From 994fb4af60135e675c294bb42aaafdbf85467d1f Mon Sep 17 00:00:00 2001 From: Tom Gebhardt Date: Wed, 9 Sep 2026 21:00:42 +0200 Subject: [PATCH] init release 0.0.1 --- LICENSE | 21 + README.md | 171 + app.R | 2743 ++++++ ...port-age-gender-composite-zensus-2022.json | 1359 +++ input_examples/age.json | 40 + input_examples/csv/patients.csv | 101 + input_examples/csv/people-100.csv | 101 + input_examples/fhir/hapi_batch1.json | 8189 +++++++++++++++++ input_examples/fhir/hapi_batch2 (copy).json | 7543 +++++++++++++++ input_examples/fhir/hapi_batch2.json | 7543 +++++++++++++++ input_examples/sex_gender_zensus/2022.json | 1745 ++++ 11 files changed, 29556 insertions(+) create mode 100644 LICENSE create mode 100644 README.md create mode 100644 app.R create mode 100644 input_examples/MeasureReport-mii-msrpt-summary-report-age-gender-composite-zensus-2022.json create mode 100644 input_examples/age.json create mode 100644 input_examples/csv/patients.csv create mode 100644 input_examples/csv/people-100.csv create mode 100644 input_examples/fhir/hapi_batch1.json create mode 100644 input_examples/fhir/hapi_batch2 (copy).json create mode 100644 input_examples/fhir/hapi_batch2.json create mode 100644 input_examples/sex_gender_zensus/2022.json diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..4395b72 --- /dev/null +++ b/LICENSE @@ -0,0 +1,21 @@ +MIT License + +Copyright (c) 2026 Interactive Medical Data App authors (University Medicine Greifswald) + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. diff --git a/README.md b/README.md new file mode 100644 index 0000000..c34d0e9 --- /dev/null +++ b/README.md @@ -0,0 +1,171 @@ +# Interactive Medical Data App + +**Version**: 0.0.1 + +--- + +## Authors + +* Tom Gebhardt +* Sarah Braun +* Christian Draeger +* Lea Michaelis +* Sherry Freiesleben +* Dagmar Waltemath +* Matthias Löbe +* Judith Wodke + +--- + +## Abstract + +> This Shiny application provides an interactive platform for uploading, integrating, visualizing, and summarizing heterogeneous medical datasets (CSV, JSON, FHIR). Built on state-of-the-art R packages (e.g., **shiny**, **fhircrackr**, **ggplot2**, **leaflet**), it enables researchers and clinical IT teams to explore data quality, distributions, and shared categories across multiple sources with full reproducibility and modularity. + +--- + +## Background + +* **Heterogeneous Data Sources** + Clinical and research data often exist in disparate formats: CSV exports, JSON-formatted histograms, and HL7 FHIR APIs. + +* **Need for Integration** + Comparative analyses require harmonization of these diverse formats into a unified view. + +* **Interactive Dashboards** + Shiny apps facilitate real-time exploration for non-technical users. + +--- + +## Features + +| **Category** | **Description** | +|------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------| +| **Data Import** | • Upload multiple CSV, JSON, or FHIR® bundle JSON files (e.g. pre-fetched from a HAPI Test Server)
• Live FHIR server connection code exists (`fhircrackr`/`httr`) but is currently not wired into the UI — no immediate use case was found, so it's unused for now | +| **Column Mapping** | • Dynamically map ‘Category’ and ‘Count’ columns when CSV headers differ | +| **Visual Exploration** | • Draggable mini-plots (Histogram, Pie Chart, Line Chart) with adjustable transparency
• “Stack All” and “Stack Selected” controls | +| **Data Combination & Intersection**| • Stacked-bar combination of selected categories across datasets
• Identify and export category intersections as JSON | +| **Statistical Overview** | • Auto-generated tables: dataset sizes, mean counts
• Color-coded summary of category prevalence (all/multiple/single sources) | +| **Geospatial Visualization** | • *Currently disabled*: code for an interactive map of German Data Integration Centers (**leaflet** + **geodata**) exists but is commented out and not part of the running app | +| **FHIR Bin Reports** | • Bin FHIR attribute values (text, numeric, boolean) and export as a FHIR `MeasureReport` (separate or composite stratifier format) | + +--- + +## System Architecture + +This application adopts a **modular Shiny framework** for clarity, testability, and maintainability: + +1. **UI Layer** + Defined via `fluidPage()` and `navbarPage()`, grouping functionality into: + + * Data Upload + * Census Data + * FHIR in bins + * Visualization + * Combined Data + * Statistics + +2. **Server Layer** + + * Reactivity: `reactive()`, `eventReactive()` ensure immediate UI updates + * Observers: `observe()`, `observeEvent()` handle user-driven events + +3. **Helper Modules** + + * `loadJsonData()`, `loadCsvData()`, `make_safe_id()` encapsulate parsing, validation, sanitization + +4. **Plotting Components** + + * `ggplot2` charts via separate render functions (`renderPlot()`); a **leaflet** map render function exists but is currently commented out (see Geospatial Visualization above) + +5. **Data Integration Pipeline** + Central reactive `allData` unifies datasets from uploads, powering both visualization and statistics without redundant computations. + +6. **Extensibility & Testing** + + * Modular structure allows adding new data sources or plot types + * Supports unit testing of individual functions independent of UI + +--- + +## Requirements + +* **R** ≥ 4.2 +* **OS**: Linux, macOS, Windows +* **Packages** (installed automatically via `ensure_pkg()`): + + ```r + install.packages(c( + "shiny", "shinythemes", "shinyjqui", + "jsonlite", "readr", "fhircrackr", "httr", + "dplyr", "tidyr", "ggplot2", "leaflet", + "DT" + )) + ``` + +--- + +## Installation + +1. **Clone repository** + + ```bash + git clone https://git.uni-greifswald.de/MILA_public/DQ-App.git + cd DQ-App + ``` + +2. **Install & Run** + + ```r + source("app.R") # ensure_pkg() installs missing dependencies + runApp("app.R") + ``` + +> **Need a ready-made R environment?** +> If you don't have a suitable R installation, use a container image from the +> [Rocker Project](https://rocker-project.org/). The `rocker/shiny` or +> `rocker/tidyverse` images provide R with Shiny preinstalled and give you a +> reproducible environment for running the app. + +--- + +## Usage + +1. Run the app (see Installation above) — Shiny will open it automatically in a browser window/tab. +2. Navigate tabs: + + * **Data Upload**: Upload CSV/JSON/FHIR bundle files + * **Census Data**: Visualize census population data and uploaded FHIR patient data + * **FHIR in bins**: Bin FHIR attribute values and export as a FHIR `MeasureReport` + * **Visualization**: Arrange & filter mini-plots + * **Combined Data**: Combine categories, download JSON + * **Statistics**: View summaries & category presence + +--- + +## Quality Assurance & Reproducibility + +* **Version Control**: Git with feature branches & peer review +* **Unit Testing**: Planned `testthat` coverage for core functions +* **Documentation**: Inline comments + precise README ensure transparency + +--- + +## Future Directions + +* **Extended FHIR Support**: Add Observations, Conditions +* **Automated Testing**: Full `testthat` suite integration + +--- + +## License & Citation + +* **License**: [MIT](LICENSE) +* **Citation**: + + > Gebhardt T., Braun S., Draeger C., Michaelis L., et al. (2025). *Interactive Medical Data App*. [https://git.uni-greifswald.de/MILA_public/DQ-App](https://git.uni-greifswald.de/MILA_public/DQ-App) + +--- + +> **Note**: A live FHIR-server connection was implemented and works, but is currently not exposed in the UI — no immediate use case was found for it. FHIR data is currently provided via uploading pre-fetched bundle JSON files instead. + + diff --git a/app.R b/app.R new file mode 100644 index 0000000..004723d --- /dev/null +++ b/app.R @@ -0,0 +1,2743 @@ +# ------------------------------------------------------------------------------- +# Title: Interactive Medical Data App +# Authors: Sarah Braun, Christian Draeger, Lea Michaelis, +# Sherry Freiesleben, Dagmar Waltemath, +# Matthias Löbe, Judith Wodke +# Date: 2025-01-08 +# Contact: sarah.braun@med.uni-greifswald.de +# Description: Shiny dashboard for uploading, combining, visualizing, +# and summarizing CSV/JSON/FHIR datasets. +# ------------------------------------------------------------------------------- + +# use this if the ragg renderer doesn't work, it defaults to the standard renderer than +options(shiny.useragg = FALSE) + +# 1. Install and load required packages +ensure_pkg <- function(pkgs) { + missing <- setdiff(pkgs, installed.packages()[, "Package"]) + if (length(missing)) install.packages(missing, dependencies = TRUE) + invisible(lapply(pkgs, library, character.only = TRUE)) +} + +required_pkgs <- c( + "shiny", "shinythemes", "shinyjqui", + "jsonlite", "readr", + "fhircrackr", "httr", + "dplyr", "tidyr", + "ggplot2", "leaflet", + "DT" +) + +ensure_pkg(required_pkgs) + +# 2. Helper: sanitize dynamic input IDs +make_safe_id <- function(x) { + id <- gsub("[^[:alnum:]_]", "_", x) + id <- gsub("_+", "_", id) + gsub("^_|_$", "", id) +} + +# Get all unique categories across all datasets for consistent x-axis +getAllCategories <- function(data_list) { + all_cats <- unique(unlist(lapply(data_list, function(x) x$data$Category))) + # Sort categories: put "unknown" last, others alphabetically + known_cats <- sort(all_cats[all_cats != "unknown"]) + if ("unknown" %in% all_cats) { + c(known_cats, "unknown") + } else { + known_cats + } +} + +# 3. UI definition +ui <- fluidPage( + theme = shinytheme("spacelab"), + + # Custom CSS & JS + tags$head( + tags$style(HTML(" + .plot_box { + min-width: 300px; + padding: 15px; + border: 1px solid #B0B0B0; + border-radius: 8px; + box-shadow: 0 4px 8px rgba(0,0,0,0.1); + background-color: transparent; + position: absolute; + } + + #plot_area { + position: relative; + height: 800px; + border: 1px solid #DDD; + overflow: auto; + padding: 10px; + } + ")), + tags$script(HTML(" + // Function to arrange plots side by side with dynamic width + function arrangeSideBySide() { + var plots = $('.plot_box'); + var containerWidth = $('#plot_area').width() - 20; + var plotHeight = 350; + + plots.each(function(index) { + var $plot = $(this); + + // Get number of categories from the plot's filter dropdown + var plotIndex = $plot.find('select[id^=\"filter_\"]').attr('id'); + if (plotIndex) { + var filterSelect = $('#' + plotIndex); + var categoryCount = filterSelect.find('option').length; + + // Calculate width: base 250px + 40px per category, max 800px + var plotWidth = Math.min(800, Math.max(250, 250 + (categoryCount * 40))); + $plot.css('width', plotWidth + 'px'); + } else { + // Fallback to default width + var plotWidth = 300; + $plot.css('width', plotWidth + 'px'); + } + + // Calculate position + var currentRowWidth = 0; + var currentRow = 0; + var plotsInCurrentRow = []; + + // Group plots by rows + plots.slice(0, index + 1).each(function(i) { + var thisWidth = parseInt($(this).css('width')) + 20; // Add margin + if (currentRowWidth + thisWidth > containerWidth && plotsInCurrentRow.length > 0) { + currentRow++; + currentRowWidth = thisWidth; + plotsInCurrentRow = [i]; + } else { + currentRowWidth += thisWidth; + plotsInCurrentRow.push(i); + } + }); + + // Position this plot + var leftOffset = 0; + for (var i = 0; i < plotsInCurrentRow.length; i++) { + if (plotsInCurrentRow[i] === index) break; + leftOffset += parseInt(plots.eq(plotsInCurrentRow[i]).css('width')) + 20; + } + + $plot.css({ + top: (currentRow * plotHeight) + 'px', + left: leftOffset + 'px' + }); + }); + } + + // Initialize side-by-side layout when plots are added + $(document).on('DOMNodeInserted', '#plot_area', function() { + setTimeout(arrangeSideBySide, 100); + }); + + // Re-arrange on window resize + $(window).resize(function() { + setTimeout(arrangeSideBySide, 100); + }); + + // Stack all plots + $(document).on('click','#stackPlots',function(){ + $('.plot_box').css({top:'0px',left:'0px'}); + }); + + // Arrange plots side by side + $(document).on('click','#arrangeSideBySide',function(){ + arrangeSideBySide(); + }); + + // Stack selected plots + $(document).on('click','#stackSelectedPlots',function(){ + var sel = $('#selectedPlotsToStack').val()||[]; + sel.slice(0,2).forEach(function(name){ + $('.plot_box[data-plot-name=\"'+name+'\"]') + .css({top:'0px',left:'0px'}); + }); + }); + + // Initialize side-by-side layout on page load + $(document).ready(function() { + setTimeout(arrangeSideBySide, 500); + }); + ")) + ), + + navbarPage("Medical Data Dashboard", + + # -- Data Upload Tab -- + tabPanel("Data Upload", + sidebarLayout( + sidebarPanel( + h4("Upload Files"), + fileInput("newFiles", "Add Files", + accept = c(".csv", ".json"), multiple = TRUE), + hr(), + uiOutput("fileListUI"), + actionButton("removeSelected", "Remove Selected", + class = "btn btn-danger", + style = "margin-top: 10px; width: 100%;") + ), + mainPanel( + h4("Uploaded Datasets"), + span("Upload your files and assign each a type. Files will be used in the corresponding tabs."), + hr(), + tableOutput("dataList") + ) + ) + ), + # -- Census Data Tab -- + tabPanel("Census Data", + sidebarLayout( + sidebarPanel( + h4("Data Selection"), + uiOutput("censusFileSelector"), + uiOutput("fhirFileSelector"), + h4("Visualization Options"), + selectInput("census_chart_type", "Chart Type:", + choices = c("Grouped Bar Chart" = "grouped", + "Stacked Bar Chart" = "stacked"), + selected = "grouped"), + checkboxInput("census_show_values", "Show Values on Bars", FALSE), + checkboxInput("census_log_scale", "Log Scale (Y-axis)", FALSE), + hr(), + downloadButton("downloadCensusData", "Download Census Data (JSON)"), + br(), br(), + downloadButton("downloadCensusPlot", "Download Plot (PNG)"), + ), + mainPanel( + h4("Census Population by Age Group and Gender"), + plotOutput("censusPlot", height = "600px"), + hr(), + h4("Census Data Summary"), + tableOutput("censusSummaryTable"), + hr(), + h4("Raw Census Data"), + DT::dataTableOutput("censusDataTable"), + hr(), + h4("FHIR Patient Data Summary"), + tableOutput("fhirSummaryTable"), + hr(), + h4("Raw FHIR Patient Data"), + DT::dataTableOutput("fhirDataTable") + ) + ) + ), + # -- FHIR in bins Tab -- + tabPanel("FHIR in bins", + sidebarLayout( + sidebarPanel( + h4("Select FHIR Files"), + uiOutput("fhirFileSelectorBinning"), + hr(), + h4("Category Selection"), + uiOutput("fhirResourceTypeUIBinning"), + hr(), + uiOutput("fhirMappingUIBinning"), + conditionalPanel( + condition = "input.fhir_category_col_binning != null && input.fhir_category_col_binning != ''", + h4("Create the bins"), + radioButtons( + "value_types", "What is the type of the values", + c("Numeric" = "num", "Boolean" = "bool", "Text" = "text"), "text"), + conditionalPanel( + condition = "input.value_types != null && input.value_types != 'bool'", + sliderInput("fhir_n_bins", "Number of bins:", + min = 1, max = 50, value = 5, step = 1) + ), + hr(), + radioButtons("bins_display_mode", "Display as:", + choices = c("Percentages" = "percent", + "Absolute Counts" = "absolute"), + selected = "percent") + ), + uiOutput("fhirValuesUIBinning") + ), + mainPanel( + h4("Visualisation of the fhir data in bins"), + plotOutput("plotBins", height = "400px"), + br(), + actionButton("downloadBinsReport", "Download Report", + class = "btn btn-primary", + icon = icon("download")) + ) + ), + ), + # -- Visualization Tab -- + tabPanel("Visualization", + sidebarLayout( + sidebarPanel( + h4("Data Sources"), + uiOutput("vizSourceSelector"), + hr(), + h4("Binning"), + radioButtons("viz_bin_type", "Use bins from:", + choices = c("Census (Age × Gender)" = "census", + "FHIR in Bins" = "fhir_bins"), + selected = "census"), + hr(), + h4("Display"), + radioButtons("viz_display_mode", "Display as:", + choices = c("Percentages" = "percent", + "Absolute Counts" = "absolute"), + selected = "percent"), + radioButtons("x_axis_display_mode", "X-Axis mode:", + choices = c("As selected bin source" = "uniform", + "Minimal" = "individual"), + selected = "uniform"), + radioButtons("viz_layout_mode", "Layout:", + choices = c("Individual plots" = "individual", + "Overlay" = "overlay"), + selected = "individual"), + conditionalPanel( + condition = "input.viz_layout_mode == 'overlay'", + sliderInput("viz_overlay_alpha", "Transparency:", + min = 0.1, max = 1, value = 0.5, step = 0.05) + ) + ), + mainPanel( + uiOutput("vizPlotsUI") + ) + ) + ), + + # -- Combined Data Tab -- + tabPanel("Combined Data", + fluidRow( + column(8, + h4("Combined Data Plot"), + plotOutput("combinedPlot"), + hr(), + h4("Intersection Plot"), + plotOutput("intersectionPlot") + ), + column(4, + div(style = "padding:15px; border:1px solid #DDD; border-radius:8px; background-color:#FFF;", + h4("Combine Data"), + checkboxGroupInput("combineFiles", + "Select Files to Combine:", choices = NULL), + uiOutput("valueSelectors"), + actionButton("combineData", "Combine Data"), + downloadButton("downloadCombined", "Download Combined Data (JSON)"), + br(), br(), + h4("Intersection Settings"), + p("Only categories present in ALL selected files will be kept."), + selectInput("intersectionValues", + "Common Categories:", choices = NULL, multiple = TRUE), + actionButton("combineIntersection", "Combine Intersection Data"), + downloadButton("downloadIntersection", "Download Intersection Data (JSON)") + ) + ) + ) + ), + + # -- Statistics Tab -- + tabPanel("Statistics", + fluidRow( + column(12, + h4("Dataset Statistics"), + tableOutput("statTable"), + hr(), + h4("Category Summary"), + tags$ul( + tags$li(strong("Green:"), " present in ALL files"), + tags$li(strong("Yellow:"), " present in ≥2 files"), + tags$li(strong("Red:"), " present in only 1 file") + ), + uiOutput("categorySummary") + ) + ) + ) + + ) # navbarPage +) # fluidPage # 4. Server logic +server <- function(input, output, session) { + + # 4.0 Manage file list + uploadedFiles <- reactiveVal(list()) + lastCensusPlot <- reactiveVal(NULL) + + # 4.1 Load JSON data + loadJsonData <- function(path) { + tryCatch({ + jd <- fromJSON(path) + + # Check if the expected structure exists + if (!is.null(jd$Histogram$Category$`@value`) && + !is.null(jd$Histogram$Count$`@value`)) { + + data.frame( + Category = jd$Histogram$Category$`@value`, + Count = as.numeric(jd$Histogram$Count$`@value`), + stringsAsFactors = FALSE + ) + } else { + # JSON doesn't have expected structure + warning(paste("JSON file", path, "doesn't have expected Histogram structure")) + data.frame(Category = character(), Count = numeric(), stringsAsFactors = FALSE) + } + }, error = function(e) { + # If JSON parsing fails or structure is wrong + warning(paste("Error loading JSON file:", e$message)) + data.frame(Category = character(), Count = numeric(), stringsAsFactors = FALSE) + }) + } + + # 4.2 Load CSV data with optional column mapping + loadCsvData <- function(path, idx) { + df <- read.csv(path, stringsAsFactors = FALSE) + + # If the CSV already has Category and Count columns, use them directly + if (all(c("Category", "Count") %in% colnames(df))) { + df$Count <- as.numeric(df$Count) + return(df[!is.na(df$Count), ]) + } + + # Otherwise, we need column mapping + category_col <- input[[paste0("map_cat_", idx)]] + + # If no category column is selected yet, return empty data frame + if (is.null(category_col) || category_col == "") { + return(data.frame(Category = character(), Count = numeric(), stringsAsFactors = FALSE)) + } + + # Check if the selected column exists in the current data frame + if (!category_col %in% colnames(df)) { + return(data.frame(Category = character(), Count = numeric(), stringsAsFactors = FALSE)) + } + + # Count occurrences of each category + tryCatch({ + result <- df %>% + count(Category = .data[[category_col]], name = "Count") %>% + as.data.frame(stringsAsFactors = FALSE) + + result$Count <- as.numeric(result$Count) + result[!is.na(result$Count), ] + }, error = function(e) { + # If there's any error, return empty data frame + data.frame(Category = character(), Count = numeric(), stringsAsFactors = FALSE) + }) + } + + # 4.3 load FHIR files + + loadFhirFile <- function(path, filename) { + tryCatch({ + fhir_data <- fromJSON(path, simplifyVector = FALSE) + + # Helper function to safely flatten any FHIR resource + flatten_fhir_resource <- function(resource, prefix = "") { + result <- list() + + if (is.list(resource)) { + for (name in names(resource)) { + value <- resource[[name]] + current_key <- if (prefix == "") name else paste(prefix, name, sep = ".") + + if (is.null(value)) { + result[[current_key]] <- NA_character_ + } else if (is.list(value) && !is.null(names(value))) { + # Named list - recurse + nested_result <- flatten_fhir_resource(value, current_key) + result <- c(result, nested_result) + } else if (is.list(value)) { + # Unnamed list (array) - convert to delimited string + if (length(value) > 0) { + array_strings <- sapply(value, function(item) { + if (is.list(item)) { + if (!is.null(item$value)) { + return(as.character(item$value)) + } else if (!is.null(item$display)) { + return(as.character(item$display)) + } else if (!is.null(item$code)) { + return(as.character(item$code)) + } else if (!is.null(item$system)) { + return(paste0(item$system, ":", item$code %||% "")) + } else { + non_null_values <- item[!sapply(item, is.null)] + if (length(non_null_values) > 0) { + key_value_pairs <- paste(names(non_null_values), + sapply(non_null_values, as.character), + sep = ":", collapse = ",") + return(paste0("{", key_value_pairs, "}")) + } else { + return("") + } + } + } else { + return(as.character(item)) + } + }) + result[[current_key]] <- paste(array_strings[array_strings != ""], collapse = "; ") + } else { + result[[current_key]] <- NA_character_ + } + } else if (length(value) > 1) { + result[[current_key]] <- paste(as.character(value), collapse = "; ") + } else { + result[[current_key]] <- as.character(value) + } + } + } else { + key <- if (prefix == "") "value" else prefix + result[[key]] <- as.character(resource) + } + + return(result) + } + + # Handle both single resources and bundles + if (is.list(fhir_data) && !is.null(fhir_data$resourceType)) { + if (fhir_data$resourceType == "Bundle" && !is.null(fhir_data$entry)) { + # Extract resources and group by type + resources_by_type <- list() + + for (i in seq_along(fhir_data$entry)) { + entry <- fhir_data$entry[[i]] + if (is.list(entry) && !is.null(entry$resource) && + is.list(entry$resource) && !is.null(entry$resource$resourceType)) { + + resource <- entry$resource + resource_type <- tolower(as.character(resource$resourceType)) + + # Initialize list for this resource type if needed + if (is.null(resources_by_type[[resource_type]])) { + resources_by_type[[resource_type]] <- list() + } + + # Add resource to appropriate type group + resources_by_type[[resource_type]][[length(resources_by_type[[resource_type]]) + 1]] <- resource + } + } + + # Create separate data frame for each resource type + result_list <- list() + + for (resource_type in names(resources_by_type)) { + resources <- resources_by_type[[resource_type]] + df_list <- list() + + for (i in seq_along(resources)) { + resource <- resources[[i]] + + # Flatten the resource + flattened <- flatten_fhir_resource(resource) + + # Add resource type prefix to all column names + if (length(flattened) > 0) { + prefixed_flattened <- list() + for (col_name in names(flattened)) { + prefixed_name <- paste(resource_type, col_name, sep = ".") + prefixed_flattened[[prefixed_name]] <- flattened[[col_name]] + } + flattened <- prefixed_flattened + } + + # Create data frame for this resource + if (length(flattened) > 0) { + flattened <- lapply(flattened, function(x) { + if (is.null(x) || length(x) == 0) { + return(NA_character_) + } else { + return(as.character(x)) + } + }) + + df_list[[i]] <- data.frame(flattened, stringsAsFactors = FALSE, check.names = FALSE) + } + } + + # Combine all resources of this type + if (length(df_list) > 0) { + df_list <- Filter(function(x) !is.null(x) && nrow(x) > 0, df_list) + + if (length(df_list) > 0) { + # Standardize columns + all_cols <- unique(unlist(lapply(df_list, names))) + df_list <- lapply(df_list, function(df) { + missing_cols <- setdiff(all_cols, names(df)) + for (col in missing_cols) { + df[[col]] <- NA_character_ + } + return(df[, all_cols, drop = FALSE]) + }) + + result_df <- do.call(rbind, df_list) + rownames(result_df) <- NULL + + # Store with resource type key + result_list[[paste0(filename, "_", resource_type)]] <- result_df + } + } + } + + return(result_list) + } + } + + # Return empty list if no valid data found + return(list()) + + }, error = function(e) { + warning(paste("Error loading FHIR file", filename, ":", e$message)) + return(list()) + }) + } + + # Helper function for null coalescing + `%||%` <- function(x, y) { + if (is.null(x) || length(x) == 0) y else x + } + + # 4.3.1 Dynamic UI: mapping CSV columns + output$mappingUI <- renderUI({ + req(input$dataFiles) + fps <- input$dataFiles$datapath + fns <- input$dataFiles$name + uiList <- lapply(seq_along(fps), function(i) { + if (tools::file_ext(fns[i]) == "csv") { + df0 <- read.csv(fps[i], stringsAsFactors = FALSE) + + # Sort column names - group by resource type prefix, then alphabetically + col_names <- colnames(df0) + + # Separate columns with resource type prefixes from those without + prefixed_cols <- col_names[grepl("\\.", col_names)] + non_prefixed_cols <- col_names[!grepl("\\.", col_names)] + + if (length(prefixed_cols) > 0) { + # Group prefixed columns by resource type + resource_groups <- split(prefixed_cols, sapply(prefixed_cols, function(x) { + strsplit(x, "\\.")[[1]][1] + })) + + # Sort resource types alphabetically, then sort columns within each group + sorted_prefixed <- unlist(lapply(sort(names(resource_groups)), function(res_type) { + cols <- resource_groups[[res_type]] + # Put basic fields first (resourceType, id, meta.*), then sort the rest + basic_pattern <- paste0("^", res_type, "\\.(resourceType|id|meta\\.)") + basic_cols <- cols[grepl(basic_pattern, cols)] + other_cols <- cols[!grepl(basic_pattern, cols)] + c(sort(basic_cols), sort(other_cols)) + })) + + # Combine: non-prefixed first (sorted), then prefixed (grouped and sorted) + sorted_cols <- c(sort(non_prefixed_cols), sorted_prefixed) + } else { + # No prefixed columns, just sort normally + sorted_cols <- sort(col_names) + } + + #if (!all(c("Category","Count") %in% colnames(df0))) { + tagList( + h4(paste("Map columns for", fns[i])), + selectInput(paste0("map_cat_", i), + "Category column:", choices = sorted_cols), + #selectInput(paste0("map_cnt_", i), + # "Count column:", choices = sorted_cols) + ) + #} + } + }) + do.call(tagList, uiList) + }) + + # 4.3.2 + output$censusFileSelector <- renderUI({ + files <- uploadedFiles() + census_files <- Filter(function(f) f$type == "census", files) + if (length(census_files) == 0) { + p("No census files uploaded yet. Please upload in the Data Upload tab.", + style = "color:#999; font-size:12px;") + } else { + selectInput("selected_census_file", "Census File:", + choices = setNames( + sapply(census_files, `[[`, "path"), + sapply(census_files, `[[`, "name") + )) + } + }) + + output$fhirFileSelector <- renderUI({ + files <- uploadedFiles() + fhir_files <- Filter(function(f) f$type == "fhir", files) + if (length(fhir_files) == 0) { + p("No FHIR files uploaded yet. Please upload in the Data Upload tab.", + style = "color:#999; font-size:12px;") + } else { + selectInput("selected_fhir_file", "FHIR File:", + choices = setNames( + sapply(fhir_files, `[[`, "path"), + sapply(fhir_files, `[[`, "name") + )) + } + }) + + loadCensusData <- function(path) { + tryCatch({ + census_json <- fromJSON(path, simplifyVector = FALSE) + + if (is.null(census_json$group) || length(census_json$group) == 0) { + warning("No group data found in census file") + return(NULL) + } + + first_group <- if (is.list(census_json$group[[1]])) { + census_json$group[[1]] + } else { + census_json$group + } + + if (is.null(first_group$stratifier) || length(first_group$stratifier) == 0) { + warning("No stratifier found in census file") + return(NULL) + } + + stratifiers <- first_group$stratifier + + # ── Detect format ──────────────────────────────────────────────────────────── + # Composite: stratifier entries have $stratum[[1]]$component + # Separate: stratifier entries have $code with LOINC codes for age/gender + first_stratum <- stratifiers[[1]]$stratum[[1]] + is_composite <- !is.null(first_stratum$component) + + if (is_composite) { + # ── Composite format (existing logic) ────────────────────────────────────── + stratum_list <- stratifiers[[1]]$stratum + + census_data <- lapply(stratum_list, function(stratum) { + components <- stratum$component + if (is.null(components) || length(components) < 2) return(NULL) + + age <- components[[1]]$value$text %||% NA + gender <- components[[2]]$value$text %||% NA + + count <- 0 + if (!is.null(stratum$measureScore$value)) { + count <- as.numeric(stratum$measureScore$value) + } else if (!is.null(stratum$population)) { + count <- as.numeric(stratum$population[[1]]$count %||% 0) + } + + data.frame(Age = age, Gender = gender, Count = count, + stringsAsFactors = FALSE) + }) + + census_df <- do.call(rbind, Filter(Negate(is.null), census_data)) + + } else { + # ── Separate format: two stratifiers, one for gender, one for age ────────── + # Identify which stratifier is gender and which is age by LOINC code + get_loinc <- function(strat) { + tryCatch({ + strat$code[[1]]$coding[[1]]$code + }, error = function(e) NA_character_) + } + + gender_strat <- NULL + age_strat <- NULL + + for (s in stratifiers) { + loinc <- get_loinc(s) + if (!is.na(loinc) && loinc == "99502-7") gender_strat <- s # Recorded sex or gender + if (!is.na(loinc) && loinc == "46251-5") age_strat <- s # Age group + } + + # Fallback: if LOINC codes not found, use position (first=gender, second=age) + if (is.null(gender_strat)) gender_strat <- stratifiers[[1]] + if (is.null(age_strat)) age_strat <- stratifiers[[2]] + + # Extract genders + genders <- lapply(gender_strat$stratum, function(s) { + list( + value = s$value$text %||% NA, + count = as.numeric(s$population[[1]]$count %||% 0) + ) + }) + + # Extract age groups + ages <- lapply(age_strat$stratum, function(s) { + list( + value = s$value$text %||% NA, + count = as.numeric(s$population[[1]]$count %||% 0) + ) + }) + + total <- sum(sapply(genders, `[[`, "count"), na.rm = TRUE) + + # Cross-tabulate: distribute counts proportionally across age × gender + # Since separate format has no cross-tabulation, estimate each cell as: + # count(age_i) * count(gender_j) / total + rows <- lapply(ages, function(a) { + lapply(genders, function(g) { + estimated_count <- if (total > 0) { + round(a$count * g$count / total) + } else 0 + data.frame( + Age = a$value, + Gender = g$value, + Count = estimated_count, + stringsAsFactors = FALSE + ) + }) + }) + + census_df <- do.call(rbind, unlist(rows, recursive = FALSE)) + } + + if (is.null(census_df) || nrow(census_df) == 0) { + warning("No valid census data extracted") + return(NULL) + } + + census_df <- census_df[!is.na(census_df$Age) & !is.na(census_df$Gender), ] + census_df$Count <- as.numeric(census_df$Count) + return(census_df) + + }, error = function(e) { + warning(paste("Error loading census JSON:", e$message)) + return(NULL) + }) + } + + # 4.4a Fetch comprehensive FHIR data using _include and _revinclude + + # Replace the fhirRawData function with this corrected version: + + fhirRawData <- reactive({ + #if (input$data_source == "fhir") { + if (input$fhir_input_type == "api") { + # Existing API logic - wrap in eventReactive + req(input$load_fhir) + req(input$fhir_url, input$max_bundles) + + showNotification("Starting FHIR data load...", type = "default", id = "fhir_load") + + all_resources <- list() + + resource_types_to_fetch <- c("Patient", "Observation", "Condition", "MedicationRequest", + "Procedure", "Encounter", "AllergyIntolerance", "Immunization") + + for (resource_type in resource_types_to_fetch) { + tryCatch({ + req_resource <- fhir_url(url = input$fhir_url, resource = resource_type) + + bundles <- fhir_search( + request = req_resource, + verbose = 0, + max_bundles = input$max_bundles + ) + + if (length(bundles) > 0) { + desc <- fhir_table_description( + resource = resource_type, + sep = " || ", + brackets = character(0), + rm_empty_cols = FALSE, + format = "compact" + ) + + df <- fhir_crack(bundles = bundles, design = desc, verbose = 0) + + if (!is.null(df) && nrow(df) > 0) { + all_resources[[resource_type]] <- df + } + } + }, error = function(e) { + print(paste("Error fetching", resource_type, ":", e$message)) + }) + } + + removeNotification("fhir_load") + + if (length(all_resources) > 0) { + showNotification(paste("Loaded", length(all_resources), "resource types"), type = "default") + } else { + showNotification("No data could be loaded", type = "error") + } + + return(all_resources) + + } else if (input$fhir_input_type == "file") { + # File upload logic + req(input$fhirFiles) + + all_files_data <- list() + fps <- input$fhirFiles$datapath + fns <- input$fhirFiles$name + + for (i in seq_along(fps)) { + file_data_list <- loadFhirFile(fps[i], fns[i]) # Now returns list of resource types + if (!is.null(file_data_list) && length(file_data_list) > 0) { + # Merge all resource types from this file into main list + all_files_data <- c(all_files_data, file_data_list) + } + } + + return(all_files_data) + } + #} + return(NULL) + }) + + # 4.4b UI for selecting resource type to visualize + output$fhirResourceTypeUI <- renderUI({ + #if (input$data_source == "fhir") { + fhir_data <- fhirRawData() + + if (!is.null(fhir_data)) { + available_resources <- names(fhir_data) + + if (length(available_resources) > 0) { + if (input$fhir_input_type == "api") { + selectInput("fhir_resource_to_viz", "Resource Type to Visualize:", + choices = available_resources, + selected = available_resources[1]) + } else { + # For file uploads, add resource type selector + resource_types <- unique(sapply(available_resources, function(x) { + parts <- strsplit(x, "_")[[1]] + if (length(parts) > 1) parts[length(parts)] else x + })) + + tagList( + selectInput("fhir_resource_to_viz", "Resource Type to Visualize:", + choices = resource_types, + selected = resource_types[1]), +# tags$div( +# h5("Available Datasets:"), +# tags$ul(lapply(available_resources, function(x) tags$li(x))) + #) + ) + } + } + } + #} + }) + + # 4.4c Update the mapping UI to show columns from selected resource + output$fhirMappingUI <- renderUI({ + if (input$data_source == "fhir") { + fhir_data <- fhirRawData() + if (!is.null(fhir_data)) { + if (input$fhir_input_type == "api") { + req(input$fhir_resource_to_viz) + df <- fhir_data[[input$fhir_resource_to_viz]] + if (!is.null(df) && nrow(df) > 0) { + selectInput("fhir_category_col", "Category column:", + choices = colnames(df), + selected = colnames(df)[1]) + } + } else { + # For file uploads, filter columns by selected resource type + req(input$fhir_resource_to_viz) + + # Get all datasets that match the selected resource type + selected_resource_type <- input$fhir_resource_to_viz + matching_datasets <- names(fhir_data)[grepl(paste0("_", selected_resource_type, "$"), names(fhir_data))] + + if (length(matching_datasets) > 0) { + # Get columns from all matching datasets + all_columns <- unique(unlist(lapply(matching_datasets, function(dataset_name) { + colnames(fhir_data[[dataset_name]]) + }))) + + # Filter to only columns that match the selected resource type + resource_prefix <- paste0(tolower(selected_resource_type), ".") + resource_columns <- all_columns[grepl(paste0("^", resource_prefix), all_columns)] + + if (length(resource_columns) > 0) { + # Remove the resource type prefix from display names + display_names <- gsub(paste0("^", resource_prefix), "", resource_columns) + + # Sort: basic fields first, then alphabetically + basic_fields <- c("resourceType", "id") + meta_fields <- display_names[grepl("^meta\\.", display_names)] + other_fields <- display_names[!display_names %in% basic_fields & !grepl("^meta\\.", display_names)] + + sorted_display_names <- c( + intersect(basic_fields, display_names), + sort(meta_fields), + sort(other_fields) + ) + + # Create named vector: display names as labels, full column names as values + choices <- setNames(resource_columns[match(sorted_display_names, display_names)], sorted_display_names) + + selectInput("fhir_category_col", "Category column:", + choices = choices, + selected = choices[1]) + } + } + } + } + } + }) + + # 4.5.1 List all uploaded files/requested data + allDataUploads <- reactive({ + req(input$dataFiles, input$fhirFiles, input$fhirApiRequest, input$censusFiles) + + json_files <- input$dataFiles + fhir_bundles <- input$fhirFiles + census_files <- input$censusFiles + fhir_api <- input$fhirApiRequest + + }) + + # 4.5.2 Aggregate uploaded/FHIR datasets + + allData <- reactive({ + req(input$data_source) + files <- uploadedFiles() + csv_json_files <- Filter(function(f) f$type == "csv_json", files) + + if (input$data_source == "file") { + if (length(csv_json_files) == 0) return(list()) + + results <- lapply(seq_along(csv_json_files), function(i) { + f <- csv_json_files[[i]] + ext <- tools::file_ext(f$name) + + df <- tryCatch({ + switch(ext, + "json" = loadJsonData(f$path), + "csv" = loadCsvData(f$path, i), + NULL + ) + }, error = function(e) { + warning(paste("Error processing file", f$name, ":", e$message)) + NULL + }) + + if (!is.null(df) && nrow(df) > 0) { + list(name = f$name, data = df) + } else { + NULL + } + }) + + results[!sapply(results, is.null)] + + } else if (input$data_source == "fhir") { + fhir_data <- fhirRawData() + if (!is.null(fhir_data) && length(fhir_data) > 0) { + results <- list() + + if (input$fhir_input_type == "file") { + req(input$fhir_category_col) + req(input$fhir_resource_to_viz) + + selected_resource_type <- input$fhir_resource_to_viz + matching_datasets <- names(fhir_data)[grepl(paste0("_", selected_resource_type, "$"), names(fhir_data))] + + for (dataset_key in matching_datasets) { + df <- fhir_data[[dataset_key]] + category_col <- input$fhir_category_col + + if (category_col %in% colnames(df)) { + df[[category_col]] <- ifelse(is.na(df[[category_col]]) | df[[category_col]] == "", + "unknown", as.character(df[[category_col]])) + + result_df <- df %>% + count(Category = .data[[category_col]], name = "Count") %>% + as.data.frame(stringsAsFactors = FALSE) + + if (nrow(result_df) > 0) { + results[[length(results) + 1]] <- list(name = dataset_key, data = result_df) + } + } + } + } else { + if (!is.null(input$fhir_resource_to_viz) && !is.null(input$fhir_category_col)) { + resource_key <- input$fhir_resource_to_viz + if (resource_key %in% names(fhir_data)) { + df <- fhir_data[[resource_key]] + category_col <- input$fhir_category_col + + if (category_col %in% colnames(df)) { + df[[category_col]] <- ifelse(is.na(df[[category_col]]), "unknown", df[[category_col]]) + + result_df <- df %>% + count(Category = .data[[category_col]], name = "Count") %>% + as.data.frame(stringsAsFactors = FALSE) + + if (nrow(result_df) > 0) { + resource_name <- paste0("FHIR-", input$fhir_resource_to_viz, ":", input$fhir_url) + results[[length(results) + 1]] <- list(name = resource_name, data = result_df) + } + } + } + } + } + return(results) + } + } + + return(list()) + }) + + # 4.6 Global maximum for shared y-axis + globalMax <- reactive({ + req(allData()) + max(unlist(lapply(allData(), function(x) x$data$Count)), + na.rm = TRUE) + }) + + # 4.7 Render dataset list & basic stats + output$dataList <- renderTable({ + do.call(rbind, lapply(allData(), function(x) + data.frame(Dataset = x$name, + Rows = nrow(x$data), + stringsAsFactors = FALSE))) + }) + output$statTable <- renderTable({ + do.call(rbind, lapply(allData(), function(x) + data.frame(Dataset = x$name, + Count = nrow(x$data), + Mean = mean(x$data$Count, na.rm = TRUE), + stringsAsFactors = FALSE))) + }) + + # 4.8 Update UI choices for combine/stack tabs + observe({ + req(allData()) + names <- sapply(allData(), `[[`, "name") + updateCheckboxGroupInput(session, "combineFiles", + choices = names, selected = names) + updateSelectInput(session, "selectedPlotsToStack", + choices = names) + }) + + # 4.9 Dynamic selectors for each chosen file + observe({ + req(allData()) + dl <- allData() + + # Make sure we have data before proceeding + if (length(dl) == 0) return(NULL) + + # Use local() to create a closure for each iteration + for (i in seq_along(dl)) { + local({ + idx <- i + f <- dl[[idx]] + + # Make sure the data frame exists and has data + if (is.null(f$data) || nrow(f$data) == 0) return(NULL) + + ui_name <- paste0("plotUI_", idx) + plot_name <- paste0("plot_", idx) + + output[[ui_name]] <- renderUI({ + enabled <- input[[paste0("cb_", idx)]] + if (isTRUE(enabled)) { + plotOutput(plot_name, height = "300px") + } + }) + + output[[plot_name]] <- renderPlot({ + enabled <- input[[paste0("cb_", idx)]] + chart <- input[[paste0("pt_", idx)]] + filterCat <- input[[paste0("filter_", idx)]] + alpha <- input[[paste0("op_", idx)]] + data0 <- f$data # Now this is captured in the local scope + + # Get all categories across all datasets for consistent x-axis + all_categories <- getAllCategories(dl) + + # Ensure data0 has all categories (add missing ones with Count = 0) + missing_cats <- setdiff(all_categories, data0$Category) + if (length(missing_cats) > 0) { + missing_data <- data.frame( + Category = missing_cats, + Count = 0, + stringsAsFactors = FALSE + ) + data0 <- rbind(data0, missing_data) + } + + # Apply filter if selected + df0 <- if (!is.null(filterCat) && length(filterCat) > 0) { + data0[data0$Category %in% filterCat, ] + } else { + data0 + } + + # Ensure categories are in consistent order + df0$Category <- factor(df0$Category, levels = all_categories) + + p_base <- ggplot(df0, aes(x = Category, y = Count, fill = Category)) + + theme_minimal(base_size = 14) + + scale_y_continuous(limits = c(0, globalMax())) + + scale_x_discrete(drop = FALSE) # Show all categories even if Count = 0 + + p <- switch(chart, + "Histogram" = p_base + geom_bar(stat = "identity", alpha = alpha), + "Pie Chart" = ggplot(df0, aes(x = "", y = Count, fill = Category)) + + geom_bar(stat = "identity", alpha = alpha, width = 1) + + coord_polar("y", start = 0), + "Line Chart" = ggplot(df0, aes(x = Category, y = Count, group = 1)) + + geom_line(size = 1.2, alpha = alpha) + + geom_point(size = 3, alpha = alpha) + + scale_x_discrete(drop = FALSE) + ) + + p + labs(title = f$name, x = "Category", y = "Count") + + theme(panel.background = element_rect(fill = "transparent", colour = NA), + plot.background = element_rect(fill = "transparent", colour = NA), + panel.grid = element_blank(), + axis.text.x = element_text(angle = 45, hjust = 1), # Rotate labels if needed + legend.position = "none" + ) + }, bg = "transparent") + }) + } + }) + + # 4.10 Combine data across files (robust) + combinedData <- reactiveVal(NULL) + observeEvent(input$combineData, { + req(input$combineFiles) + dl <- allData() + + cmb <- do.call(rbind, lapply(input$combineFiles, function(fn) { + idx <- which(sapply(dl, `[[`, "name") == fn) + df0 <- dl[[idx]]$data + safe_fn <- make_safe_id(fn) + sel <- input[[paste0("values_", safe_fn)]] + if (is.null(sel)) return(NULL) + df1 <- df0[df0$Category %in% sel, , drop = FALSE] + df1$Source <- fn + df1$Count <- as.numeric(df1$Count) + df1 <- df1[!is.na(df1$Count), ] + if (nrow(df1) == 0) return(NULL) + df1 + })) + + if (is.null(cmb) || nrow(cmb) == 0) { + showNotification("No valid data selected for combination.", type = "error") + return(NULL) + } + + combinedData(cmb) + }) + + output$combinedPlot <- renderPlot({ + req(combinedData()) + ggplot(combinedData(), aes(x = Category, y = Count, fill = Source)) + + geom_bar(stat = "identity", position = "stack") + + scale_y_continuous(limits = c(0, globalMax())) + + theme_minimal(base_size = 14) + + labs(title = "Combined Data", x = "Category", y = "Count") + }) + + output$downloadCombined <- downloadHandler( + filename = function() paste0("combined_data_", Sys.Date(), ".json"), + content = function(file) jsonlite::write_json(combinedData(), file) + ) + + # 4.11 Intersection across all selected files + intersectionData <- reactiveVal(NULL) + observe({ + req(input$combineFiles) + dl <- allData()[sapply(allData(), `[[`, "name") %in% input$combineFiles] + common <- Reduce(intersect, lapply(dl, function(x) x$data$Category)) + updateSelectInput(session, "intersectionValues", + choices = common, selected = common) + }) + + observeEvent(input$combineIntersection, { + req(input$combineFiles) + cats <- input$intersectionValues + if (is.null(cats) || length(cats) == 0) { + showNotification("No categories selected for intersection.", type = "error") + return(NULL) + } + + dl <- allData() + inter <- do.call(rbind, lapply(input$combineFiles, function(fn) { + idx <- which(sapply(dl, `[[`, "name") == fn) + df0 <- dl[[idx]]$data + df1 <- df0[df0$Category %in% cats, , drop = FALSE] + df1$Source <- fn + df1$Count <- as.numeric(df1$Count) + df1 <- df1[!is.na(df1$Count), ] + if (nrow(df1) == 0) return(NULL) + df1 + })) + + if (is.null(inter) || nrow(inter) == 0) { + showNotification("No intersection data found.", type = "error") + return(NULL) + } + + intersectionData(inter) + }) + + output$intersectionPlot <- renderPlot({ + req(intersectionData()) + ggplot(intersectionData(), aes(x = Category, y = Count, fill = Source)) + + geom_bar(stat = "identity", position = "stack") + + scale_y_continuous(limits = c(0, globalMax())) + + theme_minimal(base_size = 14) + + labs(title = "Intersection Data", x = "Category", y = "Count") + }) + + output$downloadIntersection <- downloadHandler( + filename = function() paste0("intersection_data_", Sys.Date(), ".json"), + content = function(file) jsonlite::write_json(intersectionData(), file) + ) + + # 4.12 Map of German integration centers + #output$map <- renderLeaflet({ + # centers <- data.frame( + # name = c("Greifswald","Dresden","Leipzig","Aachen","Hannover","Hamburg","Berlin"), + # lat = c(54.093,51.050,51.339,50.775,52.374,53.550,52.520), + # lng = c(13.387,13.738,12.374,6.083,9.738,9.993,13.405), + # stringsAsFactors = FALSE + # ) + # germany <- geodata::gadm("Germany", level = 0, path = tempdir()) + # leaflet() %>% + # addProviderTiles(providers$CartoDB.PositronNoLabels) %>% + # addPolygons(data = germany, color = "#333333", weight = 1, fill = FALSE) %>% + # setView(lng = 10.5, lat = 51.0, zoom = 6) %>% + # addCircleMarkers(data = centers, lat = ~lat, lng = ~lng, + # label = ~name, radius = 6, fill = TRUE, fillOpacity = 0.9) + #}) + + + #### Census data reactive + censusData <- reactive({ + req(input$selected_census_file) + census_df <- loadCensusData(input$selected_census_file) + if (is.null(census_df)) { + showNotification("Failed to load census data.", type = "error") + return(NULL) + } + census_df$Source <- "Census" + showNotification(paste("Loaded", nrow(census_df), "census records"), type = "message") + return(census_df) + }) + + fhirPatientData <- reactive({ + req(censusData()) + + census_df <- censusData() + census_age_labels <- unique(census_df$Age) + census_gender_labels <- unique(census_df$Gender) + + tryCatch({ + req(input$selected_fhir_file) + raw <- jsonlite::fromJSON(input$selected_fhir_file, simplifyVector = FALSE) + + entries <- NULL + if (!is.null(raw$resourceType) && raw$resourceType == "Bundle") { + entries <- raw$entry + } else if (is.list(raw)) { + entries <- raw + } + + if (is.null(entries) || length(entries) == 0) { + showNotification("No entries found in FHIR bundle.", type = "warning") + return(NULL) + } + + patients <- Filter(function(e) { + res <- if (!is.null(e$resource)) e$resource else e + !is.null(res$resourceType) && res$resourceType == "Patient" + }, entries) + + if (length(patients) == 0) { + showNotification("No Patient resources found in FHIR bundle.", type = "warning") + return(NULL) + } + + records <- lapply(patients, function(e) { + p <- if (!is.null(e$resource)) e$resource else e + bd <- p$birthDate %||% NA_character_ + gender <- p$gender %||% NA_character_ + list(birthDate = as.character(bd), gender = as.character(gender)) + }) + + df <- data.frame( + birthDate = sapply(records, `[[`, "birthDate"), + gender = sapply(records, `[[`, "gender"), + stringsAsFactors = FALSE + ) + + today <- Sys.Date() + + df$age_numeric <- sapply(df$birthDate, function(bd) { + if (is.null(bd) || is.na(bd) || !nzchar(trimws(bd))) return(NA_real_) + + bd <- trimws(bd) + bd <- sub("T.