\r\n
\r\n Loading...
: <>}\r\n {error ? (\r\n \r\n An error occured retriving the doucment outline\r\n
\r\n ) : (\r\n <>\r\n )}\r\n {/* \r\n \r\n {loading ? \r\n Annual Data Report Chapters\r\n \r\n \r\n \r\n \r\n \r\n
\r\n ) : (\r\n <>\r\n );\r\n};\r\n\r\nexport default MobileChapter;\r\n","import React from 'react'\r\nimport NIDDKLogo from './NIDDK_USRDS_logo.svg'\r\nimport MobileNav from './MobileNav'\r\nimport MobileChapter from './MobileChapter'\r\nimport Navbar from \"react-bootstrap/Navbar\";\r\nimport Container from \"react-bootstrap/Container\";\r\nimport './Logo.scss';\r\n\r\nconst Logo = () => {\r\n return (\r\n Loading...
: <>}\r\n {error ? (\r\n \r\n An error occured retriving the doucment outline\r\n
\r\n ) : (\r\n <>\r\n )}\r\n\r\n \r\n
\r\n )\r\n}\r\n\r\nexport default Logo","export default __webpack_public_path__ + \"static/media/icon-dot-gov.8f8f40ed.svg\";","export default __webpack_public_path__ + \"static/media/icon-https.42f84b9c.svg\";","import React from 'react';\r\nimport { useState } from 'react';\r\nimport Collapse from 'react-bootstrap/Collapse';\r\n\r\nimport './Header.scss';\r\nimport Logo from '../nav/Logo';\r\nimport us_flag_small from \"./us_flag_small.png\"\r\nimport icon_dot_gov from \"./icon-dot-gov.svg\";\r\nimport icon_https from \"./icon-https.svg\"\r\n\r\nfunction Header() {\r\nconst [open, setOpen] = useState(false);\r\n\r\n return ( \r\n \r\n
\r\n \r\n
\r\n \r\n \r\n \r\n \r\n \r\n \r\n
\r\n \r\n Skip to Main Content\r\n \r\n
\r\n \r\n 
\r\n
\r\n \r\n \r\n\r\n
\r\n \r\n setOpen(!open)}\r\n aria-controls=\"hhsbanner-collapse-text\"\r\n aria-expanded={open}\r\n variant=\"link\"\r\n className=\"hhsbanner-link\"\r\n >\r\n Here's how you know \r\n \r\n
\r\n \r\n \r\n \r\n \r\n
\r\n `\r\n : \"\";\r\n tooltipStr += sn;\r\n // q3\r\n tooltipStr += `Upper quartile: ${stringFormatter(\r\n p.point.q3,\r\n decimalPlaces\r\n )}
`;\r\n // median\r\n tooltipStr += `Median: ${stringFormatter(\r\n p.point.median,\r\n decimalPlaces\r\n )}
`;\r\n // q1\r\n tooltipStr += `Lower quartile: ${stringFormatter(\r\n p.point.q1,\r\n decimalPlaces\r\n )}
`;\r\n // mean\r\n if (p.point.mean !== null && p.point.mean !== undefined) {\r\n tooltipStr += `Mean: ${stringFormatter(\r\n p.point.mean,\r\n decimalPlaces\r\n )}`;\r\n }\r\n return tooltipStr;\r\n })\r\n );\r\n }\r\n return [this.x].concat(\r\n this.points.map((p) => {\r\n const color = `● `;\r\n const val = p.y === undefined ? p.point.value : p.y;\r\n const sn =\r\n p.series.name && p.series.name !== \"Series 1\"\r\n ? \"\" + p.series.name + \": \"\r\n : \"\";\r\n if (p.y >= 10000) {\r\n return (\r\n color +\r\n sn +\r\n val.toLocaleString(undefined, {\r\n maximumFractionDigits: mapTooltopFormats[decimalPlaces],\r\n minimumFractionDigits: mapTooltopFormats[decimalPlaces],\r\n })\r\n );\r\n } else {\r\n return (\r\n color + sn + val.toFixed(mapTooltopFormats[decimalPlaces]) + \"\"\r\n );\r\n }\r\n })\r\n );\r\n }\r\n };\r\n};\r\n\r\nconst stringFormatter = (value, decimalPlaces) => {\r\n if (isNaN(value)) return ``;\r\n if (value >= 10000) {\r\n return value.toLocaleString(undefined, {\r\n maximumFractionDigits: mapTooltopFormats[decimalPlaces],\r\n minimumFractionDigits: mapTooltopFormats[decimalPlaces],\r\n });\r\n } else {\r\n return value.toFixed(mapTooltopFormats[decimalPlaces]) + \"\";\r\n }\r\n};\r\n\r\nexport const yAxisFormatter = function (decimalPlaces) {\r\n return function () {\r\n if (this.value >= 10000) {\r\n return this.value.toLocaleString(undefined, {\r\n maximumFractionDigits: mapTooltopFormats[decimalPlaces],\r\n minimumFractionDigits: mapTooltopFormats[decimalPlaces],\r\n });\r\n } else {\r\n return this.value.toFixed(mapTooltopFormats[decimalPlaces]) + \"\";\r\n }\r\n };\r\n};\r\n\r\nexport const sharedTooltipFormatter = function (\r\n decimalPlaces,\r\n chartType,\r\n reversed\r\n) {\r\n return function () {\r\n let tt = `${this.x.name ? this.x.name : \"\"}`;\r\n if (this.x.parent && this.x.parent.name) {\r\n tt += `, ${this.x.parent.name}`;\r\n }\r\n tt += \"
\";\r\n const labels = this.points.map((p, i) => {\r\n const yVal = p.y.toFixed(mapTooltopFormats[decimalPlaces]);\r\n return i\r\n ? `● ${p.series.name}: ${yVal}
`\r\n : `● ${p.series.name}: ${yVal}`;\r\n });\r\n if (!reversed) {\r\n for (let i = this.points.length - 1; i > -1; i--) {\r\n tt += labels[i];\r\n }\r\n } else {\r\n for (let i = 0; i < this.points.length; i++) {\r\n if (i === 0) {\r\n tt += labels[i] + `
`;\r\n } else {\r\n tt += labels[i];\r\n }\r\n }\r\n }\r\n return tt;\r\n };\r\n};\r\n\r\nexport const mapTooltopFormats = {\r\n // eslint-disable-next-line\r\n [\"0.0001\"]: 4,\r\n // eslint-disable-next-line\r\n [\"0.001\"]: 3,\r\n // eslint-disable-next-line\r\n [\"0.01\"]: 2,\r\n // eslint-disable-next-line\r\n [\"0.1\"]: 1,\r\n // eslint-disable-next-line\r\n [\"1\"]: 0,\r\n};\r\n","import { toolTipFormatter } from \"./numberFormatters\";\r\n\r\nexport function removeNoneCircles(data, { tab, toggle }, isExporting) {\r\n return function () {\r\n if (isExporting) {\r\n const circles =\r\n window.document.getElementsByClassName(\"None-graph-circle\");\r\n for (let i = 0; i < circles.length; i++) {\r\n circles[i].setAttribute(\"display\", \"none\");\r\n }\r\n const delCircles =\r\n window.document.getElementsByClassName(\"delete-my-circle\");\r\n for (let i = 0; i < delCircles.length; i++) {\r\n delCircles[i].setAttribute(\"display\", \"none\");\r\n }\r\n }\r\n\r\n if (\r\n data.chartType.indexOf(\"VENN\") > -1 &&\r\n this.series.length &&\r\n this.series[0].data.filter((x) => x.labelText === \"None\").length\r\n ) {\r\n const noneDataSet = this.series[0].data.filter(\r\n (x) => x.labelText === \"None\"\r\n )[0];\r\n let figId = data.figureNumber.replace(/\\W/g, \"\");\r\n if (noneDataSet.panel) {\r\n figId += noneDataSet.panel.replace(/\\W/g, \"\");\r\n }\r\n\r\n const noneValue = noneDataSet.noneValue;\r\n const noneVal = toolTipFormatter(\r\n data.dataLabelDecimalPlaces,\r\n \"VENN\"\r\n ).call({\r\n y: noneValue,\r\n series: {\r\n name: \"None\",\r\n },\r\n point: {\r\n value: noneValue,\r\n noneValue: noneValue,\r\n options: {\r\n labelText: \"None\",\r\n },\r\n },\r\n key: \"None\",\r\n });\r\n\r\n if (!isExporting) {\r\n reCenterVenn(this);\r\n }\r\n\r\n const textX = this.chartWidth / 2 - 25;\r\n const { fig, exp } = noneAdjust(data.figureNumber);\r\n let textY = this.chartHeight - 45 + fig;\r\n if (isExporting) {\r\n textY += exp;\r\n }\r\n