_netbenefit(netbenefit_table_raw1()))
formatC(as.numeric(nhb[3,"Total"]),digits = 0,format = "f",big.mark = "," )
})
output$sii = renderText({
formatC(as.numeric(isolate(inequality_table_nb_raw1()$Value[1])),digits = 0,format = "f",big.mark = "," )
})
# ICER for results
R$baseICER = isolate(baseICER())
output$icer_text2 <- renderText({
if(R$baseICER=="dominant") {
paste0("Dominating")
} else if(R$baseICER=="dominated") {
paste0("Dominated")
} else {
paste0("£",R$baseICER,"/QALY")
}
})
# for inmb
R$incC = input$incCost_c1
R$incQ = input$incQALYs_c1
# prepare distributional health impact table
table_inputs = isolate(table_inputSummary(distPrev(),distUtil1(),distIncQALY(),distHOC()))
names(table_inputs)[1] = "x"
table = cbind(table_inputs,"Total" = c(1,NA,NA,1))
table_ext = isolate(table_recipients(recipients_table_raw1()))
names(table_ext)[1] = "x"
table = rbind(table, table_ext)
table_outcomes = isolate(table_netbenefit(netbenefit_table_raw1()))
names(table_outcomes)[1] = "x"
table = rbind(table, table_outcomes)
names(table)[1] = ""
R$dhi_table = table
# Net benefit tab --
output$netbenefit_table =renderDataTable(server = F, {
if(input$run == 0){return(NULL)}
# messy reformatting
table = reformatNBT(table)
R$final_dtbl = table
# styling
borderStyle <- "value == 'T' ? 'double black' : value != 'white' ? '' : 'white'"
class(borderStyle) <- "JS_EVAL"
bgStyle = "value == 'T' ? 'bold' : value != '' ? '' : ''"
class(bgStyle) <- "JS_EVAL"
datatable(
table,
extensions = 'Buttons',
style = 'bootstrap',
class = "hover compact",
rownames = FALSE,
options = list(
dom = 'frtipB',
buttons = c('copy', 'csv', 'excel', 'pdf'),
paging=F,searching=F,info=F,ordering=F,
columnDefs = list(list(visible=FALSE, targets=c(7,8)))
)
) %>%
formatStyle("s1", target = 'row', border = borderStyle) %>%
formatStyle("s2", target = 'row', fontWeight = bgStyle)
})
inequality_table = table_inequality_comb(
isolate(inequality_table1()),
isolate(inequality_table2()),
F # input$choiceUptake2
)
output$siai_reduction = renderText(formatC(inequality_table$Value[1],digits=6,format = "f"))
output$rii_reduction = renderText(formatC(inequality_table$Value[2],digits=6,format = "f"))
output$ci_reduction = renderText(formatC(inequality_table$Value[3],digits=6,format = "f"))
Sys.sleep(0.5)
if(R$trigger_download){
R$trigger_download = F
runjs("document.getElementById('report_download').click();")
}
}) # } -----
# _-----
# REACTIVE VALS STORE ----
R <- reactiveValues(
old_atkinson=NULL,
old_atkinson_icer=NULL,
run = 0,
scenario=NULL,
trigger_download = F
)
# Recipient pop statements
popRec1 <- reactive({
format(sum(recipients_table_raw1()$recipients_util), big.mark=",")
})
# Risk or intervenion population?
observeEvent(list(input$intRF,input$intICD, input$age_range, input$intervention_type), ignoreNULL = F, {
if(input$intervention_type == "Risk factor population"){
newVal = popRF()
} else {
newVal = popICD()
}
updateNumericInput(session,"intPop_c1",value=newVal)
})
# Eligible population statement (Dist inputs tab)
popElig <- reactive({
format(sum(resCEA()$pop), big.mark=",")
})
observe({
if(input$enable_intPop_c1){
txt_ = paste0("Set a custom target population size")
} else {
txt_ = paste0("The socioeconomic distribution of the eligible population (n=",popElig(),") has been automatically generated from disease / risk factor prevalence data. A custom distribution can be defined below (see \"Distributional inputs\").")
}
updateTip(id = "elig_pop_text",tip = txt_)
})
# ICER statement
baseICER <- reactive({
icer_calc(resCEA())
})
# Raw ICER
baseICER_raw <- reactive({
icer_calc_raw(resCEA())
})
# Weighted incremental QALYs statement
wtQALY <- reactive({
wt_qaly_calc(resCEA(),distQALYeffect(),recipients_table_raw1())
})
# User defined prevalence distribution
distPrev_user <- reactive({
sumPrev = sum(c(input$prevQ1,input$prevQ2,input$prevQ3,input$prevQ4,input$prevQ5))
table = data.frame(
imd=1:5,
prop_prev=c(input$prevQ1,input$prevQ2,input$prevQ3,input$prevQ4,input$prevQ5)/sumPrev)
})
# Auto-generated prevalence distribution (from ICD / RF selection)
distPrev_auto <- reactive({
table_prevalence_raw(input$intervention_type,input$intICD,input$intRF,input$age_range,resCEA())
})