*$", "", bd) + + bd_padded <- if (nchar(bd) == 4) paste0(bd, "-01-01") + else if (nchar(bd) == 7) paste0(bd, "-01") + else bd + + dob <- tryCatch(as.Date(bd_padded), error = function(e) NA) + + if (is.null(dob) || length(dob) == 0 || is.na(dob)) return(NA_real_) + if (dob >= today || dob < as.Date("1900-01-01")) return(NA_real_) + + year_diff <- as.numeric(format(today, "%Y")) - as.numeric(format(dob, "%Y")) + birthday_passed <- format(today, "%m-%d") >= format(dob, "%m-%d") + as.numeric(year_diff - ifelse(birthday_passed, 0L, 1L)) + }) + + df$Age <- bin_age_to_census_groups(df$age_numeric, census_age_labels) + df$Gender <- map_fhir_gender(df$gender, census_gender_labels) + df <- df[!is.na(df$Age) & !is.na(df$Gender), ] + + if (nrow(df) == 0) { + showNotification( + "FHIR patients could not be matched to census Age/Gender groups.", + type = "warning" + ) + return(NULL) + } + + result <- df %>% + dplyr::count(Age, Gender, name = "Count") %>% + as.data.frame(stringsAsFactors = FALSE) + + result$Source <- "FHIR" + + showNotification( + paste0("FHIR: ", nrow(df), " patients matched across ", + nrow(result), " Age×Gender groups"), + type = "message" + ) + + return(result) + + }, error = function(e) { + showNotification(paste("Error parsing FHIR bundle:", e$message), type = "error") + return(NULL) + }) + }) + + # Census plot + output$censusPlot <- renderPlot({ + req(censusData()) + + census_df <- censusData() + fhir_df <- fhirPatientData() # NULL if no FHIR file uploaded yet — that's fine + + chart_type <- input$census_chart_type + show_values <- input$census_show_values + + # ── Combine census + FHIR (if available) ──────────────────────────────────── + if (!is.null(fhir_df)) { + # Keep only Age groups and Genders present in census so axes stay consistent + fhir_df <- fhir_df[fhir_df$Age %in% unique(census_df$Age) & + fhir_df$Gender %in% unique(census_df$Gender), ] + + plot_df <- rbind( + census_df[, c("Age", "Gender", "Count", "Source")], + fhir_df [, c("Age", "Gender", "Count", "Source")] + ) + + # Interaction label used for fill: e.g. "female · Census", "male · FHIR" + plot_df$fill_group <- paste(plot_df$Gender, "\u00b7", plot_df$Source) + + # Colour palette: one hue per gender (from Set2), light shade = Census, dark = FHIR + genders <- sort(unique(census_df$Gender)) + base_colours <- RColorBrewer::brewer.pal(max(3, length(genders)), "Set2")[seq_along(genders)] + + # Census uses Set2 (soft greens/blues/oranges), FHIR uses Dark2 (bold versions) + census_colours <- RColorBrewer::brewer.pal(max(3, length(genders)), "Set2")[seq_along(genders)] + fhir_colours <- RColorBrewer::brewer.pal(max(3, length(genders)), "Dark2")[seq_along(genders)] + + fill_vals <- c() + for (k in seq_along(genders)) { + census_lbl <- paste(genders[k], "\u00b7 Census") + fhir_lbl <- paste(genders[k], "\u00b7 FHIR") + fill_vals[census_lbl] <- census_colours[k] + fill_vals[fhir_lbl] <- fhir_colours[k] + } + + overlay_active <- TRUE + } else { + # No FHIR data — plot census only exactly as before + plot_df <- census_df[, c("Age", "Gender", "Count", "Source")] + plot_df$fill_group <- plot_df$Gender + + fill_vals <- NULL # fall back to scale_fill_brewer below + overlay_active <- FALSE + } + + plot_df <- plot_df %>% + group_by(Source) %>% + mutate(Percent = round(Count / sum(Count, na.rm = TRUE) * 100, 2)) %>% + ungroup() + + age_order <- unique(plot_df$Age[order(as.numeric(sub("[-+].*", "", plot_df$Age)))]) + plot_df$Age <- factor(plot_df$Age, levels = age_order) + # ── Base ggplot ────────────────────────────────────────────────────────────── + p <- ggplot(plot_df, aes(x = Age, y = Percent, fill = fill_group)) + + theme_minimal(base_size = 14) + + labs( + title = if (overlay_active) "Population by Age Group and Gender (Census vs FHIR)" + else "Population by Age Group and Gender", + x = "Age Group", + y = "Population (%)", + fill = if (overlay_active) "Gender \u00b7 Source" else "Gender" + ) + + theme( + axis.text.x = element_text(angle = 45, hjust = 1), + legend.position = "bottom", + plot.title = element_text(hjust = 0.5, face = "bold", size = 16) + ) + + # Apply manual colours when FHIR overlay is active + if (overlay_active) { + p <- p + scale_fill_manual(values = fill_vals) + } else { + p <- p + scale_fill_brewer(palette = "Set2") + } + + # ── Geoms based on chart type ──────────────────────────────────────────────── + dodge_width <- if (overlay_active) 0.85 else 0.9 # slightly tighter when doubled + + if (chart_type == "grouped" || chart_type == "dodged") { + p <- p + geom_bar(stat = "identity", + position = position_dodge(width = dodge_width), + alpha = 1, + colour = "white", linewidth = 0.2) + if (show_values) { + p <- p + geom_text(aes(label = Count), + position = position_dodge(width = dodge_width), + vjust = -0.4, size = 2.8) + } + + } else if (chart_type == "stacked") { + p <- ggplot(plot_df, aes(x = Age, y = Percent, fill = fill_group)) + + theme_minimal(base_size = 14) + + labs( + title = if (overlay_active) "Population by Age Group and Gender (Census vs FHIR)" + else "Population by Age Group and Gender", + x = "Age Group", + y = "Population (%)", + fill = if (overlay_active) "Gender · Source" else "Gender" + ) + + theme( + axis.text.x = element_text(angle = 45, hjust = 1), + legend.position = "bottom", + plot.title = element_text(hjust = 0.5, face = "bold", size = 16) + ) + + geom_bar(stat = "identity", position = "stack", alpha = 1, + colour = "white", linewidth = 0.2) + + {if (overlay_active) facet_wrap(~Source, ncol = 2) else NULL} + + {if (overlay_active) scale_fill_manual(values = fill_vals) + else scale_fill_brewer(palette = "Set2")} + + if (show_values) { + p <- p + geom_text(aes(label = paste0(Percent, "%")), + position = position_stack(vjust = 0.5), size = 2.8) + } + } + + if (isTRUE(input$census_log_scale)) { + p <- p + scale_y_continuous( + trans = "log10", + labels = scales::comma + ) + } + lastCensusPlot(p) + return(p) + }) + + # Input files table + + output$inputFilesTable <- DT::renderDataTable({ + req() + }) + + + # Census summary table + output$censusSummaryTable <- renderTable({ + req(censusData()) + + df <- censusData() + + # Create summary statistics + summary_df <- df %>% + group_by(Gender) %>% + summarise( + Total_Population = sum(Count, na.rm = TRUE), + Age_Groups = n_distinct(Age), + Average_per_Group = round(mean(Count, na.rm = TRUE), 0) + ) %>% + as.data.frame() + + return(summary_df) + }) + + # Census data table + output$censusDataTable <- DT::renderDataTable({ + req(censusData()) + + df <- censusData() + + # Sort age groups numerically + age_order <- unique(df$Age[order(as.numeric(sub("[-+].*", "", df$Age)))]) + df$Age <- factor(df$Age, levels = age_order) + df <- df[order(df$Age), ] + df$Age <- as.character(df$Age) # convert back so DT renders it cleanly + + DT::datatable( + df, + options = list( + pageLength = 25, + scrollX = TRUE, + order = list() # ← remove default ordering so our pre-sort is respected + ), + rownames = FALSE + ) + }) + + output$fhirSummaryTable <- renderTable({ + req(fhirPatientData()) + + df <- fhirPatientData() + + df %>% + group_by(Gender) %>% + summarise( + Total_Patients = sum(Count, na.rm = TRUE), + Age_Groups = n_distinct(Age), + Average_per_Group = round(mean(Count, na.rm = TRUE), 0) + ) %>% + as.data.frame() + }) + + output$fhirDataTable <- DT::renderDataTable({ + req(fhirPatientData()) + + df <- fhirPatientData() + + # Sort age groups numerically + age_order <- unique(df$Age[order(as.numeric(sub("[-+].*", "", df$Age)))]) + df$Age <- factor(df$Age, levels = age_order) + df <- df[order(df$Age), ] + df$Age <- as.character(df$Age) + + DT::datatable( + df, + options = list( + pageLength = 25, + scrollX = TRUE, + order = list() + ), + rownames = FALSE + ) + }) + + # Download census data + output$downloadCensusData <- downloadHandler( + filename = function() { + paste0("census_data_", Sys.Date(), ".json") + }, + content = function(file) { + req(censusData()) + jsonlite::write_json(censusData(), file, pretty = TRUE) + } + ) + + # Download census plot + output$downloadCensusPlot <- downloadHandler( + filename = function() { + paste0("census_plot_", Sys.Date(), ".png") + }, + content = function(file) { + req(lastCensusPlot()) + ggsave(file, plot = lastCensusPlot(), width = 12, height = 8, dpi = 300) + } + ) + + # ── HELPER: bin a numeric age into whatever age-group labels exist in census ── + # Reads the census age labels (e.g. "0-17", "18-34", "35-49", "50-64", "65+") + # and maps a numeric age to the correct label. + # Returns NA if no label can be matched. + bin_age_to_census_groups <- function(age_numeric, census_age_labels) { + # Parse each label into a (low, high) pair + # Supported formats: "0-17" "18-34" "65+" "under 18" "80 and over" + parse_label <- function(lbl) { + lbl <- trimws(lbl) + # Pattern: "65+" or "65 and over" or "65 and older" → [65, Inf) + if (grepl("^(\\d+)\\s*\\+$", lbl) || + grepl("^(\\d+)\\s+and\\s+(over|older|above)", lbl, ignore.case = TRUE) || + grepl("^(\\d+)\\s+or\\s+(over|older|above)", lbl, ignore.case = TRUE)) { + lo <- as.numeric(sub("^(\\d+).*", "\\1", lbl)) + return(c(lo, Inf)) + } + # Pattern: "under 18" or "less than 18" → [0, 17] + if (grepl("^under\\s+(\\d+)$", lbl, ignore.case = TRUE) || + grepl("^less\\s+than\\s+(\\d+)$", lbl, ignore.case = TRUE)) { + hi <- as.numeric(sub("\\D*(\\d+)$", "\\1", lbl)) - 1 + print("bin: ", c(0, hi)) + return(c(0, hi)) + } + # Pattern: "18-34" or "18 to 34" or "18–34" + m <- regmatches(lbl, regexpr("^(\\d+)\\s*[-–to]+\\s*(\\d+)$", lbl)) + if (length(m) == 1) { + nums <- as.numeric(regmatches(m, gregexpr("\\d+", m))[[1]]) + return(c(nums[1], nums[2])) + } + # Single number label – exact match + if (grepl("^\\d+$", lbl)) { + n <- as.numeric(lbl) + return(c(n, n)) + } + return(c(NA, NA)) + } + + # Build lookup table once + bounds <- lapply(census_age_labels, parse_label) + + # Assign each age + sapply(age_numeric, function(a) { + if (is.na(a)) return(NA_character_) + for (k in seq_along(census_age_labels)) { + lo <- bounds[[k]][1]; hi <- bounds[[k]][2] + if (!is.na(lo) && a >= lo && a <= hi) return(census_age_labels[k]) + } + NA_character_ # age falls outside all defined groups + }) + } + + # ── HELPER: normalise FHIR gender to census Gender labels ──────────────────── + # census_gender_labels: the unique Gender values found in censusData() + # fhir_gender: character vector of raw FHIR gender values + map_fhir_gender <- function(fhir_gender, census_gender_labels) { + fhir_lower <- tolower(trimws(as.character(fhir_gender))) + census_lower <- tolower(trimws(census_gender_labels)) + + unique_fhir <- unique(fhir_lower) + # Remove NA values from the unique set — handle them at the end + unique_fhir <- unique_fhir[!is.na(unique_fhir)] + + mapping <- setNames(rep(NA_character_, length(unique_fhir)), unique_fhir) + + for (fg in unique_fhir) { + exact <- census_lower == fg + exact[is.na(exact)] <- FALSE # ← guard: NA → FALSE + if (any(exact)) { mapping[fg] <- census_gender_labels[which(exact)[1]]; next } + + sub_match <- startsWith(census_lower, fg) | startsWith(fg, census_lower) + sub_match[is.na(sub_match)] <- FALSE # ← same guard + if (any(sub_match)) { mapping[fg] <- census_gender_labels[which(sub_match)[1]]; next } + + if (!is.na(fg) && fg %in% c("male", "m")) { m <- census_lower %in% c("male","männlich","m","man"); if (any(m)) mapping[fg] <- census_gender_labels[which(m)[1]] } + if (!is.na(fg) && fg %in% c("female", "f", "w")) { m <- census_lower %in% c("female","weiblich","f","w","woman"); if (any(m)) mapping[fg] <- census_gender_labels[which(m)[1]] } + if (!is.na(fg) && fg %in% c("other", "diverse", "d")) { m <- census_lower %in% c("other","diverse","d","divers"); if (any(m)) mapping[fg] <- census_gender_labels[which(m)[1]] } + if (!is.na(fg) && fg %in% c("unknown", "")) { m <- census_lower %in% c("unknown","unbekannt","u"); if (any(m)) mapping[fg] <- census_gender_labels[which(m)[1]] } + } + + # Apply mapping — NA fhir_gender values map to NA_character_ naturally + mapped <- mapping[fhir_lower] + ifelse(is.na(mapped), NA_character_, mapped) + } + + # 4.13 Draggable mini‐plots + output$plotsUI <- renderUI({ + req(allData()) + dl <- allData() + tagList(lapply(seq_along(dl), function(i) { + f <- dl[[i]] + safe_i <- i + jqui_draggable( + div(class = "plot_box", `data-plot-name` = f$name, + div(style = "display:flex; justify-content:space-between;", + h4(f$name), checkboxInput(paste0("cb_", safe_i), NULL, TRUE) + ), + selectizeInput(paste0("filter_", safe_i), "Filter Categories:", + choices = unique(f$data$Category), multiple = TRUE), + selectInput(paste0("pt_", safe_i), "Chart Type:", + c("Histogram", "Pie Chart", "Line Chart")), + uiOutput(paste0("plotUI_", safe_i)), + sliderInput(paste0("op_", safe_i), "Transparency:", + min = 0.1, max = 1, value = 1, step = 0.1), + downloadButton(paste0("download_", safe_i), "Export JSON", + class = "btn btn-sm btn-outline-secondary", + style = "width: 100%; margin-top: 10px;") + ) + ) + })) + }) + + # 4.14 Category summary table + output$categorySummary <- renderUI({ + req(allData()) + dl <- allData() + names <- sapply(dl, `[[`, "name") + catMap <- list() + for (f in dl) for (c in unique(f$data$Category)) { + catMap[[c]] <- union(catMap[[c]], f$name) + } + + # Build HTML table + html <- '' + html <- paste0(html, '', + paste0('', collapse = ''), '') + + for (c in names(catMap)) { + pres <- length(catMap[[c]]) + color <- if (pres == length(names)) "#d4edda" + else if (pres >= 2) "#fff3cd" + else "#f8d7da" + row <- paste0( + '', + paste0(ifelse(names %in% catMap[[c]], + paste0(''), + ''), + collapse = ''), + '' + ) + html <- paste0(html, row) + } + + HTML(paste0(html, '
Category', names, 'Count
', c, '', pres, '