const txt = this.renderer\r\n .text(noneVal, textX, textY, true)\r\n .attr({\r\n fill: \"black\",\r\n stroke: \"black\",\r\n \"stroke-width\": 1,\r\n class: \"a-none-circle-\" + figId,\r\n })\r\n .css({\r\n fontSize: \"14px\",\r\n });\r\n txt.add();\r\n\r\n processSpecialLabels();\r\n }\r\n };\r\n}\r\n\r\nconst processSpecialLabels = () => {\r\n // adjust figure 4.6 labels\r\n const classNames = [\r\n \"LipidloweringagentsCADCKDn47517\",\r\n \"LipidloweringagentsAMINoCKDn19092\",\r\n \"LipidloweringagentsAMICKDn12002\",\r\n \"WarfarinDOACsNVAFNoCKDn77624\",\r\n \"BetablockersAMIAllDialysisn29539\",\r\n \"LipidloweringagentsAMITransplantn3634\",\r\n \"BetablockersHFTransplantn10234\",\r\n \"LipidloweringagentsPADTransplantn12326\",\r\n \"DMMedicareAdvantageCKD\",\r\n \"DMPercentageofcoststotal30855B\",\r\n ];\r\n for (let i = 0; i < classNames.length; i++) {\r\n const elems = document.getElementsByClassName(classNames[i]);\r\n for (let j = 0; j < elems.length; j++) {\r\n const txts = elems[j].getElementsByTagName(\"text\");\r\n for (let k = 0; k < txts.length; k++) {\r\n if (\r\n classNames[i] === \"WarfarinDOACsNVAFNoCKDn77624\" ||\r\n classNames[i] === \"LipidloweringagentsAMITransplantn3634\"\r\n ) {\r\n txts[k].setAttribute(\"transform\", \"translate(82, 0)\");\r\n } else if (\r\n classNames[i] === \"BetablockersAMIAllDialysisn29539\" ||\r\n classNames[i] === \"BetablockersHFTransplantn10234\" ||\r\n classNames[i] === \"LipidloweringagentsPADTransplantn12326\"\r\n ) {\r\n txts[k].setAttribute(\"transform\", \"translate(100, 0)\");\r\n } else if (\r\n classNames[i] === \"DMPercentageofcoststotal30855B\" ||\r\n classNames[i] === \"DMMedicareAdvantageCKD\"\r\n ) {\r\n txts[k].setAttribute(\"transform\", \"translate(45, 50)\");\r\n } else {\r\n txts[k].setAttribute(\"transform\", \"translate(85, 90)\");\r\n }\r\n }\r\n }\r\n }\r\n};\r\n\r\nconst noneAdjust = (figNum) => {\r\n switch (figNum) {\r\n case \"Figure 1.6\":\r\n return { fig: -30, exp: 30 };\r\n case \"Figure 4.6\":\r\n return { fig: 42, exp: -15 };\r\n case \"Figure 6.1\":\r\n return { fig: 35, exp: -35 };\r\n case \"Figure 8.4\":\r\n return { fig: 40, exp: -10 };\r\n default:\r\n return { fig: 0, exp: 0 };\r\n }\r\n};\r\n\r\nconst reCenterVenn = (chart) => {\r\n var figChart = document.getElementsByClassName(\"venn-adjust\");\r\n for (let i = 0; i < figChart.length; i++) {\r\n let figChartArea = figChart[i].getElementsByClassName(\r\n \"highcharts-series-group\"\r\n )[0];\r\n let figChartLabels = figChart[i].getElementsByClassName(\r\n \"highcharts-data-labels\"\r\n )[0];\r\n let figToolTips =\r\n figChart[i].getElementsByClassName(\"highcharts-tooltip\")[0];\r\n let { x, width } = figChartArea.getBBox();\r\n const cWidth = chart.chartWidth;\r\n\r\n let sign = \"-\";\r\n\r\n if (x + width / 2 < cWidth / 2) {\r\n sign = \"\";\r\n }\r\n\r\n let newX = x + width / 2 - cWidth / 2;\r\n figChartArea.setAttribute(\"transform\", `translate(${sign + newX}, 0)`);\r\n\r\n let figLabels = figChartLabels.getElementsByTagName(\"g\");\r\n for (let j = 0; j < figLabels.length; j++) {\r\n let txtLbl = figLabels[j].getElementsByTagName(\"text\");\r\n for (let k = 0; k < txtLbl.length; k++) {\r\n txtLbl[k].setAttribute(\"transform\", `translate(${sign + newX}, 0)`);\r\n }\r\n }\r\n\r\n if (!figToolTips) {\r\n const config = { childList: true, subtree: true };\r\n\r\n const root = figChart[i].getElementsByClassName(\"highcharts-root\")[0];\r\n\r\n const cb = function (mutList, obs) {\r\n if (figChart[i]) {\r\n figChartArea = figChart[i].getElementsByClassName(\r\n \"highcharts-series-group\"\r\n )[0];\r\n const bbBoxArea = figChartArea.getBBox();\r\n x = bbBoxArea.x;\r\n width = bbBoxArea.width;\r\n if (x + width / 2 < cWidth / 2) {\r\n sign = \"\";\r\n } else {\r\n sign = \"-\";\r\n }\r\n newX = x + width / 2 - cWidth / 2;\r\n\r\n if (figChart[i]) {\r\n figToolTips =\r\n figChart[i].getElementsByClassName(\"highcharts-tooltip\")[0];\r\n if (figToolTips) {\r\n let ttBoxes = figToolTips.getElementsByTagName(\"path\");\r\n for (let j = 0; j < ttBoxes.length; j++) {\r\n ttBoxes[j].setAttribute(\r\n \"transform\",\r\n `translate(${sign + newX}, 0)`\r\n );\r\n }\r\n let txt = figToolTips.getElementsByTagName(\"text\");\r\n for (let j = 0; j < txt.length; j++) {\r\n txt[j].setAttribute(\r\n \"transform\",\r\n `translate(${sign + newX}, 0)`\r\n );\r\n }\r\n }\r\n } else {\r\n obs.disconnect();\r\n }\r\n }\r\n };\r\n\r\n const obs = new MutationObserver(cb);\r\n obs.observe(root, config);\r\n } else {\r\n figChartArea = figChart[i].getElementsByClassName(\r\n \"highcharts-series-group\"\r\n )[0];\r\n const bbBoxArea = figChartArea.getBBox();\r\n x = bbBoxArea.x;\r\n width = bbBoxArea.width;\r\n if (x + width / 2 < cWidth / 2) {\r\n sign = \"\";\r\n } else {\r\n sign = \"-\";\r\n }\r\n newX = x + width / 2 - cWidth / 2;\r\n\r\n let ttBoxes = figToolTips.getElementsByTagName(\"path\");\r\n for (let j = 0; j < ttBoxes.length; j++) {\r\n ttBoxes[j].setAttribute(\"transform\", `translate(${sign + newX}, 0)`);\r\n }\r\n let txt = figToolTips.getElementsByTagName(\"text\");\r\n for (let j = 0; j < txt.length; j++) {\r\n txt[j].setAttribute(\"transform\", `translate(${sign + newX}, 0)`);\r\n }\r\n }\r\n }\r\n};\r\n","const highchartsVennExportFix = function (data) {\r\n return function ({ dataRows, ...evt }) {\r\n evt.preventDefault()\r\n if (data.chartType.indexOf('VENN') > -1 && this.series.length) {\r\n const firstSeries = this.series[0].data\r\n\r\n for (let i = 0; i < dataRows.length; i++) {\r\n // header\r\n let seriesIdx = i - 1\r\n if (i === 0) {\r\n continue;\r\n }\r\n\r\n // weird xls export fix\r\n if (dataRows.length - firstSeries.length === 2) {\r\n if (i === 1) {\r\n continue;\r\n }\r\n seriesIdx = i - 2\r\n }\r\n\r\n let exportRow = dataRows[i]\r\n let seriesRow = firstSeries[seriesIdx]\r\n\r\n if (seriesRow.labelText === 'None') {\r\n exportRow[0] = 'None'\r\n exportRow[1] = seriesRow.noneValue\r\n } else {\r\n if (seriesRow.sets.length > 1 && seriesRow.sets.some(x => x === 'None')) {\r\n exportRow[0] = null\r\n exportRow[1] = null\r\n } else {\r\n exportRow[0] = seriesRow.labelText\r\n }\r\n }\r\n }\r\n }\r\n\r\n }\r\n}\r\n\r\nexport default highchartsVennExportFix","import React from 'react'\r\nimport { replaceToggle, replaceTab } from '../../../../../utils/dynamicHeader'\r\n\r\nexport const replaceHdr = (title, currentTab, currentToggle) => {\r\n let replacement = replaceToggle(currentToggle, title)\r\n replacement = replaceTab(currentTab, replacement)\r\n return replacement\r\n}\r\n\r\n\r\nconst Header = ({ figureData, currentToggle, slug, currentTab }) => {\r\n return (\r\n <>\r\n