')) + }) + + # 4.15 Individual plot download handlers + observe({ + req(allData()) + dl <- allData() + + for (i in seq_along(dl)) { + local({ + idx <- i + f <- dl[[idx]] + + output[[paste0("download_", idx)]] <- downloadHandler( + filename = function() { + # Create safe filename from dataset name + safe_name <- make_safe_id(f$name) + category_col <- input$fhir_category_col + safe_category <- make_safe_id(category_col) + paste0(safe_name, "_", safe_category, "_", Sys.Date(), ".json") + }, + content = function(file) { + # Get the current filtered data (same logic as plot) + filterCat <- input[[paste0("filter_", idx)]] + + export_data <- if (!is.null(filterCat) && length(filterCat) > 0) { + f$data[f$data$Category %in% filterCat, ] + } else { + f$data + } + + # Add metadata to the export + export_object <- list( + metadata = list( + dataset_name = f$name, + category_column = input$fhir_category_col, + export_date = Sys.time(), + total_rows = nrow(export_data), + filtered = !is.null(filterCat) && length(filterCat) > 0, + filter_categories = if (!is.null(filterCat)) filterCat else NULL + ), + data = export_data + ) + + jsonlite::write_json(export_object, file, pretty = TRUE, auto_unbox = TRUE) + } + ) + }) + } + }) + + # 4.16 handle file additions + observeEvent(input$newFiles, { + req(input$newFiles) + current <- uploadedFiles() + + new_entries <- lapply(seq_len(nrow(input$newFiles)), function(i) { + list( + name = input$newFiles$name[i], + path = input$newFiles$datapath[i], + type = "csv_json" # default type + ) + }) + + # Avoid duplicates by name + existing_names <- sapply(current, `[[`, "name") + new_entries <- Filter(function(e) !e$name %in% existing_names, new_entries) + + uploadedFiles(c(current, new_entries)) + }) + + # 4.17 handlie file removal + observeEvent(input$removeSelected, { + current <- uploadedFiles() + + # Collect which checkboxes are checked + to_remove <- which(sapply(seq_along(current), function(i) { + isTRUE(input[[paste0("file_select_", i)]]) + })) + + if (length(to_remove) > 0) { + uploadedFiles(current[-to_remove]) + } + }) + + # 4.19 Render file list UI + output$fileListUI <- renderUI({ + files <- uploadedFiles() + if (length(files) == 0) { + return(p("No files uploaded yet.", style = "color: #999;")) + } + + tagList( + h4("Uploaded Files"), + lapply(seq_along(files), function(i) { + f <- files[[i]] + div(style = "display:flex; align-items:center; gap:10px; margin-bottom:8px; + padding:8px; border:1px solid #DDD; border-radius:4px;", + checkboxInput(paste0("file_select_", i), label = NULL, value = FALSE), + div(style = "flex:1; font-size:13px; word-break:break-all;", f$name), + selectInput(paste0("file_type_", i), label = NULL, + choices = c("CSV/JSON" = "csv_json", + "Census" = "census", + "FHIR" = "fhir"), + selected = f$type, + width = "130px") + ) + }) + ) + }) + + # 4.20 Sync type changes + observe({ + files <- uploadedFiles() + if (length(files) == 0) return() + + updated <- lapply(seq_along(files), function(i) { + type_val <- input[[paste0("file_type_", i)]] + if (!is.null(type_val)) files[[i]]$type <- type_val + files[[i]] + }) + + uploadedFiles(updated) + }) + + # 4.18 FHIR data binning and aggregation + output$fhirFileSelectorBinning <- renderUI({ + files <- uploadedFiles() + fhir_files <- Filter(function(f) f$type == "fhir", files) + if (length(fhir_files) == 0) { + p("No FHIR files uploaded yet. Please upload in the Data Upload tab.", + style = "color:#999; font-size:12px;") + } else { + checkboxGroupInput("selected_fhir_files_binning", "Select FHIR Files:", + choices = setNames( + sapply(fhir_files, `[[`, "path"), + sapply(fhir_files, `[[`, "name") + )) + } + }) + + fhirDataBinning <- reactive({ + req(input$selected_fhir_files_binning) + + selected_paths <- input$selected_fhir_files_binning + files <- uploadedFiles() + fhir_files <- Filter(function(f) f$type == "fhir" && f$path %in% selected_paths, files) + + if (length(fhir_files) == 0) return(list()) + + all_files_data <- list() + for (f in fhir_files) { + file_data_list <- loadFhirFile(f$path, f$name) + if (!is.null(file_data_list) && length(file_data_list) > 0) { + all_files_data <- c(all_files_data, file_data_list) + } + } + + return(all_files_data) + }) + + output$fhirMappingUIBinning <- renderUI({ + fhir_data <- fhirDataBinning() + req(input$fhir_resource_to_viz_binning) + + selected_resource_type <- input$fhir_resource_to_viz_binning + matching_datasets <- names(fhir_data)[grepl(paste0("_", selected_resource_type, "$"), names(fhir_data))] + + if (length(matching_datasets) > 0) { + all_columns <- unique(unlist(lapply(matching_datasets, function(dataset_name) { + colnames(fhir_data[[dataset_name]]) + }))) + + resource_prefix <- paste0(tolower(selected_resource_type), ".") + resource_columns <- all_columns[grepl(paste0("^", resource_prefix), all_columns)] + + if (length(resource_columns) > 0) { + selectInput("fhir_category_col_binning", "Category column:", + choices = resource_columns, + selected = resource_columns[1]) + } + + } + }) + + output$fhirValuesUIBinning <- renderUI({ + fhir_data <- fhirDataBinning() + req(input$fhir_category_col_binning, input$fhir_resource_to_viz_binning) + + selected_resource_type <- input$fhir_resource_to_viz_binning + selected_attribute <- input$fhir_category_col_binning + + n_bins <- input$fhir_n_bins %||% 5 #get bins from input or default to 5 if input isn't loaded yet + value_type <- input$value_types %||% FALSE + + # Get unique values from the selected column + matching_datasets <- names(fhir_data)[grepl(paste0("_", selected_resource_type, "$"), names(fhir_data))] + + uniqueValues <- sort(unique(unlist(lapply(matching_datasets, function(dataset_name) { + df <- fhir_data[[dataset_name]] + if (selected_attribute %in% colnames(df)) { + df[[selected_attribute]] + } + else cat("FAILED \n") + })))) + + if (value_type == "bool"){ + n_bins = 2 + } + + bin_inputs <- lapply(1:n_bins, function(i){ + if(value_type == "num"){ + numericInput( + paste0("bin_", i), paste("Bin", i, "max:"), i) + } else { + selectInput( + inputId = paste0("bin_", i), + label = paste("Bin", i, "values:"), + choices = uniqueValues, + multiple = FALSE + ) + } + }) + + tagList( + h4("Create the bins"), + bin_inputs + ) + }) + + output$plotBins <- renderPlot({ + fhir_data <- fhirDataBinning() + req(input$fhir_category_col_binning, input$fhir_resource_to_viz_binning, + input$fhir_n_bins, input$value_types, input$selected_fhir_files_binning) + + selected_resource_type <- input$fhir_resource_to_viz_binning + selected_attribute <- input$fhir_category_col_binning + n_bins <- input$fhir_n_bins + value_type <- input$value_types + display_mode <- input$bins_display_mode + + files <- uploadedFiles() + fhir_files <- Filter(function(f) f$type == "fhir" && + f$path %in% input$selected_fhir_files_binning, files) + file_name_map <- setNames( + sapply(fhir_files, `[[`, "name"), + sapply(fhir_files, `[[`, "path") + ) + + # Get all data from matching datasets, tagged by source file + matching_datasets <- names(fhir_data)[grepl(paste0("_", selected_resource_type, "$"), + names(fhir_data))] + + all_data <- do.call(rbind, lapply(matching_datasets, function(dataset_name) { + df <- fhir_data[[dataset_name]] + if (selected_attribute %in% colnames(df)) { + # Extract source file path from dataset name + # dataset_name format is "filename_resourcetype" + source_name <- dataset_name + for (path in names(file_name_map)) { + fname <- tools::file_path_sans_ext(file_name_map[path]) + if (grepl(fname, dataset_name, fixed = TRUE)) { + source_name <- file_name_map[path] + break + } + } + data.frame( + value = df[[selected_attribute]], + source = source_name, + stringsAsFactors = FALSE + ) + } + })) + + if (is.null(all_data) || nrow(all_data) == 0) return(NULL) + + # Assign each value to a bin + all_data$bin <- NA_character_ + for (i in 1:n_bins) { + if (value_type == "text") { + bin_values <- input[[paste0("bin_", i)]] + if (!is.null(bin_values) && length(bin_values) > 0) { + all_data$bin[all_data$value %in% bin_values] <- paste("Bin", i) + } + } else if (value_type == "num") { + bin_max <- input[[paste0("bin_", i)]] + bin_min <- input[[paste0("bin_", i - 1)]] %||% -Inf + all_data$bin[all_data$value <= bin_max & all_data$value > bin_min] <- paste("Bin", i) + } else if (value_type == "bool") { + if (i == 1) all_data$bin[all_data$value == FALSE] <- paste("Bin", i) + if (i == 2) all_data$bin[all_data$value == TRUE] <- paste("Bin", i) + } + } + + all_data <- all_data[!is.na(all_data$bin), ] + if (nrow(all_data) == 0) return(NULL) + + # Count per bin per source + # Count per bin per source + bin_counts <- all_data %>% + count(source, bin, name = "Count") %>% + as.data.frame() + + # Calculate percentages within each source + bin_counts <- bin_counts %>% + group_by(source) %>% + mutate(Percent = round(Count / sum(Count) * 100, 2)) %>% + ungroup() + + # Truncate labels to 15 characters + truncate_label <- function(x, max_chars = 15) { + ifelse(nchar(x) > max_chars, paste0(substr(x, 1, max_chars), "..."), x) + } + + # Build bin labels from selected values + bin_labels <- setNames(sapply(1:n_bins, function(i) { + if (value_type == "text") { + vals <- input[[paste0("bin_", i)]] + if (!is.null(vals) && length(vals) > 0) truncate_label(vals) else paste("Bin", i) + } else if (value_type == "num") { + bin_max <- input[[paste0("bin_", i)]] + bin_min <- input[[paste0("bin_", i - 1)]] %||% -Inf + if (is.infinite(bin_min)) paste0("≤ ", bin_max) else paste0(bin_min, " – ", bin_max) + } else if (value_type == "bool") { + if (i == 1) "False" else "True" + } + }), paste0("Bin ", 1:n_bins)) + + # Apply labels + bin_counts$bin_label <- bin_labels[bin_counts$bin] + bin_counts$bin_label <- factor(bin_counts$bin_label, levels = bin_labels) + + y_var <- if (display_mode == "percent") "Percent" else "Count" + y_label <- if (display_mode == "percent") "Percentage (%)" else "Count" + + ggplot(bin_counts, aes(x = bin_label, y = .data[[y_var]], fill = bin_label)) + + geom_bar(stat = "identity", position = position_dodge(width = 0.9)) + + theme_minimal(base_size = 14) + + labs( + title = paste("Distribution of", selected_attribute, "across bins"), + x = "Bin", + y = y_label, + fill = "Bin" + ) + + scale_fill_brewer(palette = "Set2") + + facet_wrap(~source, ncol = length(unique(bin_counts$source))) + + theme( + legend.position = "bottom", + axis.text.x = element_text(angle = 45, hjust = 1) + ) + }) + + output$fhirResourceTypeUIBinning <- renderUI({ + fhir_data <- fhirDataBinning() + if (is.null(fhir_data) || length(fhir_data) == 0) return(NULL) + + available_resources <- names(fhir_data) + if (length(available_resources) > 0) { + resource_types <- unique(sapply(available_resources, function(x) { + parts <- strsplit(x, "_")[[1]] + if (length(parts) > 1) parts[length(parts)] else x + })) + + selectInput("fhir_resource_to_viz_binning", "Resource Type:", + choices = resource_types, + selected = resource_types[1]) + } + }) + + output$vizSourceSelector <- renderUI({ + files <- uploadedFiles() + if (length(files) == 0) { + return(p("No files uploaded yet.", style = "color:#999; font-size:12px;")) + } + + checkboxGroupInput("viz_selected_sources", "Select Sources:", + choices = setNames( + sapply(files, `[[`, "path"), + sapply(files, `[[`, "name") + ), + selected = sapply(files, `[[`, "path")) + }) + + vizData <- reactive({ + req(input$viz_selected_sources) + + files <- uploadedFiles() + selected <- Filter(function(f) f$path %in% input$viz_selected_sources, files) + bin_type <- input$viz_bin_type + display_mode <- input$viz_display_mode + + results <- lapply(selected, function(f) { + + if (bin_type == "census") { + # Use census Age x Gender bins + # Load census reference directly — independent of Census tab selector + all_files <- uploadedFiles() + census_files <- Filter(function(f) f$type == "census", all_files) + + census_ref <- if (!is.null(input$selected_census_file)) { + loadCensusData(input$selected_census_file) + } else if (length(census_files) > 0) { + loadCensusData(census_files[[1]]$path) + } else { + NULL + } + + if (is.null(census_ref)) return(NULL) + + census_age_labels <- unique(census_ref$Age) + census_gender_labels <- unique(census_ref$Gender) + census_age_labels <- unique(census_ref$Age) + census_gender_labels <- unique(census_ref$Gender) + + tryCatch({ + if (f$type == "census") { + df <- loadCensusData(f$path) + if (is.null(df)) return(NULL) + df$Source <- f$name + + # Calculate percent within this source + df <- df %>% + mutate(x_label = paste(Age, Gender, sep = " · ")) %>% + group_by(x_label) %>% + summarise(Count = sum(Count), .groups = "drop") + + } else if (f$type == "fhir") { + raw <- jsonlite::fromJSON(f$path, simplifyVector = FALSE) + entries <- if (!is.null(raw$resourceType) && raw$resourceType == "Bundle") raw$entry else raw + if (is.null(entries) || length(entries) == 0) return(NULL) + + patients <- Filter(function(e) { + res <- if (!is.null(e$resource)) e$resource else e + !is.null(res$resourceType) && res$resourceType == "Patient" + }, entries) + if (length(patients) == 0) return(NULL) + + records <- lapply(patients, function(e) { + p <- if (!is.null(e$resource)) e$resource else e + list(birthDate = as.character(p$birthDate %||% NA_character_), + gender = as.character(p$gender %||% NA_character_)) + }) + + df <- data.frame( + birthDate = sapply(records, `[[`, "birthDate"), + gender = sapply(records, `[[`, "gender"), + stringsAsFactors = FALSE + ) + + today <- Sys.Date() + df$age_numeric <- sapply(df$birthDate, function(bd) { + if (is.null(bd) || is.na(bd) || !nzchar(trimws(bd))) return(NA_real_) + bd <- sub("T.*$", "", trimws(bd)) + bd_padded <- if (nchar(bd) == 4) paste0(bd, "-01-01") + else if (nchar(bd) == 7) paste0(bd, "-01") + else bd + dob <- tryCatch(as.Date(bd_padded), error = function(e) NA) + if (is.na(dob) || dob >= today || dob < as.Date("1900-01-01")) return(NA_real_) + year_diff <- as.numeric(format(today, "%Y")) - as.numeric(format(dob, "%Y")) + birthday_passed <- format(today, "%m-%d") >= format(dob, "%m-%d") + as.numeric(year_diff - ifelse(birthday_passed, 0L, 1L)) + }) + + df$Age <- bin_age_to_census_groups(df$age_numeric, census_age_labels) + df$Gender <- map_fhir_gender(df$gender, census_gender_labels) + df <- df[!is.na(df$Age) & !is.na(df$Gender), ] + if (nrow(df) == 0) return(NULL) + + df <- df %>% + dplyr::count(Age, Gender, name = "Count") %>% + mutate(x_label = paste(Age, Gender, sep = " · ")) + + } else { + return(NULL) + } + + # Sort x_label by age numerically + age_order <- unique(df$x_label[order(as.numeric(sub("[-+].*", "", + sub(" · .*", "", df$x_label))))]) + df$x_label <- factor(df$x_label, levels = age_order) + + if (display_mode == "percent") { + df <- df %>% mutate(y_val = round(Count / sum(Count) * 100, 2)) + } else { + df <- df %>% mutate(y_val = Count) + } + + # Full label set for uniform x-axis + all_x_labels <- if (bin_type == "census") { + age_order <- unique(census_ref$Age[order(as.numeric(sub("[-+].*", "", census_ref$Age)))]) + genders <- sort(unique(census_ref$Gender)) + as.vector(t(outer(age_order, genders, paste, sep = " · "))) + } else { + # All bin labels from FHIR bins + req(input$fhir_n_bins, input$value_types) + n_bins <- input$fhir_n_bins + value_type <- input$value_types + truncate_label <- function(x, max_chars = 15) { + ifelse(nchar(x) > max_chars, paste0(substr(x, 1, max_chars), "..."), x) + } + sapply(1:n_bins, function(i) { + if (value_type == "text") { + vals <- input[[paste0("bin_", i)]] + if (!is.null(vals) && length(vals) > 0) truncate_label(vals) else paste("Bin", i) + } else if (value_type == "num") { + bin_max <- input[[paste0("bin_", i)]] + bin_min <- input[[paste0("bin_", i - 1)]] %||% -Inf + if (is.infinite(bin_min)) paste0("≤ ", bin_max) else paste0(bin_min, " – ", bin_max) + } else { + if (i == 1) "False" else "True" + } + }) + } + + # Expand to full label set for uniform mode + if (input$x_axis_display_mode == "uniform") { + full_df <- data.frame(x_label = factor(all_x_labels, levels = all_x_labels), + stringsAsFactors = FALSE) + df <- full_df %>% + left_join(df %>% mutate(x_label = as.character(x_label)), + by = "x_label") %>% + mutate( + Count = ifelse(is.na(Count), 0, Count), + y_val = ifelse(is.na(y_val), 0, y_val) + ) + df$x_label <- factor(df$x_label, levels = all_x_labels) + } + + list(name = f$name, data = df) + + }, error = function(e) { + warning(paste("vizData error for", f$name, ":", e$message)) + NULL + }) + + } else if (bin_type == "fhir_bins") { + # Use FHIR in bins configuration + req(input$fhir_resource_to_viz_binning, + input$fhir_category_col_binning, + input$fhir_n_bins, + input$value_types) + + if (f$type != "fhir") return(NULL) + + tryCatch({ + file_data_list <- loadFhirFile(f$path, f$name) + if (is.null(file_data_list) || length(file_data_list) == 0) return(NULL) + + selected_resource_type <- input$fhir_resource_to_viz_binning + selected_attribute <- input$fhir_category_col_binning + n_bins <- input$fhir_n_bins + value_type <- input$value_types + + matching_datasets <- names(file_data_list)[grepl( + paste0("_", selected_resource_type, "$"), names(file_data_list))] + if (length(matching_datasets) == 0) return(NULL) + + all_vals <- do.call(rbind, lapply(matching_datasets, function(dn) { + d <- file_data_list[[dn]] + if (selected_attribute %in% colnames(d)) { + data.frame(value = d[[selected_attribute]], stringsAsFactors = FALSE) + } + })) + if (is.null(all_vals) || nrow(all_vals) == 0) return(NULL) + + # Build bin labels + truncate_label <- function(x, max_chars = 15) { + ifelse(nchar(x) > max_chars, paste0(substr(x, 1, max_chars), "..."), x) + } + + bin_labels <- setNames(sapply(1:n_bins, function(i) { + if (value_type == "text") { + vals <- input[[paste0("bin_", i)]] + if (!is.null(vals) && length(vals) > 0) truncate_label(vals) else paste("Bin", i) + } else if (value_type == "num") { + bin_max <- input[[paste0("bin_", i)]] + bin_min <- input[[paste0("bin_", i - 1)]] %||% -Inf + if (is.infinite(bin_min)) paste0("≤ ", bin_max) else paste0(bin_min, " – ", bin_max) + } else { + if (i == 1) "False" else "True" + } + }), paste0("Bin ", 1:n_bins)) + + # Assign bins + all_vals$bin <- NA_character_ + for (i in 1:n_bins) { + if (value_type == "text") { + bv <- input[[paste0("bin_", i)]] + if (!is.null(bv)) all_vals$bin[all_vals$value %in% bv] <- paste("Bin", i) + } else if (value_type == "num") { + bmax <- input[[paste0("bin_", i)]] + bmin <- input[[paste0("bin_", i - 1)]] %||% -Inf + all_vals$bin[all_vals$value <= bmax & all_vals$value > bmin] <- paste("Bin", i) + } else { + if (i == 1) all_vals$bin[all_vals$value == FALSE] <- paste("Bin", i) + if (i == 2) all_vals$bin[all_vals$value == TRUE] <- paste("Bin", i) + } + } + + all_vals <- all_vals[!is.na(all_vals$bin), ] + if (nrow(all_vals) == 0) return(NULL) + + df <- all_vals %>% + count(bin, name = "Count") %>% + mutate(x_label = bin_labels[bin], + x_label = factor(x_label, levels = bin_labels)) + + if (display_mode == "percent") { + df <- df %>% mutate(y_val = round(Count / sum(Count) * 100, 2)) + } else { + df <- df %>% mutate(y_val = Count) + } + + # Full label set for uniform x-axis + all_x_labels <- if (bin_type == "census") { + age_order <- unique(census_ref$Age[order(as.numeric(sub("[-+].*", "", census_ref$Age)))]) + genders <- sort(unique(census_ref$Gender)) + as.vector(t(outer(age_order, genders, paste, sep = " · "))) + } else { + # All bin labels from FHIR bins + req(input$fhir_n_bins, input$value_types) + n_bins <- input$fhir_n_bins + value_type <- input$value_types + truncate_label <- function(x, max_chars = 15) { + ifelse(nchar(x) > max_chars, paste0(substr(x, 1, max_chars), "..."), x) + } + sapply(1:n_bins, function(i) { + if (value_type == "text") { + vals <- input[[paste0("bin_", i)]] + if (!is.null(vals) && length(vals) > 0) truncate_label(vals) else paste("Bin", i) + } else if (value_type == "num") { + bin_max <- input[[paste0("bin_", i)]] + bin_min <- input[[paste0("bin_", i - 1)]] %||% -Inf + if (is.infinite(bin_min)) paste0("≤ ", bin_max) else paste0(bin_min, " – ", bin_max) + } else { + if (i == 1) "False" else "True" + } + }) + } + + # Expand to full label set for uniform mode + if (input$x_axis_display_mode == "uniform") { + full_df <- data.frame(x_label = factor(all_x_labels, levels = all_x_labels), + stringsAsFactors = FALSE) + df <- full_df %>% + left_join(df %>% mutate(x_label = as.character(x_label)), + by = "x_label") %>% + mutate( + Count = ifelse(is.na(Count), 0, Count), + y_val = ifelse(is.na(y_val), 0, y_val) + ) + df$x_label <- factor(df$x_label, levels = all_x_labels) + } + + list(name = f$name, data = df) + + }, error = function(e) { + warning(paste("vizData fhir_bins error for", f$name, ":", e$message)) + NULL + }) + } + }) + + Filter(Negate(is.null), results) + }) + + output$vizPlotsUI <- renderUI({ + req(vizData()) + dl <- vizData() + if (length(dl) == 0) return(p("No data to display.", style = "color:#999;")) + + if (input$viz_layout_mode == "overlay") { + plotOutput("vizOverlayPlot", height = "500px") + } else { + tagList(lapply(seq_along(dl), function(i) { + plotOutput(paste0("vizPlot_", i), height = "350px") + })) + } + }) + + observe({ + req(vizData()) + dl <- vizData() + display_mode <- isolate(input$viz_display_mode) + y_label <- if (isolate(input$viz_display_mode) == "percent") "Percentage (%)" else "Count" + + # Shared y max + y_max <- max(unlist(lapply(dl, function(x) x$data$y_val)), na.rm = TRUE) + + for (i in seq_along(dl)) { + local({ + idx <- i + d <- dl[[idx]] + + output[[paste0("vizPlot_", idx)]] <- renderPlot({ + ggplot(d$data, aes(x = x_label, y = y_val, fill = sub(".* · ", "", as.character(x_label)))) + + geom_bar(stat = "identity", alpha = 1, colour = "white", linewidth = 0.2) + + scale_y_continuous(limits = c(0, y_max * 1.05)) + + scale_x_discrete(drop = FALSE) + # ← keep empty bins + scale_fill_brewer(palette = "Set2") + + theme_minimal(base_size = 14) + + labs( + title = d$name, + x = NULL, + y = y_label, + fill = "Gender" + ) + + theme( + axis.text.x = element_text(angle = 45, hjust = 1), + legend.position = "bottom", + plot.title = element_text(face = "bold") + ) + }) + }) + } + }) + + output$vizOverlayPlot <- renderPlot({ + req(vizData()) + dl <- vizData() + alpha <- input$viz_overlay_alpha + y_label <- if (input$viz_display_mode == "percent") "Percentage (%)" else "Count" + y_max <- max(unlist(lapply(dl, function(x) x$data$y_val)), na.rm = TRUE) + + # Combine all sources into one data frame, keeping only needed columns + combined <- do.call(rbind, lapply(dl, function(d) { + data.frame( + x_label = as.character(d$data$x_label), + y_val = d$data$y_val, + source = d$name, + stringsAsFactors = FALSE + ) + })) + + # Ensure x_label factor levels are consistent + all_levels <- levels(dl[[1]]$data$x_label) + combined$x_label <- factor(combined$x_label, levels = all_levels) + + ggplot(combined, aes(x = x_label, y = y_val, fill = source)) + + geom_bar(stat = "identity", position = "identity", + alpha = alpha, colour = "white", linewidth = 0.2) + + scale_y_continuous(limits = c(0, y_max * 1.05)) + + scale_x_discrete(drop = FALSE) + + scale_fill_brewer(palette = "Set2") + + theme_minimal(base_size = 14) + + labs( + title = "Overlay Comparison", + x = NULL, + y = y_label, + fill = "Source" + ) + + theme( + axis.text.x = element_text(angle = 45, hjust = 1), + legend.position = "bottom", + plot.title = element_text(face = "bold") + ) + }) + + # Show format selection modal on button click + observeEvent(input$downloadBinsReport, { + req(input$fhir_category_col_binning, input$fhir_resource_to_viz_binning) + + showModal(modalDialog( + title = "Download Bin Report", + radioButtons("bins_report_format", "Report Format:", + choices = c("Separate" = "separate", + "Composite" = "composite"), + selected = "separate"), + footer = tagList( + modalButton("Cancel"), + downloadButton("downloadBinsReportFile", "Download", + class = "btn btn-primary") + ) + )) + }) + + output$downloadBinsReportFile <- downloadHandler( + filename = function() { + attr <- make_safe_id(input$fhir_category_col_binning) + paste0("bin_report_", attr, "_", Sys.Date(), ".json") + }, + content = function(file) { + fhir_data <- fhirDataBinning() + n_bins <- input$fhir_n_bins + value_type <- input$value_types + selected_resource_type <- input$fhir_resource_to_viz_binning + selected_attribute <- input$fhir_category_col_binning + format <- input$bins_report_format + + # Build truncate helper + truncate_label <- function(x, max_chars = 15) { + ifelse(nchar(x) > max_chars, paste0(substr(x, 1, max_chars), "..."), x) + } + + # Build bin labels + bin_labels <- setNames(sapply(1:n_bins, function(i) { + if (value_type == "text") { + vals <- input[[paste0("bin_", i)]] + if (!is.null(vals) && length(vals) > 0) truncate_label(vals) else paste("Bin", i) + } else if (value_type == "num") { + bin_max <- input[[paste0("bin_", i)]] + bin_min <- input[[paste0("bin_", i - 1)]] %||% -Inf + if (is.infinite(bin_min)) paste0("\u2264 ", bin_max) else paste0(bin_min, " \u2013 ", bin_max) + } else { + if (i == 1) "False" else "True" + } + }), paste0("Bin ", 1:n_bins)) + + # Collect all data + matching_datasets <- names(fhir_data)[grepl( + paste0("_", selected_resource_type, "$"), names(fhir_data))] + + all_vals <- do.call(rbind, lapply(matching_datasets, function(dn) { + d <- fhir_data[[dn]] + if (selected_attribute %in% colnames(d)) { + data.frame(value = d[[selected_attribute]], stringsAsFactors = FALSE) + } + })) + + # Assign bins + all_vals$bin <- NA_character_ + for (i in 1:n_bins) { + if (value_type == "text") { + bv <- input[[paste0("bin_", i)]] + if (!is.null(bv)) all_vals$bin[all_vals$value %in% bv] <- paste("Bin", i) + } else if (value_type == "num") { + bmax <- input[[paste0("bin_", i)]] + bmin <- input[[paste0("bin_", i - 1)]] %||% -Inf + all_vals$bin[all_vals$value <= bmax & all_vals$value > bmin] <- paste("Bin", i) + } else { + if (i == 1) all_vals$bin[all_vals$value == FALSE] <- paste("Bin", i) + if (i == 2) all_vals$bin[all_vals$value == TRUE] <- paste("Bin", i) + } + } + + all_vals <- all_vals[!is.na(all_vals$bin), ] + + # Count per bin + bin_counts <- all_vals %>% + count(bin, name = "Count") %>% + mutate(label = bin_labels[bin]) %>% + as.data.frame() + + total_count <- sum(bin_counts$Count) + + if (format == "separate") { + # ── Separate format: one stratifier with one stratum per bin ────────────── + report <- list( + resourceType = "MeasureReport", + status = "complete", + type = "summary", + date = format(Sys.time(), "%Y-%m-%dT%H:%M:%S+00:00"), + period = list( + start = as.character(Sys.Date()), + end = as.character(Sys.Date()) + ), + group = list(list( + population = list(list( + code = list(coding = list(list( + system = "http://terminology.hl7.org/CodeSystem/measure-population", + code = "initial-population" + ))), + count = total_count + )), + stratifier = list(list( + code = list(list(text = selected_attribute)), + stratum = lapply(seq_len(nrow(bin_counts)), function(i) { + list( + value = list(text = bin_counts$label[i]), + population = list(list( + code = list(coding = list(list( + system = "http://terminology.hl7.org/CodeSystem/measure-population", + code = "initial-population" + ))), + count = bin_counts$Count[i] + )) + ) + }) + )) + )) + ) + + } else { + # ── Composite format: one stratifier with component per bin ─────────────── + report <- list( + resourceType = "MeasureReport", + status = "complete", + type = "summary", + date = format(Sys.time(), "%Y-%m-%dT%H:%M:%S+00:00"), + period = list( + start = as.character(Sys.Date()), + end = as.character(Sys.Date()) + ), + group = list(list( + population = list(list( + code = list(coding = list(list( + system = "http://terminology.hl7.org/CodeSystem/measure-population", + code = "initial-population" + ))), + count = total_count + )), + stratifier = list(list( + code = list(list(text = selected_attribute)), + stratum = lapply(seq_len(nrow(bin_counts)), function(i) { + list( + component = list( + list( + code = list(text = selected_attribute), + value = list(text = bin_counts$label[i]) + ) + ), + measureScore = list(value = bin_counts$Count[i]), + population = list(list( + code = list(coding = list(list( + system = "http://terminology.hl7.org/CodeSystem/measure-population", + code = "initial-population" + ))), + count = bin_counts$Count[i] + )) + ) + }) + )) + )) + ) + } + + jsonlite::write_json(report, file, pretty = TRUE, auto_unbox = TRUE) + removeModal() + } + ) +} +# end server + +# 5. Launch the application +shinyApp(ui = ui, server = server) \ No newline at end of file diff --git a/input_examples/MeasureReport-mii-msrpt-summary-report-age-gender-composite-zensus-2022.json b/input_examples/MeasureReport-mii-msrpt-summary-report-age-gender-composite-zensus-2022.json new file mode 100644 index 0000000..17018ba --- /dev/null +++ b/input_examples/MeasureReport-mii-msrpt-summary-report-age-gender-composite-zensus-2022.json @@ -0,0 +1,1359 @@ +{ + "resourceType" : "MeasureReport", + "id" : "mii-msrpt-summary-report-age-gender-composite-zensus-2022", + "text" : { + "status" : "generated", + "div" : "

Generated Narrative: MeasureReport mii-msrpt-summary-report-age-gender-composite-zensus-2022

status: Complete

type: Summary

measure: Measure Summary Report Composite Age Gender CQL

date: 2025-10-16

period: 2022 --> 2022

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+ }] + }, + "value" : { + "text" : "male" + } + }], + "population" : [{ + "code" : { + "coding" : [{ + "system" : "http://terminology.hl7.org/CodeSystem/measure-population", + "code" : "initial-population" + }] + }, + "count" : 236467 + }] + }, + { + "component" : [{ + "code" : { + "coding" : [{ + "system" : "http://loinc.org", + "code" : "46251-5", + "display" : "Age group" + }] + }, + "value" : { + "text" : "90+" + } + }, + { + "code" : { + "coding" : [{ + "system" : "http://loinc.org", + "code" : "99502-7", + "display" : "Recorded sex or gender" + }] + }, + "value" : { + "text" : "female" + } + }], + "population" : [{ + "code" : { + "coding" : [{ + "system" : "http://terminology.hl7.org/CodeSystem/measure-population", + "code" : "initial-population" + }] + }, + "count" : 605005 + }] + }] + }] + }] +} \ No newline at end of file diff --git a/input_examples/age.json b/input_examples/age.json new file mode 100644 index 0000000..5760372 --- /dev/null +++ b/input_examples/age.json @@ -0,0 +1,40 @@ +{ + "Histogram": [ + { + "Category": { + "@value": "18-25" + }, + "Count": { + "@value": 80, + "@type": "xsd:decimal" + } + }, + { + "Category": { + "@value": "26-35" + }, + "Count": { + "@value": 120, + "@type": "xsd:decimal" + } + }, + { + "Category": { + "@value": "36-45" + }, + "Count": { + "@value": 60, + "@type": "xsd:decimal" + } + }, + { + "Category": { + "@value": "46+" + }, + "Count": { + "@value": 40, + "@type": "xsd:decimal" + } + } + ] +} \ No newline at end of file diff --git a/input_examples/csv/patients.csv b/input_examples/csv/patients.csv new file mode 100644 index 0000000..484ed4b --- /dev/null +++ b/input_examples/csv/patients.csv @@ -0,0 +1,101 @@ +subject_id,gender,anchor_age,anchor_year,anchor_year_group,dod +10014729,F,21,2125,2011 - 2013, +10003400,F,72,2134,2011 - 2013,2137-09-02 +10002428,F,80,2155,2011 - 2013, +10032725,F,38,2143,2011 - 2013,2143-03-30 +10027445,F,48,2142,2011 - 2013,2146-02-09 +10037928,F,78,2175,2011 - 2013, +10001725,F,46,2110,2011 - 2013, +10040025,F,64,2143,2011 - 2013,2148-02-07 +10008454,F,26,2110,2011 - 2013, +10020640,F,91,2153,2011 - 2013,2154-02-04 +10014078,F,60,2166,2011 - 2013, +10007795,F,53,2136,2011 - 2013, +10001217,F,55,2157,2011 - 2013, +10019172,F,63,2118,2011 - 2013, +10039831,F,57,2115,2011 - 2013, +10007928,F,59,2129,2011 - 2013, +10019003,F,65,2148,2011 - 2013,2155-12-03 +10002930,F,48,2193,2011 - 2013,2201-12-24 +10010471,F,89,2155,2014 - 2016,2155-12-07 +10027602,F,71,2201,2014 - 2016, +10031757,F,67,2137,2014 - 2016,2137-10-31 +10016742,F,58,2178,2014 - 2016, +10039997,F,67,2134,2014 - 2016, +10012853,F,91,2175,2014 - 2016, +10000032,F,52,2180,2014 - 2016,2180-09-09 +10031404,F,82,2113,2014 - 2016, +10029291,F,50,2123,2014 - 2016, +10005909,F,40,2144,2014 - 2016, +10039708,F,46,2138,2014 - 2016, +10019568,F,59,2120,2014 - 2016, +10020187,F,63,2169,2014 - 2016, +10016810,F,66,2185,2014 - 2016, +10038081,F,63,2115,2014 - 2016,2115-10-12 +10021312,F,55,2113,2014 - 2016, +10006580,F,63,2137,2014 - 2016, +10010867,F,28,2147,2014 - 2016, +10020786,F,86,2189,2014 - 2016, +10020306,F,74,2129,2014 - 2016, +10023239,F,29,2137,2014 - 2016, +10018328,F,83,2154,2014 - 2016, +10008287,F,43,2145,2014 - 2016, +10036156,F,88,2157,2014 - 2016, +10015272,F,78,2137,2014 - 2016, +10022281,M,84,2125,2011 - 2013, +10035631,M,63,2112,2011 - 2013,2116-03-12 +10024043,M,67,2117,2011 - 2013,2117-06-26 +10025612,M,82,2125,2011 - 2013, +10003046,M,64,2154,2011 - 2013, +10021666,M,87,2172,2011 - 2013,2172-04-19 +10018423,M,37,2162,2011 - 2013, +10025463,M,66,2136,2011 - 2013,2137-10-09 +10017492,M,84,2114,2011 - 2013,2116-07-05 +10004422,M,78,2111,2011 - 2013, +10011398,M,67,2146,2011 - 2013, +10021938,M,65,2181,2011 - 2013,2182-10-16 +10009628,M,58,2153,2011 - 2013, +10004457,M,65,2140,2011 - 2013, +10015860,M,53,2186,2011 - 2013, +10021487,M,43,2116,2011 - 2013, +10013049,M,52,2114,2011 - 2013, +10026255,M,66,2200,2011 - 2013,2201-07-13 +10023771,M,70,2113,2011 - 2013, +10023117,M,53,2170,2011 - 2013,2175-07-20 +10022041,M,64,2187,2011 - 2013, +10005348,M,76,2128,2011 - 2013, +10009035,M,28,2161,2011 - 2013, +10018081,M,79,2133,2011 - 2013,2134-10-28 +10038933,M,34,2148,2011 - 2013, +10037975,M,60,2185,2014 - 2016,2185-01-22 +10035185,M,70,2120,2014 - 2016, +10014354,M,60,2146,2014 - 2016, +10022880,M,66,2177,2014 - 2016, +10004720,M,61,2183,2014 - 2016,2186-11-17 +10019385,M,44,2180,2014 - 2016, +10029484,M,64,2160,2014 - 2016, +10037861,M,77,2115,2014 - 2016,2117-03-24 +10026406,M,45,2129,2014 - 2016, +10007818,M,69,2146,2014 - 2016,2146-07-12 +10020740,M,56,2150,2014 - 2016, +10038999,M,45,2131,2014 - 2016, +10004235,M,47,2196,2014 - 2016, +10022017,M,59,2189,2014 - 2016, +10002495,M,81,2141,2014 - 2016, +10018845,M,91,2184,2014 - 2016,2184-11-22 +10020944,M,72,2131,2014 - 2016,2131-04-28 +10016150,M,69,2142,2014 - 2016, +10005866,M,57,2146,2014 - 2016,2149-11-21 +10026354,M,34,2119,2014 - 2016, +10019917,M,44,2182,2014 - 2016, +10019777,M,51,2187,2014 - 2016,2187-04-29 +10005817,M,66,2132,2014 - 2016,2135-01-19 +10009049,M,56,2174,2014 - 2016, +10015931,M,87,2176,2014 - 2016,2177-03-29 +10006053,M,52,2111,2014 - 2016,2111-11-15 +10012552,M,78,2140,2014 - 2016, +10004733,M,51,2174,2014 - 2016, +10021118,M,62,2161,2014 - 2016, +10018501,M,83,2141,2014 - 2016, +10007058,M,48,2167,2014 - 2016, +10038992,M,70,2185,2014 - 2016, diff --git a/input_examples/csv/people-100.csv b/input_examples/csv/people-100.csv new file mode 100644 index 0000000..0901ebd --- /dev/null +++ b/input_examples/csv/people-100.csv @@ -0,0 +1,101 @@ +Index,User Id,First Name,Last Name,Sex,Email,Phone,Date of birth,Job Title +1,88F7B33d2bcf9f5,Shelby,Terrell,Male,elijah57@example.net,001-084-906-7849x73518,1945-10-26,Games developer +2,f90cD3E76f1A9b9,Phillip,Summers,Female,bethany14@example.com,214.112.6044x4913,1910-03-24,Phytotherapist +3,DbeAb8CcdfeFC2c,Kristine,Travis,Male,bthompson@example.com,277.609.7938,1992-07-02,Homeopath +4,A31Bee3c201ef58,Yesenia,Martinez,Male,kaitlinkaiser@example.com,584.094.6111,2017-08-03,Market researcher +5,1bA7A3dc874da3c,Lori,Todd,Male,buchananmanuel@example.net,689-207-3558x7233,1938-12-01,Veterinary surgeon +6,bfDD7CDEF5D865B,Erin,Day,Male,tconner@example.org,001-171-649-9856x5553,2015-10-28,Waste management officer +7,bE9EEf34cB72AF7,Katherine,Buck,Female,conniecowan@example.com,+1-773-151-6685x49162,1989-01-22,Intelligence analyst +8,2EFC6A4e77FaEaC,Ricardo,Hinton,Male,wyattbishop@example.com,001-447-699-7998x88612,1924-03-26,Hydrogeologist +9,baDcC4DeefD8dEB,Dave,Farrell,Male,nmccann@example.net,603-428-2429x27392,2018-10-06,Lawyer +10,8e4FB470FE19bF0,Isaiah,Downs,Male,virginiaterrell@example.org,+1-511-372-1544x8206,1964-09-20,"Engineer, site" +11,BF0BbA03C29Bb3b,Sheila,Ross,Female,huangcathy@example.com,895.881.4746,2008-03-20,Advertising account executive +12,F738c69fB34E62E,Stacy,Newton,Male,rayleroy@example.org,710.673.3213x80335,1980-10-20,Warden/ranger +13,C03fDADdAadAdCe,Mandy,Blake,Male,jefferynoble@example.org,(992)466-1305x4947,2007-12-08,"Scientist, clinical (histocompatibility and immunogenetics)" +14,b759b74BD1dE80d,Bridget,Nash,Female,mercedes44@example.com,(216)627-8359,2004-06-28,Social worker +15,1F0B7D65A00DAF9,Crystal,Farmer,Male,pmiranda@example.org,+1-024-377-5391,1992-03-09,Agricultural consultant +16,50Bb061cB30B461,Thomas,Knight,Female,braunpriscilla@example.net,+1-360-880-0766,2006-02-18,Sport and exercise psychologist +17,D6dbA5308fEC4BC,Maurice,Rangel,Male,sheenabanks@example.com,(246)187-4969,2004-08-20,Secretary/administrator +18,311D775990f066d,Frank,Meadows,Male,gbrewer@example.org,429.965.3902x4447,2008-09-16,Audiological scientist +19,7F7E1BAcb0C9AFf,Alvin,Paul,Male,gilbertdonaldson@example.com,219.436.0887x07551,1949-05-12,"Teacher, adult education" +20,88473e15D5c3cD0,Jared,Mitchell,Female,jcortez@example.com,+1-958-849-6781,1921-01-18,Paediatric nurse +21,b31D271F8c200AB,Jacqueline,Norton,Female,carias@example.net,819.309.7679x59173,1952-10-09,"Scientist, marine" +22,42F4BdA841aBadC,Colleen,Hatfield,Female,fknox@example.org,638.584.1090,1949-10-14,Commercial horticulturist +23,cBbBcA0FCA3C4Bc,Randy,Barnes,Male,huangbill@example.org,001-960-629-7164x67214,1947-12-30,Outdoor activities/education manager +24,f1f89173353aD90,Janice,Rhodes,Female,juarezdominique@example.net,001-249-314-9742x6996,1999-11-01,Drilling engineer +25,c5B09fb33e8bA0A,Alfred,Mcneil,Female,cassandramorris@example.com,(468)276-9509x53058,1993-05-28,Systems analyst +26,c9F2282C40BEC1E,Sean,Levine,Male,sallymiller@example.net,4915828504,2010-10-09,"Conservation officer, nature" +27,9c1bc7EC53Fb7cE,Louis,Payne,Male,bsullivan@example.net,6232695307,1916-01-29,Counsellor +28,ddEc50e2A2e3a2B,Brittney,Vega,Female,ayalajose@example.net,945-739-8686,1932-10-31,Recycling officer +29,66F096D36Ebae11,Judy,Buckley,Male,irosales@example.net,001-654-208-1241x52830,1963-07-28,Art gallery manager +30,F0fE2faAd78F8b5,Norman,Weber,Male,mconrad@example.com,223.002.0429,1957-05-21,Gaffer +31,5d2feAfbdCAA6B5,Isaiah,Camacho,Female,jimblake@example.org,001-536-544-3367,1966-04-07,Food technologist +32,cDa5F303fCd6dEa,Jacqueline,Gallagher,Male,nsampson@example.net,(247)762-8934,1999-02-25,Building services engineer +33,8Ef7DBfcaB02b6B,Bonnie,Andrews,Female,caitlin24@example.net,+1-253-987-2776x9161,1953-12-21,Seismic interpreter +34,6Dec5b5542F8ed8,Brandon,Schmidt,Female,mconley@example.net,+1-386-673-1465x006,1931-05-12,"Engineer, biomedical" +35,3Fb8a7f68e12784,Jackson,Sparks,Female,reynoldsdarryl@example.net,(137)908-3129x65035,1980-11-18,Set designer +36,035eff50B9A0F24,Melody,Cook,Male,jeannovak@example.org,(826)792-7381,1963-06-25,Research scientist (life sciences) +37,aa614aAE4B7Cf0C,Leonard,Hurst,Male,clinton78@example.org,941-038-0427x38800,1938-03-13,"Accountant, chartered management" +38,ACcde95AAe3e6cC,Gene,Rich,Female,luisdeleon@example.org,+1-356-818-6604x89537,1946-08-22,"Surveyor, quantity" +39,b6a35de5CB6fc25,Cynthia,Wiggins,Female,rosariodave@example.org,(110)858-2437x70190,1984-01-27,Outdoor activities/education manager +40,e92A191E345fA3A,Tanya,Mckinney,Female,vickihouston@example.com,(830)774-9002x086,2003-03-12,Information systems manager +41,7D0AcBF6CCac3fd,Matthew,Stone,Female,evelyn31@example.org,952-381-6360,2017-08-23,"Scientist, clinical (histocompatibility and immunogenetics)" +42,CEFA7BBCef013AE,Kirk,Walsh,Female,stephenfuller@example.org,001-826-496-5529x8661,2009-04-08,Accounting technician +43,9edBC94aE7cA22a,Willie,Vang,Female,haleymathews@example.net,741.168.6854x067,1978-02-02,Management consultant +44,fFe7BAA737aDbe2,Miguel,Hill,Female,tyrone56@example.org,5247842945,1930-08-26,Make +45,5F2f3fAca8B0946,Darren,Andrews,Male,lhernandez@example.com,(975)799-4261,1997-10-04,Retail banker +46,6bFcfc3cc1BC6B4,Haley,Pugh,Female,molly03@example.org,(746)182-6137x2453,1980-09-16,Commissioning editor +47,f3BD2cBF7eEb6df,Danielle,Estrada,Female,jvang@example.org,(890)374-9518x772,1930-07-09,"Accountant, chartered management" +48,Ee4eB129dC7913A,Becky,Brady,Male,erikmueller@example.org,(390)002-0863,1957-06-27,Seismic interpreter +49,dBCEf340C3657Eb,Caitlyn,Frey,Male,rivasdominique@example.org,805-021-3965x46344,1968-01-26,Jewellery designer +50,E47FB71DD9ACCd9,Joshua,Sweeney,Male,daisymcgee@example.net,875.994.2100x535,1954-07-28,"Education officer, museum" +51,eA3fDd79BE9f0E7,Heidi,Escobar,Female,staffordtravis@example.net,601-155-3065x1131,1931-09-25,Estate manager/land agent +52,aF0eE4547Bc025c,Brian,Oconnell,Female,saralong@example.net,952-283-1423x733,1911-10-23,Physiotherapist +53,9F5DeD7aD228F5a,Beverly,Esparza,Female,iphelps@example.net,+1-327-578-8754x6771,1930-12-09,Passenger transport manager +54,D3Fa0220dDE4d36,Nathaniel,Rivas,Female,roberto29@example.com,(655)887-2040x37888,1908-11-17,Call centre manager +55,60FdBFd5e7BE8fF,Debra,Payne,Female,yolanda07@example.org,001-731-525-8400x52593,1927-08-20,Special educational needs teacher +56,D8bF5Ab2b98caff,Mackenzie,Rocha,Female,abbottyvette@example.net,4225525458,1980-10-21,Museum/gallery exhibitions officer +57,CD8d33aA25bc8BB,Courtney,Watkins,Female,ochang@example.org,210.683.2761x5883,2003-12-07,Pension scheme manager +58,Fac3BfFf0A3d03c,Fred,Olsen,Female,amyanderson@example.com,497-774-3053,1910-04-10,Archaeologist +59,e552D7ddafe1FFb,Ryan,Nelson,Female,qnorman@example.org,956.330.2951,1924-05-02,Historic buildings inspector/conservation officer +60,0f8deedb629A5f6,Grace,Phelps,Male,clarkeangela@example.net,(034)867-8827x6777,1909-10-15,Petroleum engineer +61,bB9e49E506F65ed,Shari,Daugherty,Male,kalvarado@example.org,001-951-655-4798x6124,1944-11-24,Curator +62,Ed724605A403D91,Kelli,Garner,Male,jodyvincent@example.org,995.000.4213x0982,2010-01-17,Retail banker +63,0aBE5ACb18E0c10,Jackie,Bennett,Male,hutchinsonkirk@example.com,001-740-937-0846x0087,1915-11-11,Neurosurgeon +64,5D2cb63CaAF53f6,Leslie,Conway,Female,floreschristina@example.org,795.782.4384x555,1983-11-06,Chiropractor +65,Ee6974f90eeCe18,Harold,Barnett,Female,nathan65@example.org,+1-026-265-6392,1943-03-15,"Biochemist, clinical" +66,cEf02C076afa07f,Larry,Harper,Male,maria32@example.org,+1-244-630-3792x4121,2021-05-05,"Scientist, water quality" +67,9Df5Ba591bF3EFf,Mike,Ward,Female,imccullough@example.com,116-729-5046,1967-11-09,Hydrologist +68,3faB1CBfEFBDdD4,Brittney,Rubio,Female,corey92@example.com,593.976.2528,1959-12-24,"Biochemist, clinical" +69,Ebcefdf75eCb0a9,Frank,Pineda,Male,daltoncalvin@example.net,(035)961-5060x9182,1926-03-10,Hospital pharmacist +70,e75e5DBfcb68887,Sandra,Wu,Male,ubanks@example.com,+1-096-606-6454x067,1925-04-28,Warehouse manager +71,6a53a8D41dDF6de,Ryan,Benton,Male,lopezdebbie@example.org,+1-695-557-9948x485,2020-10-06,Physiological scientist +72,F0d3bD1aaf9E3Bc,Tamara,Hull,Male,meagan39@example.net,017.665.3744x7944,1933-01-31,English as a second language teacher +73,5bC87340799FBD0,Jean,Ritter,Female,kristina76@example.com,(954)060-1066,1985-08-06,Financial trader +74,dBfA17Aaf16b4ab,Veronica,Briggs,Female,weissbridget@example.com,+1-521-589-2387x48490,1974-06-08,Structural engineer +75,c935b7Eb6FA0B0F,Kim,Andrews,Female,wpetersen@example.org,7677125383,1990-11-15,"Biochemist, clinical" +76,b3e15e65Ca2CcBf,Tina,Cunningham,Male,wongmary@example.org,079-907-5051,1956-11-29,Race relations officer +77,dade3452F0c32FD,Jonathon,Atkinson,Male,gailfrench@example.net,874-037-2032x932,2011-07-19,"Psychologist, forensic" +78,AdEd6cfD85DeC46,Jermaine,Reid,Female,vpaul@example.com,(742)214-8691,1974-08-18,Newspaper journalist +79,DAf111987098ae4,Regina,Stevens,Male,xpoole@example.net,891-359-2684,2011-11-28,Public house manager +80,6e6a5b885F6496d,Terrence,Huff,Male,cassandra80@example.org,221.800.6408x5416,1944-02-27,Careers information officer +81,12DCb4ED8E01D5C,Tyler,Foley,Female,johnathan72@example.org,001-386-469-3075x8030,1908-09-19,Economist +82,E1cB5cA8CA7CC0a,Andrew,Waters,Male,nhall@example.net,+1-376-865-2765x3351,1948-05-14,Jewellery designer +83,AedDfaE8Cf49F07,Reginald,Stephenson,Male,erikaball@example.net,+1-832-500-6044x475,2010-02-08,Contracting civil engineer +84,bff9853aFAeF772,Douglas,Reese,Female,nixonvanessa@example.net,001-834-660-8312x9864,1961-11-11,Higher education lecturer +85,E883773cA5219Be,Helen,Williamson,Female,melvin08@example.net,001-377-726-4229,1911-08-11,"Lecturer, further education" +86,CB19EafEbBfF9eC,Mario,Vaughn,Male,oblake@example.com,160-144-5039x12276,1990-07-08,Research scientist (life sciences) +87,5834700fbEd2771,Chelsea,Dickson,Male,johnnyhendricks@example.net,001-698-651-0138x18588,1958-05-13,"Teacher, early years/pre" +88,2b0Ab1Dc9E01D7E,Dustin,Bailey,Male,pbarron@example.net,+1-965-621-1157x345,1908-08-22,Travel agency manager +89,3f3a3D89ad042Dd,Harry,Medina,Female,olsenmalik@example.net,+1-451-099-5805,1947-08-24,Technical sales engineer +90,9425E2F38C408ef,Kathy,Haney,Female,teresa37@example.com,(164)105-8456,1955-09-02,Charity fundraiser +91,F0aeC9c2759F3C6,Alison,Nixon,Female,zmiles@example.net,3506680871,1941-07-10,Patent attorney +92,d6EA619A7C4aA95,Jamie,Hardy,Female,sheenadouglas@example.com,(900)803-9295x11533,1994-07-17,"Conservator, furniture" +93,2A33E7Cad1bb0F5,Melody,Cox,Female,evan90@example.org,(626)520-5080x3511,1974-07-30,Dance movement psychotherapist +94,d181FFB7d3E68bb,Xavier,Cole,Male,nicolas90@example.org,8164259975,1938-11-29,Financial planner +95,feaBf8dAE0C0d6F,Dillon,Guzman,Female,angelanavarro@example.net,971-992-4521,1942-04-01,Air broker +96,5eFda7caAeB260E,Dennis,Barnes,Female,bmartin@example.org,001-095-524-2112x257,1954-07-30,Software engineer +97,CCbFce93d3720bE,Steve,Patterson,Female,latasha46@example.net,001-865-478-5157,1932-04-29,Barrister +98,2fEc528aFAF0b69,Wesley,Bray,Male,regina11@example.org,995-542-3004x76800,1994-12-28,Police officer +99,Adc7ad9B6e4A1Fe,Summer,Oconnell,Female,alexiscantrell@example.org,001-273-685-6932x092,2012-04-12,Broadcast journalist +100,b8D0aD3490FC7e1,Mariah,Bernard,Male,pcopeland@example.org,(341)594-6554x44657,2016-11-15,IT sales professional diff --git a/input_examples/fhir/hapi_batch1.json b/input_examples/fhir/hapi_batch1.json new file mode 100644 index 0000000..673cccf --- /dev/null +++ b/input_examples/fhir/hapi_batch1.json @@ -0,0 +1,8189 @@ +{ + "resourceType": "Bundle", + "id": "c1364268-d5a8-4f6c-a470-249f6afd8966", + "meta": { + "lastUpdated": "2025-07-23T12:29:52.255+00:00" + }, + "type": "searchset", + "link": [ { + "relation": "self", + "url": "https://hapi.fhir.org/baseR4/Patient?_count=50&_format=json&_include=Patient%3A*&_revinclude=*" + }, { + "relation": "next", + "url": "https://hapi.fhir.org/baseR4?_getpages=c1364268-d5a8-4f6c-a470-249f6afd8966&_getpagesoffset=50&_count=50&_format=json&_pretty=true&_include=Patient%3A*&_bundletype=searchset" + } ], + "entry": [ { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597296", + "resource": { + "resourceType": "Patient", + "id": "597296", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:35:22.962+00:00", + "source": "#gQiXZQOED0rCZpve" + }, + "text": { + "status": "generated", + "div": "
Fozzy BEAR
Address1 Muppets Way
New York NY USA
" + }, + "name": [ { + "family": "Bear", + "given": [ "Fozzy" ] + } ], + "telecom": [ { + "system": "phone", + "value": "0405687522", + "use": "mobile" + } ], + "gender": "male", + "address": [ { + "use": "work", + "line": [ "1 Muppets Way" ], + "city": "New York", + "state": "NY", + "country": "USA" + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597297", + "resource": { + "resourceType": "Patient", + "id": "597297", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:36:37.036+00:00", + "source": "#GjFq9E2Z8Odv115n" + }, + "text": { + "status": "generated", + "div": "
John DOE
Address123 fake street
noWhere noneyah nowheres
Date of birth05 September 2017
" + }, + "name": [ { + "family": "doe", + "given": [ "John" ] + } ], + "telecom": [ { + "system": "phone", + "value": "123-456-7890", + "use": "mobile" + } ], + "gender": "male", + "birthDate": "2017-09-05T22:00:00.000Z", + "address": [ { + "line": [ "123 fake street" ], + "city": "noWhere", + "state": "noneyah", + "postalCode": "11111", + "country": "nowheres" + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597298", + "resource": { + "resourceType": "Patient", + "id": "597298", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:36:57.354+00:00", + "source": "#UiwiXLtrJ5yffAN3" + }, + "text": { + "status": "generated", + "div": "
Fozzy BEAR
Address1 Muppets Way
New York NY USA
Date of birth31 December 1999