\r\n \r\n
\r\n
\r\n \r\n )\r\n}\r\n\r\nexport default Header","import { isArray, mergeWith } from \"lodash\";\r\n\r\nexport const nonNullMerge = (src, ...args) => {\r\n return mergeWith(src, ...args, (a, b) => (b === null ? a : undefined));\r\n};\r\n\r\nexport const arrayReplaceMerge = (src, ...args) => {\r\n return mergeWith(src, ...args, (a, b, key, obj) => {\r\n const rr = isArray(a) && isArray(b) ? [...b] : undefined;\r\n return rr;\r\n });\r\n};\r\n\r\nexport const defaultMerge = (src, ...args) => {\r\n return mergeWith(src, ...args, (a, b) => {\r\n if (b === null) {\r\n return a;\r\n } else if (isArray(a) && isArray(b)) {\r\n return b;\r\n }\r\n });\r\n};\r\n","import { RESPONSIVE_BREAK } from \"../../../../../utils/constants\";\r\nimport {\r\n mapTooltopFormats,\r\n sharedTooltipFormatter,\r\n} from \"../../../../../utils/numberFormatters\";\r\n\r\nexport const LBL_ROT_AMT = -90;\r\n\r\nexport const setAreaChartOptions = (initialOptions, data, reverse) => {\r\n initialOptions = enable100PercentageSharedToolTip(\r\n initialOptions,\r\n data.dataLabelDecimalPlaces,\r\n !!reverse\r\n );\r\n initialOptions.yAxis.reversedStacks = !!reverse;\r\n initialOptions.plotOptions.area = {\r\n ...initialOptions.plotOptions.area,\r\n marker: {\r\n enabled: false,\r\n },\r\n states: {\r\n hover: {\r\n enabled: false,\r\n },\r\n },\r\n };\r\n initialOptions.xAxis.crosshair = {\r\n color: \"black\",\r\n };\r\n return initialOptions;\r\n};\r\n\r\nexport const rotateSecondXAxis = (\r\n initialOptions,\r\n useResponsiveBreak,\r\n rotateSingleCategory\r\n) => {\r\n if (!useResponsiveBreak || window.innerWidth < RESPONSIVE_BREAK) {\r\n if (\r\n initialOptions.xAxis.categories.every((cat) => typeof cat === \"object\") &&\r\n !rotateSingleCategory\r\n ) {\r\n initialOptions.xAxis.labels.rotation = LBL_ROT_AMT;\r\n initialOptions.xAxis.labels.groupedOptions = [\r\n {\r\n rotation: 0,\r\n },\r\n ];\r\n }\r\n if (\r\n !rotateSingleCategory &&\r\n initialOptions.xAxis.categories.every((cat) => typeof cat === \"string\")\r\n ) {\r\n initialOptions.xAxis.labels.rotation = 0;\r\n }\r\n }\r\n\r\n return initialOptions;\r\n};\r\n\r\nexport const percentStackChartFix = (initialOptions) => {\r\n initialOptions.yAxis.showLastLabel = false;\r\n initialOptions.yAxis.tickPositioner = function () {\r\n return this.tickPositions.concat([105]);\r\n };\r\n};\r\n\r\nexport const enable100PercentageSharedToolTip = (\r\n initialOptions,\r\n decimalPlaces,\r\n reversed\r\n) => {\r\n initialOptions.tooltip.split = false;\r\n initialOptions.tooltip.shared = true;\r\n initialOptions.tooltip.formatter = sharedTooltipFormatter(\r\n decimalPlaces,\r\n null,\r\n reversed\r\n );\r\n initialOptions.tooltip.valueDecimals = mapTooltopFormats[decimalPlaces];\r\n return initialOptions;\r\n};\r\n\r\nexport const fullStackLabelsOnlyFormatter = function () {\r\n const allVisible = this.axis.chart.series\r\n .map((x) => x.visible)\r\n .every((y) => y);\r\n if (!allVisible) {\r\n return \"\";\r\n } else {\r\n return this.total.toFixed(1) + \"\";\r\n }\r\n};\r\n\r\nexport function xAxisLabelsFormatter() {\r\n if (typeof this.value === \"object\") {\r\n return Number(this.value.userOptions).toFixed(1) + \"\";\r\n } else {\r\n return Number(this.value).toFixed(1) + \"\";\r\n }\r\n}\r\n","import { isArray } from \"lodash\";\r\nimport { RESPONSIVE_BREAK } from \"../../../../../utils/constants\";\r\nimport { nonNullMerge } from \"./customMerge\";\r\nimport { enable100PercentageSharedToolTip } from \"./figureSpecificOptions\";\r\n\r\nconst mixinCommands = (initialOptions, data, figJson) => {\r\n initialOptions = enableSharedTooltip(initialOptions, data, figJson);\r\n initialOptions = breakWordsXAxis(initialOptions, figJson);\r\n initialOptions = addSeriesOptions(initialOptions, data, figJson);\r\n return initialOptions;\r\n};\r\n\r\n// put newlines on xaxis labels between words\r\nexport const breakWordsXAxis = (initialOptions, figJson) => {\r\n if (figJson.BREAKWORDSXAXIS) {\r\n if (\r\n figJson.BREAKWORDSXAXIS.responsiveBreak === \"lg\" &&\r\n window.innerWidth >= RESPONSIVE_BREAK\r\n ) {\r\n initialOptions.xAxis.categories = initialOptions.xAxis.categories.map(\r\n (x) => {\r\n // if this is a multi-xaxis\r\n if (x.name && isArray(x.categories)) {\r\n return {\r\n name: x.name,\r\n categories: x.categories.map((y) => y.replace(/ /g, \"\r\n {figureData.figureNumber}\r\n \r\n {replaceHdr(figureData.title, currentTab, currentToggle)}
\r\n \")),\r\n };\r\n }\r\n return x.replace(/ /g, \"
\");\r\n }\r\n );\r\n }\r\n }\r\n return initialOptions;\r\n};\r\n\r\nexport const enableSharedTooltip = (initialOptions, data, figJson) => {\r\n if (figJson.ENABLESHAREDTOOLTIP) {\r\n initialOptions = enable100PercentageSharedToolTip(\r\n initialOptions,\r\n figJson.ENABLESHAREDTOOLTIP.decimalPlaces ?? data.dataLabelDecimalPlaces,\r\n figJson.ENABLESHAREDTOOLTIP.reversed\r\n );\r\n }\r\n return initialOptions;\r\n};\r\n\r\nexport const addSeriesOptions = (initialOptions, data, figJson) => {\r\n if (figJson.SERIES) {\r\n if (figJson.SERIES.name) {\r\n const seriesNames = Object.keys(figJson.SERIES.name);\r\n if (\r\n seriesNames.length === 1 &&\r\n seriesNames.find((x) => x === \"default\")\r\n ) {\r\n const defaultSeries = figJson.SERIES.name.default;\r\n initialOptions.series[0] = nonNullMerge(\r\n initialOptions.series[0],\r\n defaultSeries\r\n );\r\n } else {\r\n for (let seriesName of seriesNames) {\r\n const seriesOptions = figJson.SERIES.name[seriesName];\r\n let namedSeries = initialOptions.series.find(\r\n (x) => x.name === seriesName\r\n );\r\n namedSeries = nonNullMerge(namedSeries, seriesOptions);\r\n }\r\n }\r\n }\r\n }\r\n return initialOptions;\r\n};\r\n\r\nexport default mixinCommands;\r\n","import { RESPONSIVE_BREAK } from \"../../../../../utils/constants\";\r\nimport { nonNullMerge } from \"./customMerge\";\r\nimport mixinCommands from \"./mixinCommands\";\r\n\r\nconst panelMixins = (initialOptions, data, json, { tab, toggle, panel }) => {\r\n if (json?.PANEL) {\r\n if (json.PANEL[panel]) {\r\n initialOptions = nonNullMerge(initialOptions, json.PANEL[panel]);\r\n // TODO: temporary hack\r\n if (json.PANEL[panel].series) {\r\n initialOptions.series = json.PANEL[panel].series;\r\n }\r\n\r\n if (window.innerWidth < RESPONSIVE_BREAK && json.PANEL[panel].MOBILE) {\r\n initialOptions = nonNullMerge(initialOptions, json.PANEL[panel].MOBILE);\r\n }\r\n\r\n initialOptions = mixinCommands(initialOptions, data, json.PANEL[panel]);\r\n } else if (json.PANEL.default) {\r\n initialOptions = nonNullMerge(initialOptions, json.PANEL.default);\r\n\r\n initialOptions = mixinCommands(initialOptions, data, json.PANEL.default);\r\n }\r\n }\r\n return initialOptions;\r\n};\r\n\r\nexport default panelMixins;\r\n","import {\r\n toolTipFormatter,\r\n yAxisFormatter,\r\n} from \"../../../../../utils/numberFormatters\";\r\nimport { nonNullMerge } from \"./customMerge\";\r\nimport { enable100PercentageSharedToolTip } from \"./figureSpecificOptions\";\r\nimport mixinCommands from \"./mixinCommands\";\r\n\r\nconst toggleMixins = (initialOptions, data, json, { tab, toggle, panel }) => {\r\n if (json.TOGGLE) {\r\n if (json.TOGGLE[toggle]) {\r\n initialOptions = nonNullMerge(initialOptions, json.TOGGLE[toggle]);\r\n initialOptions = mixinCommands(initialOptions, json.TOGGLE[toggle], data);\r\n\r\n if (json.TOGGLE[toggle].YAXISFORMATTER) {\r\n initialOptions.yAxis.labels.formatter = yAxisFormatter(\r\n json.TOGGLE[toggle].YAXISFORMATTER.decimalPlaces\r\n );\r\n }\r\n\r\n if (json.TOGGLE[toggle].TOOLTIPFORMATTER) {\r\n initialOptions.tooltip.formatter = toolTipFormatter(\r\n json.TOGGLE[toggle].TOOLTIPFORMATTER.decimalPlaces,\r\n data.chartType\r\n );\r\n }\r\n\r\n if (json.TOGGLE[toggle].ENABLESHAREDTOOLTIP) {\r\n initialOptions = enable100PercentageSharedToolTip(\r\n initialOptions,\r\n json.TOGGLE[toggle].ENABLESHAREDTOOLTIP.decimalPlaces ??\r\n data.dataLabelDecimalPlaces,\r\n json.TOGGLE[toggle].ENABLESHAREDTOOLTIP.reversed\r\n );\r\n }\r\n\r\n initialOptions = mixinCommands(initialOptions, data, json.TOGGLE[toggle]);\r\n } else if (json.TOGGLE.default) {\r\n initialOptions = nonNullMerge(initialOptions, json.TOGGLE.default);\r\n initialOptions = mixinCommands(initialOptions, json.TOGGLE.default, data);\r\n\r\n if (json.TOGGLE.default.YAXISFORMATTER) {\r\n initialOptions.yAxis.labels.formatter = yAxisFormatter(\r\n json.TOGGLE.default.YAXISFORMATTER.decimalPlaces\r\n );\r\n }\r\n\r\n if (json.TOGGLE.default.TOOLTIPFORMATTER) {\r\n initialOptions.tooltip.formatter = toolTipFormatter(\r\n json.TOGGLE.default.TOOLTIPFORMATTER.decimalPlaces,\r\n data.chartType\r\n );\r\n }\r\n\r\n if (json.TOGGLE.default.ENABLESHAREDTOOLTIP) {\r\n initialOptions = enable100PercentageSharedToolTip(\r\n initialOptions,\r\n json.TOGGLE.default.ENABLESHAREDTOOLTIP.decimalPlaces ??\r\n data.dataLabelDecimalPlaces,\r\n json.TOGGLE.default.ENABLESHAREDTOOLTIP.reversed\r\n );\r\n }\r\n\r\n initialOptions = mixinCommands(initialOptions, data, json.TOGGLE.default);\r\n }\r\n }\r\n return initialOptions;\r\n};\r\n\r\nexport default toggleMixins;\r\n","import { set } from \"lodash\";\r\nimport {\r\n toolTipFormatter,\r\n yAxisFormatter,\r\n} from \"../../../../../utils/numberFormatters\";\r\nimport { nonNullMerge } from \"./customMerge\";\r\nimport mixinCommands from \"./mixinCommands\";\r\nimport panelMixins from \"./panelMixins\";\r\nimport toggleMixins from \"./toggleMixins\";\r\n\r\nconst tabToggleMixins = (\r\n initialOptions,\r\n data,\r\n json,\r\n { tab, toggle, panel }\r\n) => {\r\n if (json?.TAB) {\r\n if (json.TAB[tab]) {\r\n initialOptions = nonNullMerge(initialOptions, json.TAB[tab]);\r\n\r\n if (json.TAB[tab].REPLACE) {\r\n set(\r\n initialOptions,\r\n json.TAB[tab].REPLACE.path,\r\n json.TAB[tab].REPLACE.value\r\n );\r\n }\r\n\r\n if (json.TAB[tab].YAXISFORMATTER) {\r\n initialOptions.yAxis.labels.formatter = yAxisFormatter(\r\n json.TAB[tab].YAXISFORMATTER.decimalPlaces\r\n );\r\n }\r\n if (json.TAB[tab].TOOLTIPFORMATTER) {\r\n initialOptions.tooltip.formatter = toolTipFormatter(\r\n json.TAB[tab].TOOLTIPFORMATTER.decimalPlaces,\r\n data.chartType\r\n );\r\n }\r\n\r\n initialOptions = mixinCommands(initialOptions, data, json.TAB[tab]);\r\n\r\n if (json.TAB[tab].TOGGLE)\r\n initialOptions = toggleMixins(initialOptions, data, json.TAB[tab], {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n\r\n if (json.TAB[tab].PANEL) {\r\n initialOptions = panelMixins(initialOptions, data, json.TAB[tab], {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n }\r\n } else if (json.TAB.default) {\r\n initialOptions = nonNullMerge(initialOptions, json.TAB.default);\r\n\r\n if (json.TAB.default.YAXISFORMATTER) {\r\n initialOptions.yAxis.labels.formatter = yAxisFormatter(\r\n json.TAB.default.YAXISFORMATTER.decimalPlaces\r\n );\r\n }\r\n if (json.TAB.default.TOOLTIPFORMATTER) {\r\n initialOptions.tooltip.formatter = toolTipFormatter(\r\n json.TAB.default.TOOLTIPFORMATTER.decimalPlaces,\r\n data.chartType\r\n );\r\n }\r\n\r\n initialOptions = mixinCommands(initialOptions, data, json.TAB.default);\r\n\r\n if (json.TAB.default.TOGGLE)\r\n initialOptions = toggleMixins(initialOptions, data, json.TAB.default, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n\r\n if (json.TAB.default.PANEL) {\r\n initialOptions = panelMixins(initialOptions, data, json.TAB.default, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n }\r\n }\r\n }\r\n return initialOptions;\r\n};\r\n\r\nexport default tabToggleMixins;\r\n","/* eslint-disable no-template-curly-in-string */\r\nimport { get, set } from \"lodash\";\r\nimport merge from \"lodash/merge\";\r\nimport { RESPONSIVE_BREAK } from \"../../../../../utils/constants\";\r\nimport {\r\n toolTipFormatter,\r\n yAxisFormatter,\r\n} from \"../../../../../utils/numberFormatters\";\r\nimport { replaceHdr } from \"../graphComponents/Header\";\r\nimport { nonNullMerge } from \"./customMerge\";\r\nimport {\r\n fullStackLabelsOnlyFormatter,\r\n rotateSecondXAxis,\r\n setAreaChartOptions,\r\n xAxisLabelsFormatter,\r\n} from \"./figureSpecificOptions\";\r\nimport mixinCommands from \"./mixinCommands\";\r\nimport panelMixins from \"./panelMixins\";\r\nimport tabToggleMixins from \"./tabToggleMixins\";\r\nimport toggleMixins from \"./toggleMixins\";\r\n\r\nconst mixins = (initialOptions, data, { tab, toggle, panel }) => {\r\n try {\r\n let subtitle = \"\";\r\n let exportSubtitle = \"\";\r\n if (data.tab) {\r\n const selectedTab = data.tab.find((tb) => tb.tab === tab);\r\n if (selectedTab?.values) {\r\n const selectedToggle = selectedTab.values.find(\r\n (tog) => tog.toggle === toggle\r\n );\r\n initialOptions = nonNullMerge(initialOptions, selectedToggle.values);\r\n }\r\n }\r\n\r\n if (data.toggle) {\r\n const selectedToggle = data.toggle.find((tg) => tg.toggle === toggle);\r\n initialOptions = nonNullMerge(initialOptions, selectedToggle.values);\r\n }\r\n\r\n if (data.tabOnly) {\r\n const selectedTab = data.tabOnly.find((tb) => tb.tab === tab);\r\n\r\n if (selectedTab) {\r\n initialOptions = nonNullMerge(initialOptions, {\r\n ...selectedTab.values,\r\n });\r\n }\r\n }\r\n\r\n if (data.none?.values) {\r\n initialOptions = nonNullMerge(initialOptions, data.none.values);\r\n }\r\n\r\n if (data.tabPanel) {\r\n const selectedTab = data.tabPanel.find((tb) => tb.tab === tab);\r\n if (selectedTab?.values) {\r\n const selectedPanel = selectedTab.values.find(\r\n (pan) => pan.panel === panel\r\n );\r\n initialOptions = nonNullMerge(initialOptions, selectedPanel.values);\r\n }\r\n }\r\n\r\n if (data.panel?.values) {\r\n initialOptions = nonNullMerge(initialOptions, data.panel.values);\r\n if (data.panel.subtitle) {\r\n subtitle = data.panel.subtitle;\r\n exportSubtitle = data.panel.subtitle;\r\n }\r\n }\r\n\r\n initialOptions = mergeFigureJson(initialOptions, data, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n\r\n if (subtitle) {\r\n initialOptions.title.text = subtitle;\r\n }\r\n\r\n if (exportSubtitle) {\r\n initialOptions.exporting.chartOptions.subtitle.text = exportSubtitle;\r\n }\r\n\r\n replacePaths(initialOptions, { tab, toggle, panel });\r\n return initialOptions;\r\n } catch (e) {\r\n console.log(e);\r\n // TODO: temporary will remove later\r\n throw e;\r\n }\r\n};\r\n\r\nexport const mergeFigureJson = (\r\n initialOptions,\r\n data,\r\n { tab, toggle, panel }\r\n) => {\r\n if (data.figureJson) {\r\n const figJson = JSON.parse(data.figureJson);\r\n\r\n initialOptions = merge(initialOptions, figJson);\r\n\r\n initialOptions = tabToggleMixins(initialOptions, data, figJson, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n initialOptions = toggleMixins(initialOptions, data, figJson, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n initialOptions = panelMixins(initialOptions, data, figJson, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n\r\n initialOptions = mixinCommands(initialOptions, data, figJson);\r\n\r\n if (figJson.FULLSTACKLABELSONLYFORMATTER) {\r\n initialOptions.yAxis.stackLabels.formatter = fullStackLabelsOnlyFormatter;\r\n }\r\n\r\n if (figJson.XAXISLABELSFORMATTER) {\r\n initialOptions.xAxis.labels.formatter = xAxisLabelsFormatter;\r\n }\r\n\r\n if (figJson.YAXISFORMATTER) {\r\n initialOptions.yAxis.labels.formatter = yAxisFormatter(\r\n figJson.YAXISFORMATTER.decimalPlaces\r\n );\r\n }\r\n\r\n if (figJson.TOOLTIPFORMATTER) {\r\n if (figJson.TOOLTIPFORMATTER.scatterString) {\r\n initialOptions.tooltip.formatter = function () {\r\n return `${this.key}: ${this.x}, ${this.y}`;\r\n };\r\n } else {\r\n initialOptions.tooltip.formatter = toolTipFormatter(\r\n figJson.TOOLTIPFORMATTER.decimalPlaces,\r\n data.chartType\r\n );\r\n }\r\n }\r\n\r\n if (figJson.SETAREACHARTOPTIONS) {\r\n initialOptions = setAreaChartOptions(\r\n initialOptions,\r\n data,\r\n figJson.SETAREACHARTOPTIONS.reverse\r\n );\r\n }\r\n\r\n rotateSecondXAxisWrapper(initialOptions, figJson);\r\n\r\n if (figJson.REPLACEHDR) {\r\n let value = replaceHdr(\r\n get(data, figJson.REPLACEHDR.textPath),\r\n tab,\r\n toggle\r\n );\r\n if (figJson.REPLACEHDR.prefix) {\r\n value = figJson.REPLACEHDR.prefix + value;\r\n }\r\n set(initialOptions, figJson.REPLACEHDR.path, value);\r\n }\r\n\r\n if (window.innerWidth < RESPONSIVE_BREAK && figJson.MOBILE) {\r\n initialOptions = nonNullMerge(initialOptions, figJson.MOBILE);\r\n\r\n initialOptions = tabToggleMixins(initialOptions, data, figJson.MOBILE, {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n rotateSecondXAxisWrapper(initialOptions, figJson.MOBILE);\r\n }\r\n }\r\n return initialOptions;\r\n};\r\n\r\nconst rotateSecondXAxisWrapper = (initialOptions, figJson) => {\r\n if (figJson.ROTATESECONDXAXIS) {\r\n initialOptions = rotateSecondXAxis(\r\n initialOptions,\r\n figJson.ROTATESECONDXAXIS.useResponsiveBreak,\r\n figJson.ROTATESECONDXAXIS.rotateSingleCategory\r\n );\r\n }\r\n return initialOptions;\r\n};\r\n\r\nconst replacePaths = (initialOptions, { tab, toggle, panel }) => {\r\n replaceText(initialOptions, \"title.text\", { tab, toggle, panel });\r\n replaceText(initialOptions, \"xAxis.title.text\", { tab, toggle, panel });\r\n replaceText(initialOptions, \"yAxis.title.text\", { tab, toggle, panel });\r\n replaceText(initialOptions, \"exporting.chartOptions.subtitle.text\", {\r\n tab,\r\n toggle,\r\n panel,\r\n });\r\n};\r\n\r\nconst replaceText = (initialOptions, path, { tab, toggle, panel }) => {\r\n const tokenValue = get(initialOptions, path);\r\n if (tokenValue) {\r\n const replacedValue = tokenValue\r\n .replace(\"${initTab}\", tab)\r\n .replace(\"${initialToggle}\", toggle);\r\n set(initialOptions, path, replacedValue);\r\n }\r\n};\r\n\r\nexport default mixins;\r\n","// eslint-disable-next-line import/no-anonymous-default-export\r\nexport default (figId, data, tab) => {\r\n const nones = document.getElementsByClassName(\"a-none-circle-\" + figId);\r\n if (nones.length) {\r\n for (let i = 0; i < nones.length; i++) {\r\n nones[i].remove();\r\n }\r\n }\r\n\r\n // delete old none labels when switching tabs\r\n if (data.toggleType === \"TAB AND PANEL\") {\r\n const unSelectedTabPanels = data.tabPanel\r\n .filter((x) => {\r\n return tab !== x.tab;\r\n })\r\n .flatMap((y) => y.values);\r\n const unSelectedTabPanelIds = unSelectedTabPanels.map(\r\n (x) => data.figureNumber.replace(/\\W/g, \"\") + x.panel.replace(/\\W/g, \"\")\r\n );\r\n removeLabels(unSelectedTabPanelIds);\r\n } else if (data.toggleType === \"TAB AND TOGGLE\") {\r\n const unselectedTabs = data.tab\r\n .filter((x) => {\r\n return tab !== x.tab;\r\n })\r\n .flatMap((y) => y.values);\r\n const unselecteTabIds = unselectedTabs.map((x) =>\r\n data.figureNumber.replace(/\\W/g, \"\")\r\n );\r\n removeLabels(unselecteTabIds);\r\n }\r\n};\r\n\r\nconst removeLabels = (labels) => {\r\n for (let i = 0; i < labels.length; i++) {\r\n const id = \"a-none-circle-\" + labels[i];\r\n const noneCircles = document.getElementsByClassName(id);\r\n for (let j = 0; j < noneCircles.length; j++) {\r\n noneCircles[j].remove();\r\n }\r\n }\r\n};\r\n","const getYear = () => {\r\n const year = window?.location?.pathname?.split(\"/\")[1] || 2024;\r\n return year;\r\n};\r\n\r\nexport default getYear;\r\n","import StackColumnOptions from \"./mixins/stackedColumnOptions\";\r\nimport { determinePlotLines } from \"../../../../utils/highchartsConfig\";\r\nimport { replaceToggle } from \"../../../../utils/dynamicHeader\";\r\nimport { RESPONSIVE_BREAK } from \"../../../../utils/constants\";\r\nimport {\r\n toolTipFormatter,\r\n yAxisFormatter,\r\n} from \"../../../../utils/numberFormatters\";\r\nimport { removeNoneCircles } from \"../../../../utils/highchartsVennNone\";\r\nimport HighchartsVennExportFix from \"../../../../utils/highchartsVennExportFix\";\r\nimport { replaceHdr } from \"./graphComponents/Header\";\r\nimport mixins from \"./mixins/mixins\";\r\nimport removeNoneLabels from \"../../../../utils/removeNoneLabels\";\r\nimport getYear from \"../../../../utils/getYear\";\r\n\r\nconst setInitialFigureOptions = (\r\n initialOptions,\r\n data,\r\n initSeries,\r\n size,\r\n initTab,\r\n initialToggle,\r\n panelTab\r\n) => {\r\n let initWidth = initialOptions.chart.width;\r\n let initHeight = initialOptions.chart.height;\r\n\r\n if (\r\n data.toggleType.indexOf(\"PANEL\") > -1 &&\r\n window.innerWidth >= RESPONSIVE_BREAK\r\n ) {\r\n if (\r\n initSeries.panelCount > 1 ||\r\n (initSeries.data &&\r\n initSeries.data.length &&\r\n initSeries.data[0].panelCount > 1)\r\n ) {\r\n initWidth = 375;\r\n } else {\r\n initWidth = 600;\r\n }\r\n if (data.chartType === \"PIE CHART\") {\r\n initHeight = 375;\r\n }\r\n }\r\n\r\n if (\r\n window.innerWidth >= RESPONSIVE_BREAK &&\r\n data.chartType.indexOf(\"VENN\") > -1 &&\r\n !(data.toggleType.indexOf(\"PANEL\") > -1)\r\n ) {\r\n initWidth = 800;\r\n }\r\n\r\n let init = {\r\n ...initialOptions,\r\n tab: initTab,\r\n toggle: initialToggle,\r\n panel: panelTab,\r\n chart: {\r\n ...initialOptions.chart,\r\n type: mapChartType[data.chartType],\r\n width: size === \"micro\" ? null : initWidth,\r\n height: size === \"micro\" ? null : initHeight,\r\n marginTop: size === \"micro\" ? 30 : initialOptions.chart.marginTop,\r\n events: {\r\n load: removeNoneCircles(data, { tab: initTab, toggle: initialToggle }),\r\n redraw: removeNoneCircles(data, {\r\n tab: initTab,\r\n toggle: initialToggle,\r\n }),\r\n render: removeNoneLabels(data.figureNumber, data, initTab),\r\n exportData: HighchartsVennExportFix(data),\r\n },\r\n },\r\n title: {\r\n text: initSeries.subtitle\r\n ? initSeries.subtitle\r\n : panelTab\r\n ? panelTab\r\n : initTab\r\n ? initTab\r\n : \"\",\r\n },\r\n caption: {\r\n ...initialOptions.caption,\r\n useHTML: true,\r\n text: data.toggleType.indexOf(\"PANEL\") > -1 ? \"\" : data.methods,\r\n },\r\n yAxis: {\r\n ...initialOptions.yAxis,\r\n title: {\r\n ...initialOptions.yAxis.title,\r\n text: data.yAxisLabel,\r\n },\r\n labels: {\r\n ...initialOptions.yAxis.labels,\r\n format: mapValueFormats[data.yAxisDecimalPlaces],\r\n formatter: yAxisFormatter(data.yAxisDecimalPlaces),\r\n },\r\n },\r\n xAxis: {\r\n labels: {\r\n ...initialOptions.xAxis.labels,\r\n style: {\r\n fontSize:\r\n data.chartType === \"Clusted vertical cummulative bar\" ||\r\n data.chartType === \"GROUP STACK COLUMN CHART\"\r\n ? \"14px\"\r\n : initialOptions.xAxis.labels.style.fontSize,\r\n },\r\n step:\r\n data.chartType === \"Clusted vertical cummulative bar\" ||\r\n data.chartType === \"GROUP STACK COLUMN CHART\"\r\n ? 1\r\n : 1,\r\n },\r\n },\r\n tooltip: {\r\n ...initialOptions.tooltip,\r\n formatter: toolTipFormatter(data.dataLabelDecimalPlaces, data.chartType),\r\n // Cannot read property 'pos' of undefined\r\n split:\r\n data.chartType === \"VENN DIAGRAM\" || data.chartType === \"PIE CHART\"\r\n ? false\r\n : true,\r\n style: {\r\n visibility: data.chartType.indexOf(\"BOX PLOT\" > -1)\r\n ? \"inherit\"\r\n : undefined,\r\n },\r\n },\r\n series: initSeries.data ?? initSeries.dataSet,\r\n exporting: {\r\n ...initialOptions.exporting,\r\n enabled: !(size === \"micro\"),\r\n filename: data.figureNumber,\r\n sourceHeight: 567,\r\n sourceWidth: 1024,\r\n chartOptions: {\r\n chart: {\r\n events: {\r\n load: removeNoneCircles(\r\n data,\r\n { tab: initTab, toggle: initialToggle },\r\n true\r\n ),\r\n redraw: removeNoneCircles(\r\n data,\r\n { tab: initTab, toggle: initialToggle },\r\n true\r\n ),\r\n },\r\n },\r\n title: {\r\n text:\r\n data.figureNumber + \" \" + replaceToggle(initialToggle, data.title),\r\n align: \"left\",\r\n widthAdjust: -100,\r\n },\r\n colors: initialOptions.colors,\r\n subtitle: {\r\n text: replaceHdr(\r\n initSeries.subtitle\r\n ? initSeries.subtitle\r\n : panelTab\r\n ? panelTab\r\n : initTab\r\n ? initTab\r\n : \"\"\r\n ),\r\n },\r\n caption: {\r\n text: `Data Source: ${getYear()} United States Renal Data System Annual Data Report`,\r\n },\r\n legend: {\r\n symbolPadding: 5,\r\n symbolHeight: 16,\r\n symbolWidth: 16,\r\n itemDistance: 50,\r\n },\r\n },\r\n },\r\n };\r\n\r\n if (\r\n data.chartType === \"STACK COLUMN CHART\" ||\r\n data.chartType === \"STACKED COLUMN CHART\" ||\r\n data.chartType === \"Clusted vertical cummulative bar\" ||\r\n data.chartType === \"GROUP STACK COLUMN CHART\" ||\r\n data.chartType === \"STACK CLUSTER COLUMN CHART\" ||\r\n data.chartType === \"COLUMN CHART\" ||\r\n data.chartType === \"STACK BAR CHART\"\r\n ) {\r\n init = StackColumnOptions(init, data.yAxisDecimalPlaces);\r\n }\r\n\r\n if (data.chartType === \"FOREST PLOT\") {\r\n init.chart.inverted = true;\r\n }\r\n\r\n //init = mixins(init, data, initialToggle ?? panelTab, initTab);\r\n init = mixins(init, data, {\r\n tab: initTab,\r\n toggle: initialToggle,\r\n panel: panelTab,\r\n });\r\n\r\n if (!init.xAxis.plotLines) {\r\n init.xAxis.plotLines = determinePlotLines(init.xAxis, data.chartType);\r\n }\r\n\r\n return init;\r\n};\r\n\r\nconst mapChartType = {\r\n // line\r\n \"LINE CHART\": \"line\",\r\n\r\n // regular column\r\n \"COLUMN CHART\": \"column\",\r\n\r\n // no grouping, stacking\r\n \"STACK COLUMN CHART\": \"column\",\r\n // grouping, stacking\r\n \"Clusted vertical cummulative bar\": \"column\",\r\n \"GROUP STACK COLUMN CHART\": \"column\",\r\n // grouping, no stacking\r\n \"Clusted vertical Bar Chart\": \"column\",\r\n \"Clusted vertical bar\": \"column\",\r\n \"CLUSTER COLUMN CHART\": \"column\",\r\n \"GROUP CLUSTER COLUMN CHART\": \"column\",\r\n\r\n // Venn diagrams\r\n \"VENN DIAGRAM\": \"venn\",\r\n\r\n // Pie charts\r\n \"PIE CHART\": \"pie\",\r\n\r\n // area\r\n \"STACK AREA CHART\": \"area\",\r\n};\r\n\r\nconst mapValueFormats = {\r\n // eslint-disable-next-line\r\n [\"100\"]: \"{value:00.0f}\",\r\n // eslint-disable-next-line\r\n [\"10\"]: \"{value:0.0f}\",\r\n // eslint-disable-next-line\r\n [\"1\"]: \"{value:,.0f}\",\r\n // eslint-disable-next-line\r\n [\"0.1\"]: \"{value:,.1f}\",\r\n // eslint-disable-next-line\r\n [\"0.01\"]: \"{value:,.2f}\",\r\n // eslint-disable-next-line\r\n [\"0.001\"]: \"{value:,.3f}\",\r\n};\r\n\r\nexport default setInitialFigureOptions;\r\n","import React from 'react'\r\nimport HighchartsReact from 'highcharts-react-official'\r\n\r\nconst Graph = ({ highcharts, options, size }) => {\r\n\r\n return (\r\n