" + }, + "name": [ { + "family": "Bear", + "given": [ "Fozzy" ] + } ], + "telecom": [ { + "system": "phone", + "value": "0405687522", + "use": "mobile" + } ], + "gender": "male", + "birthDate": "1999-12-31", + "address": [ { + "use": "work", + "line": [ "1 Muppets Way" ], + "city": "New York", + "state": "NY", + "country": "USA" + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597301", + "resource": { + "resourceType": "Patient", + "id": "597301", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:38:27.166+00:00", + "source": "#Fi6vSpGmOIEtxKm7" + }, + "text": { + "status": "generated", + "div": "
\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Name Christine Eko\n Chalmers \n
Address 120 Chalmers St Surry Hills
Contacts Home: unknown. Work: (03) 5555 6473
Id MRN: 999999 (Acme Healthcare)
\n
" + }, + "identifier": [ { + "use": "usual", + "type": { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0203", + "code": "MR" + } ] + }, + "system": "urn:oid:1.2.36.146.595.217.0.1", + "value": "12345", + "period": { + "start": "2001-05-06" + }, + "assigner": { + "display": "Acme Healthcare" + } + } ], + "active": true, + "name": [ { + "use": "official", + "family": "Ekos", + "given": [ "Christine", "Christine" ] + }, { + "use": "usual", + "given": [ "Christine" ] + }, { + "use": "maiden", + "family": "Ekos", + "given": [ "Christine", "Christine" ], + "period": { + "end": "2002" + } + } ], + "telecom": [ { + "use": "home" + }, { + "system": "phone", + "value": "(03) 5555 6473", + "use": "work", + "rank": 1 + }, { + "system": "phone", + "value": "(03) 3410 5613", + "use": "mobile", + "rank": 2 + }, { + "system": "phone", + "value": "(03) 5555 8834", + "use": "old", + "period": { + "end": "2014" + } + } ], + "gender": "male", + "birthDate": "1974-12-25", + "_birthDate": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/patient-birthTime", + "valueDateTime": "1974-12-25T14:35:45-05:00" + } ] + }, + "deceasedBoolean": false, + "address": [ { + "use": "home", + "type": "both", + "text": "534 Erewhon St PeasantVille, Rainbow, Vic 3999", + "line": [ "534 Erewhon St" ], + "city": "PleasantVille", + "district": "Rainbow", + "state": "Vic", + "postalCode": "3999", + "period": { + "start": "1974-12-25" + } + } ], + "contact": [ { + "relationship": [ { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0131", + "code": "N" + } ] + } ], + "name": { + "family": "du Marché", + "_family": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/humanname-own-prefix", + "valueString": "VV" + } ] + }, + "given": [ "Bénédicte" ] + }, + "telecom": [ { + "system": "phone", + "value": "+33 (237) 998327" + } ], + "address": { + "use": "home", + "type": "both", + "line": [ "534 Erewhon St" ], + "city": "PleasantVille", + "district": "Rainbow", + "state": "Vic", + "postalCode": "3999", + "period": { + "start": "1974-12-25" + } + }, + "gender": "female", + "period": { + "start": "2012" + } + } ], + "managingOrganization": { + "reference": "Organization/250369" + } + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597303", + "resource": { + "resourceType": "Patient", + "id": "597303", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:40:39.936+00:00", + "source": "#8FGOIppWpWAWemJX" + }, + "text": { + "status": "generated", + "div": "
Nisarg PATEL
Identifiernpatel431
" + }, + "identifier": [ { + "system": "http://fhirtutorial.example/patient", + "value": "npatel431" + } ], + "name": [ { + "family": "Patel", + "given": [ "Nisarg" ] + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597304", + "resource": { + "resourceType": "Patient", + "id": "597304", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:40:56.035+00:00", + "source": "#4EGx5czntbTynpBO" + }, + "text": { + "status": "generated", + "div": "
Nisarg PATEL
Identifiernpatel431
" + }, + "identifier": [ { + "system": "http://fhirtutorial.example/patient", + "value": "npatel431" + } ], + "name": [ { + "family": "Patel", + "given": [ "Nisarg" ] + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597305", + "resource": { + "resourceType": "Patient", + "id": "597305", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:44:12.221+00:00", + "source": "#eq9Nmio5KIX2UKre" + }, + "text": { + "status": "generated", + "div": "
\n\t\t\t\n\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\n\t\t\t\t\n\t\t\t
NamePeter James \n Chalmers ("Jim")\n
Address534 Erewhon, Pleasantville, Vic, 3999
ContactsHome: unknown. Work: (03) 5555 6473
IdMRN: 12345 (Acme Healthcare)
\n\t\t
" + }, + "identifier": [ { + "use": "usual", + "type": { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0203", + "code": "MR" + } ] + }, + "system": "urn:oid:1.2.36.146.595.217.0.1", + "value": "12345", + "period": { + "start": "2001-05-06" + }, + "assigner": { + "display": "Acme Healthcare" + } + } ], + "active": true, + "name": [ { + "use": "official", + "family": "Thompson", + "given": [ "Blair", "Richard" ] + } ], + "gender": "male", + "birthDate": "1994-08-31", + "_birthDate": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/patient-birthTime", + "valueDateTime": "1974-12-25T14:35:45-05:00" + } ] + }, + "deceasedBoolean": false, + "address": [ { + "use": "home", + "type": "both", + "text": "534 Erewhon St PeasantVille, Rainbow, Vic 3999", + "line": [ "534 Erewhon St" ], + "city": "PleasantVille", + "district": "Rainbow", + "state": "Vic", + "postalCode": "3999", + "period": { + "start": "1974-12-25" + } + } ], + "contact": [ { + "relationship": [ { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0131", + "code": "N" + } ] + } ], + "name": { + "family": "du Marché", + "_family": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/humanname-own-prefix", + "valueString": "VV" + } ] + }, + "given": [ "Bénédicte" ] + }, + "telecom": [ { + "system": "phone", + "value": "+33 (237) 998327" + } ], + "address": { + "use": "home", + "type": "both", + "line": [ "534 Erewhon St" ], + "city": "PleasantVille", + "district": "Rainbow", + "state": "Vic", + "postalCode": "3999", + "period": { + "start": "1974-12-25" + } + }, + "gender": "female", + "period": { + "start": "2012" + } + } ], + "managingOrganization": { + "reference": "Organization/22856" + } + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597307", + "resource": { + "resourceType": "Patient", + "id": "597307", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:47:19.631+00:00", + "source": "#JV7luZSjLCXsiaBi" + }, + "text": { + "status": "generated", + "div": "
\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
Name Christine Eko\n Chalmers \n
Address 120 Chalmers St Surry Hills
Contacts Home: unknown. Work: (03) 5555 6473
Id MRN: 999999 (Acme Healthcare)
\n
" + }, + "identifier": [ { + "use": "usual", + "type": { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0203", + "code": "MR" + } ] + }, + "system": "urn:oid:1.2.36.146.595.217.0.1", + "value": "9999999", + "period": { + "start": "2001-05-06" + }, + "assigner": { + "display": "Acme Healthcare" + } + } ], + "active": true, + "name": [ { + "use": "official", + "family": "Ekos", + "given": [ "Christine", "Christine" ] + }, { + "use": "usual", + "given": [ "Christine" ] + }, { + "use": "maiden", + "family": "Ekos", + "given": [ "Christine", "Christine" ], + "period": { + "end": "2002" + } + } ], + "telecom": [ { + "use": "home" + }, { + "system": "phone", + "value": "(03) 5555 6473", + "use": "work", + "rank": 1 + }, { + "system": "phone", + "value": "(03) 3410 5613", + "use": "mobile", + "rank": 2 + }, { + "system": "phone", + "value": "(03) 5555 8834", + "use": "old", + "period": { + "end": "2014" + } + } ], + "gender": "male", + "birthDate": "1974-12-25", + "_birthDate": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/patient-birthTime", + "valueDateTime": "1974-12-25T14:35:45-05:00" + } ] + }, + "deceasedBoolean": false, + "address": [ { + "use": "home", + "type": "both", + "text": "534 Erewhon St PeasantVille, Rainbow, Vic 3999", + "line": [ "534 Erewhon St" ], + "city": "PleasantVille", + "district": "Rainbow", + "state": "Vic", + "postalCode": "3999", + "period": { + "start": "1974-12-25" + } + } ], + "contact": [ { + "relationship": [ { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0131", + "code": "N" + } ] + } ], + "name": { + "family": "du Marché", + "_family": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/humanname-own-prefix", + "valueString": "VV" + } ] + }, + "given": [ "Bénédicte" ] + }, + "telecom": [ { + "system": "phone", + "value": "+33 (237) 998327" + } ], + "address": { + "use": "home", + "type": "both", + "line": [ "534 Erewhon St" ], + "city": "PleasantVille", + "district": "Rainbow", + "state": "Vic", + "postalCode": "3999", + "period": { + "start": "1974-12-25" + } + }, + "gender": "female", + "period": { + "start": "2012" + } + } ], + "managingOrganization": { + "reference": "Organization/250369" + } + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597308", + "resource": { + "resourceType": "Patient", + "id": "597308", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:50:15.311+00:00", + "source": "#IviJSWqZZa88TjJE" + }, + "text": { + "status": "generated", + "div": "
Nisarg PATEL
Identifiernpatel431
" + }, + "identifier": [ { + "system": "http://fhirtutorial.example/patient", + "value": "npatel431" + } ], + "name": [ { + "family": "Patel", + "given": [ "Nisarg" ] + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597309", + "resource": { + "resourceType": "Patient", + "id": "597309", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T01:52:03.414+00:00", + "source": "#FTehhQaGIUueOpuX" + }, + "text": { + "status": "generated", + "div": "
John DOE
Identifierphoecke3
Address123 fake street
noWhere noneyah nowheres
Date of birth05 September 2017
" + }, + "identifier": [ { + "value": "phoecke3" + } ], + "name": [ { + "family": "doe", + "given": [ "John" ] + } ], + "telecom": [ { + "system": "phone", + "value": "123-456-7890", + "use": "mobile" + } ], + "gender": "male", + "birthDate": "2017-09-05T22:00:00.000Z", + "address": [ { + "line": [ "123 fake street" ], + "city": "noWhere", + "state": "noneyah", + "postalCode": "11111", + "country": "nowheres" + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597302", + "resource": { + "resourceType": "Patient", + "id": "597302", + "meta": { + "versionId": "3", + "lastUpdated": "2020-02-04T01:57:06.436+00:00", + "source": "#BrCsFDqE8boqIsBq" + }, + "text": { + "status": "generated", + "div": "
Moss TEST2 EL BIAD
Identifier12345
" + }, + "identifier": [ { + "value": "12345" + } ], + "name": [ { + "use": "official", + "family": "El Biad", + "given": [ "Moss", "TEST2" ] + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597310", + "resource": { + "resourceType": "Patient", + "id": "597310", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T02:02:43.912+00:00", + "source": "#YZGvN78qxkkgymwe" + }, + "text": { + "status": "generated", + "div": "
Moss EL BIAD
Identifier12345
Date of birth01 January 1978
" + }, + "identifier": [ { + "use": "usual", + "type": { + "coding": [ { + "system": "http://terminology.hl7.org/CodeSystem/v2-0203", + "code": "MR" + } ] + }, + "system": "urn:oid:1.2.36.146.595.217.0.1", + "value": "12345", + "period": { + "start": "2001-05-06" + }, + "assigner": { + "display": "Acme Healthcare" + } + } ], + "active": true, + "name": [ { + "use": "official", + "family": "El Biad", + "given": [ "Moss" ] + } ], + "gender": "male", + "birthDate": "1978-01-01", + "_birthDate": { + "extension": [ { + "url": "http://hl7.org/fhir/StructureDefinition/patient-birthTime", + "valueDateTime": "1978-01-01T14:35:45-05:00" + } ] + } + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597311", + "resource": { + "resourceType": "Patient", + "id": "597311", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T02:06:43.622+00:00", + "source": "#3lGOI6RByBT49qXL" + }, + "text": { + "status": "generated", + "div": "
Zhiyu LIU
" + }, + "name": [ { + "family": "Liu", + "given": [ "Zhiyu" ] + } ] + }, + "search": { + "mode": "match" + } + }, { + "fullUrl": "https://hapi.fhir.org/baseR4/Patient/597312", + "resource": { + "resourceType": "Patient", + "id": "597312", + "meta": { + "versionId": "1", + "lastUpdated": "2020-02-04T02:08:13.057+00:00", + "source": "#f9jT4FB89sLntQEi" + }, + "text": { + "status": "generated", + "div": "
Greg JUNIPER
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Neil CHARLES
Identifierncharles3
Address12345 Six Flags
Las Vegas Nevada US
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ying YU
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Los Angeles CA
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Neil CHARLES
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Neil CHARLES
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Ethan WU
Identifierewu41
Address444 Orange St
San Diego CA usa
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Neil CHARLES
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Bob ALEXANDER
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Caleb CUSHING
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Bob ALEXANDER
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Caleb CUSHING
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Bob ALEXANDER
Identifierc0538cfe-7f06-4f45-8947-f72e2bd4aaa9
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Caleb CUSHING
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Bob ALEXANDER
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Caleb CUSHING
Identifier21066ac8-f9ef-4d04-8f9d-38ddc5d7fa3a
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Bob ALEXANDER
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Caleb CUSHING
Identifierd024de9e-d156-4b92-ad05-18cb567e7aaf
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Bob ALEXANDER
Identifier45e98499-55c7-4035-b6b4-70bf5c298eeb
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Caleb CUSHING
Identifier96cc98ad-0f49-48f9-80c3-56183316cc04
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Bob ALEXANDER
Identifier6904bc5c-dbb3-4c9f-9d6e-18fc9631d8a7
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Caleb CUSHING
Identifier84a2de6f-98f4-4b3a-b7a5-c5c52286757d
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Tighe BODALLA Esquire
Identifierljones91
Address365 North 200 West
St. George Utah USA
Date of birth14 March 1954
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Tony STARK
Identifierbgray38
Address200 Park Avenue
Manhattan NY USA
Date of birth29 May 1970
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Mark BIGGERS
Identifierxliu724
Address3100 Haven Street
Redwood City California
Date of birth27 November 1998
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ying YU
Address123
Los Angeles CA
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Dio BRANDO
Identifierjpark965
Address11 PACIFIC AVENUE
APT 200
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atlanta GA
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Zhiyu LIU
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Ethan WU
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Bob ALEXANDER
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Caleb CUSHING
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Tighe BODALLA Esquire
Identifierljones91
Address365 North 200 West
St. George Utah USA
Date of birth14 March 1954
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Tony STARK
Identifierbgray38
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Manhattan NY USA
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Mark BIGGERS
Identifierxliu724
Address3100 Haven Street
Redwood City California
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ying YU
Address123
Los Angeles CA
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Dio BRANDO
Identifierjpark965
Address11 PACIFIC AVENUE
APT 200
SEATTLE WA USA
Date of birth11 March 1900
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Greg JUNIPER
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yiiiing YUUUU
Identifieryyu413
Address123
Los Angeles CA
Date of birth15 February 1995
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