\r\n
\r\n )\r\n}\r\n\r\nexport default Graph","import React from 'react'\r\nimport DOMPurify from 'dompurify';\r\n\r\nconst Summary = ({ figureData, size }) => {\r\n return (size !== 'micro' && size !== 'mini') ?\r\n <>\r\n \r\n {toggleValues ? (\r\n toggleValues.map((tv) => (\r\n \r\n ))\r\n ) : (\r\n <>\r\n )}\r\n
\r\n );\r\n};\r\n\r\nexport default TogglePane;\r\n","export const DATA_SET_CHANGE = 'DATA_SET_CHANGE'","export const extractMapSeries = (data, tab, toggle, dataPointMapper) => {\r\n let seriesData = [];\r\n let name = \"\";\r\n if (data.panel) {\r\n name = data.panel.panel;\r\n seriesData = data.panel.values.series.map(dataPointMapper);\r\n } else if (data.none) {\r\n name = data.none.panel;\r\n seriesData = data.none.values.series.map(dataPointMapper);\r\n } else if (data.tabOnly) {\r\n name = data.tabOnly.tab;\r\n seriesData = data.tabOnly\r\n .find((x) => x.tab === tab)\r\n .values.series.map(dataPointMapper);\r\n } else if (data.toggle) {\r\n name = toggle;\r\n seriesData = data.toggle\r\n .find((x) => x.toggle === toggle)\r\n .values.series.map(dataPointMapper);\r\n } else {\r\n name = tab;\r\n try {\r\n let tabSeriesData = data.tab\r\n .filter((x) => x.tab === tab)[0]\r\n .values.filter((y) => y.toggle === toggle)[0].values;\r\n if (!tabSeriesData.series) {\r\n seriesData = tabSeriesData.map(dataPointMapper);\r\n } else {\r\n seriesData = tabSeriesData.series.map(dataPointMapper);\r\n }\r\n } catch (ex) {\r\n console.log(ex);\r\n seriesData = [];\r\n }\r\n }\r\n\r\n name = name ?? data.figureNumber;\r\n\r\n const series = {\r\n type: \"map\",\r\n name,\r\n data: seriesData,\r\n };\r\n\r\n return series;\r\n};\r\n","import React from \"react\";\r\nimport Highcharts from \"./HighchartsMixins\";\r\nimport HighchartsReact from \"highcharts-react-official\";\r\nimport mapDataUS from \"./maps/smaller.json\";\r\nimport initOptions from \"./initialToggleOptions\";\r\nimport { mergeFigureJson } from \"./mixins/mixins\";\r\nimport { extractMapSeries } from \"./maps/mapUtils\";\r\nimport { replaceHdr } from \"./graphComponents/Header\";\r\nimport * as chartConfig from \"../../../../utils/highchartsConfig\";\r\nimport getYear from \"../../../../utils/getYear\";\r\n\r\nconst HSAMap = ({ data, tab, toggle }) => {\r\n const dataPointMapper = (x) => ({\r\n \"hc-key\": x.name.toLowerCase(),\r\n value: x.data[0],\r\n x: x.data[0],\r\n });\r\n\r\n let mapOptions = {\r\n ...initOptions().style,\r\n chart: {\r\n map: mapDataUS,\r\n type: \"map\",\r\n width: 350,\r\n style: {\r\n fontFamily: chartConfig.font,\r\n },\r\n },\r\n title: {\r\n text: data.panel\r\n ? data.panel.panel\r\n : data.toggle\r\n ? data.toggle.toggle\r\n : data.tab\r\n ? data.tab.tab\r\n : \"\",\r\n },\r\n caption: {\r\n useHTML: true,\r\n text: data.toggleType.indexOf(\"PANEL\") > -1 ? \"\" : data.methods,\r\n },\r\n tooltip: {\r\n style: {\r\n fontSize: \"14px\",\r\n },\r\n valueDecimals: mapTooltopFormats[data.dataLabelDecimalPlaces],\r\n //formatter: toolTipFormatter(data.dataLabelDecimalPlaces, data.chartType),\r\n },\r\n colorAxis: {\r\n type: \"linear\",\r\n minColor: \"#45ba8f\",\r\n maxColor: \"#2a4372\",\r\n stops: [\r\n [0, \"#45ba8f\"],\r\n [0.2, \"#00a59a\"],\r\n [0.4, \"#008e9f\"],\r\n [0.6, \"#00759a\"],\r\n [0.8, \"#005c8b\"],\r\n [1, \"#2a4372\"],\r\n ],\r\n labels: {\r\n style: {\r\n textOverflow: \"none\",\r\n },\r\n },\r\n },\r\n credits: {\r\n text: \"\",\r\n },\r\n series: [extractMapSeries(data, tab, toggle, dataPointMapper)],\r\n mapNavigation: {\r\n enabled: true,\r\n enableDoubleClickZoomTo: true,\r\n },\r\n exporting: {\r\n filename: data.figureNumber,\r\n sourceHeight: 567,\r\n sourceWidth: 1024,\r\n chartOptions: {\r\n title: {\r\n text: data.figureNumber + \" \" + replaceHdr(data.title, tab, toggle),\r\n align: \"left\",\r\n widthAdjust: -100,\r\n },\r\n caption: {\r\n text: `Data Source: ${getYear()} United States Renal Data System Annual Data Report`,\r\n },\r\n subtitle: {\r\n text: data.panel?.panel ? data.panel.panel : \"\",\r\n },\r\n },\r\n buttons: {\r\n contextButton: {\r\n menuItems: [\r\n \"downloadPNG\",\r\n \"downloadJPEG\",\r\n \"downloadSVG\",\r\n \"separator\",\r\n \"downloadCSV\",\r\n \"downloadXLS\",\r\n ],\r\n },\r\n },\r\n },\r\n };\r\n\r\n mapOptions = mergeFigureJson(mapOptions, data, {\r\n tab,\r\n toggle,\r\n panel: data.panel?.panel,\r\n });\r\n delete mapOptions.xAxis;\r\n\r\n return (\r\n \r\n
\r\n );\r\n};\r\n\r\nconst mapTooltopFormats = {\r\n // eslint-disable-next-line\r\n [\"0.001\"]: 3,\r\n // eslint-disable-next-line\r\n [\"0.01\"]: 2,\r\n // eslint-disable-next-line\r\n [\"0.1\"]: 1,\r\n // eslint-disable-next-line\r\n [\"1\"]: 0,\r\n};\r\n\r\nexport default HSAMap;\r\n","import React from \"react\";\r\nimport Highcharts from \"./HighchartsMixins\";\r\nimport HighchartsReact from \"highcharts-react-official\";\r\nimport mapDataUS from \"@highcharts/map-collection/countries/us/us-all.geo.json\";\r\nimport initOptions from \"./initialToggleOptions\";\r\nimport { mergeFigureJson } from \"./mixins/mixins\";\r\nimport { extractMapSeries } from \"./maps/mapUtils\";\r\nimport * as chartConfig from \"../../../../utils/highchartsConfig\";\r\nimport getYear from \"../../../../utils/getYear\";\r\n\r\nconst StateMap = ({ data, tab, toggle }) => {\r\n const dataPointMapper = (x) => ({\r\n name: x.name,\r\n \"hc-key\": \"us-\" + x.name.toLowerCase(),\r\n value: x.data[0],\r\n x: x.data[0],\r\n });\r\n\r\n let mapOptions = {\r\n ...initOptions().style,\r\n chart: {\r\n map: mapDataUS,\r\n type: \"map\",\r\n width: !data.tabOnly ? 350 : undefined,\r\n style: {\r\n fontFamily: chartConfig.font,\r\n },\r\n },\r\n title: {\r\n text: data.panel\r\n ? data.panel.subtitle\r\n ? data.panel.subtitle\r\n : data.panel.panel\r\n : tab,\r\n },\r\n caption: {\r\n useHTML: true,\r\n text: data.toggleType.indexOf(\"PANEL\") > -1 ? \"\" : data.methods,\r\n },\r\n tooltip: {\r\n style: {\r\n fontSize: \"14px\",\r\n },\r\n valueDecimals: mapTooltopFormats[data.dataLabelDecimalPlaces],\r\n //formatter: toolTipFormatter(data.dataLabelDecimalPlaces, data.chartType),\r\n },\r\n colorAxis: {\r\n type: \"linear\",\r\n minColor: \"#45ba8f\",\r\n maxColor: \"#2a4372\",\r\n stops: [\r\n [0, \"#45ba8f\"],\r\n [0.2, \"#00a59a\"],\r\n [0.4, \"#008e9f\"],\r\n [0.6, \"#00759a\"],\r\n [0.8, \"#005c8b\"],\r\n [1, \"#2a4372\"],\r\n ],\r\n },\r\n credits: {\r\n text: \"\",\r\n },\r\n series: [extractMapSeries(data, tab, toggle, dataPointMapper)],\r\n exporting: {\r\n filename: data.figureNumber,\r\n sourceHeight: 567,\r\n sourceWidth: 1024,\r\n chartOptions: {\r\n title: {\r\n text: data.figureNumber + \" \" + data.title,\r\n align: \"left\",\r\n widthAdjust: -100,\r\n },\r\n subtitle: {\r\n text: data.panel\r\n ? data.panel.subtitle\r\n ? data.panel.subtitle\r\n : data.panel.panel\r\n : tab,\r\n },\r\n caption: {\r\n text: `Data Source: ${getYear()} United States Renal Data System Annual Data Report`,\r\n },\r\n },\r\n buttons: {\r\n contextButton: {\r\n menuItems: [\r\n \"downloadPNG\",\r\n \"downloadJPEG\",\r\n \"downloadSVG\",\r\n \"separator\",\r\n \"downloadCSV\",\r\n \"downloadXLS\",\r\n ],\r\n },\r\n },\r\n },\r\n };\r\n\r\n mapOptions = mergeFigureJson(mapOptions, data, {\r\n tab,\r\n toggle,\r\n panel: data.panel?.panel,\r\n });\r\n delete mapOptions.xAxis;\r\n\r\n return (\r\n \r\n
\r\n );\r\n};\r\n\r\nconst mapTooltopFormats = {\r\n // eslint-disable-next-line\r\n [\"0.001\"]: 3,\r\n // eslint-disable-next-line\r\n [\"0.01\"]: 2,\r\n // eslint-disable-next-line\r\n [\"0.1\"]: 1,\r\n // eslint-disable-next-line\r\n [\"1\"]: 0,\r\n};\r\n\r\nexport default StateMap;\r\n","import React from \"react\";\r\nimport Highcharts from \"./HighchartsMixins\";\r\nimport HighchartsReact from \"highcharts-react-official\";\r\nimport mapDataUS from \"@highcharts/map-collection/countries/us/us-all-all.geo.json\";\r\nimport initOptions from \"./initialToggleOptions\";\r\nimport { mergeFigureJson } from \"./mixins/mixins\";\r\nimport { extractMapSeries } from \"./maps/mapUtils\";\r\nimport * as chartConfig from \"../../../../utils/highchartsConfig\";\r\nimport getYear from \"../../../../utils/getYear\";\r\n\r\nconst CountyMap = ({ data, tab, toggle }) => {\r\n const dataPointMapper = (x) => ({\r\n name: x.name,\r\n \"hc-key\": \"us-\" + x.name.toLowerCase(),\r\n value: x.data[0],\r\n x: x.data[0],\r\n });\r\n\r\n let lines = Highcharts.geojson(\r\n mapDataUS, 'mapline'\r\n );\r\n\r\n let mapOptions = {\r\n ...initOptions().style,\r\n chart: {\r\n map: mapDataUS,\r\n type: \"map\",\r\n width: !data.tabOnly ? 350 : undefined,\r\n style: {\r\n fontFamily: chartConfig.font,\r\n },\r\n },\r\n title: {\r\n text: \r\n data.toggle? \r\n data.toggle.find(y => y.toggle === toggle)?.values.title.text\r\n :\r\n \"\"\r\n },\r\n caption: {\r\n useHTML: true,\r\n text: data.toggleType.indexOf(\"PANEL\") > -1 ? \"\" : data.methods,\r\n },\r\n tooltip: {\r\n style: {\r\n fontSize: \"14px\",\r\n },\r\n valueDecimals: mapTooltopFormats[data.dataLabelDecimalPlaces],\r\n //formatter: toolTipFormatter(data.dataLabelDecimalPlaces, data.chartType),\r\n },\r\n colorAxis: {\r\n type: \"linear\",\r\n minColor: \"#45ba8f\",\r\n maxColor: \"#2a4372\",\r\n stops: [\r\n [0, \"#45ba8f\"],\r\n [0.2, \"#00a59a\"],\r\n [0.4, \"#008e9f\"],\r\n [0.6, \"#00759a\"],\r\n [0.8, \"#005c8b\"],\r\n [1, \"#2a4372\"],\r\n ],\r\n },\r\n credits: {\r\n text: \"\",\r\n },\r\n series: [extractMapSeries(data, tab, toggle, dataPointMapper),\r\n {\r\n type: 'mapline',\r\n name: 'State borders',\r\n data: [lines[0]],\r\n lineWidth: 0.5\r\n }\r\n ],\r\n mapNavigation: {\r\n enabled: true,\r\n enableDoubleClickZoomTo: true,\r\n }, \r\n exporting: {\r\n filename: data.figureNumber,\r\n sourceHeight: 567,\r\n sourceWidth: 1024,\r\n chartOptions: {\r\n title: {\r\n text: data.figureNumber + \" \" + data.title,\r\n align: \"left\",\r\n widthAdjust: -100,\r\n },\r\n subtitle: {\r\n text: \r\n data.toggle? \r\n data.toggle.find(y => y.toggle === toggle)?.values.title.text\r\n :\r\n \"\"\r\n },\r\n caption: {\r\n text: `Data Source: ${getYear()} United States Renal Data System Annual Data Report`,\r\n },\r\n },\r\n buttons: {\r\n contextButton: {\r\n menuItems: [\r\n \"downloadPNG\",\r\n \"downloadJPEG\",\r\n \"downloadSVG\",\r\n \"separator\",\r\n \"downloadCSV\",\r\n \"downloadXLS\",\r\n ],\r\n },\r\n },\r\n },\r\n };\r\n\r\n mapOptions = mergeFigureJson(mapOptions, data, {\r\n tab,\r\n toggle,\r\n panel: data.panel?.panel,\r\n });\r\n delete mapOptions.xAxis;\r\n\r\n return (\r\n \r\n
\r\n );\r\n};\r\n\r\nconst mapTooltopFormats = {\r\n // eslint-disable-next-line\r\n [\"0.001\"]: 3,\r\n // eslint-disable-next-line\r\n [\"0.01\"]: 2,\r\n // eslint-disable-next-line\r\n [\"0.1\"]: 1,\r\n // eslint-disable-next-line\r\n [\"1\"]: 0,\r\n};\r\n\r\nexport default CountyMap;\r\n","import React from \"react\";\r\nimport { useDispatch, useSelector } from \"react-redux\";\r\nimport Highcharts from \"./HighchartsMixins\";\r\n\r\nimport \"./figure.scss\";\r\nimport { useState } from \"react\";\r\nimport setInitialOptions from \"./setInitialFigureOptions\";\r\nimport initialOptions from \"./initialToggleOptions\";\r\nimport Header from \"./graphComponents/Header\";\r\nimport Graph from \"./graphComponents/Graph\";\r\nimport Summary from \"./graphComponents/Summary\";\r\nimport TogglePane from \"./graphComponents/TogglePane\";\r\nimport { DATA_SET_CHANGE } from \"../../../../redux/actions/graphs\";\r\nimport HSAMap from \"./HSAMap\";\r\nimport StateMap from \"./StateMap\";\r\nimport CountyMap from \"./CountyMap\";\r\nimport { useEffect } from \"react\";\r\n\r\nconst Toggle = ({ serverdata, size, slug }) => {\r\n const dispatch = useDispatch();\r\n\r\n const data = serverdata;\r\n\r\n const toggleValues = Array.from(new Set(data.toggle.map((x) => x.toggle)));\r\n\r\n let iTog = toggleValues[0];\r\n\r\n if (data.figureJson) {\r\n try {\r\n const figJson = JSON.parse(data.figureJson);\r\n if (figJson.defaultToggle) {\r\n iTog = figJson.defaultToggle;\r\n }\r\n } catch {\r\n console.warn(\"tried to parse non-json json\");\r\n }\r\n }\r\n\r\n const selection = useSelector((state) => state.graphState[data.figureNumber]);\r\n const [toggle, setToggle] = useState(\r\n selection && selection.toggle ? selection.toggle : iTog\r\n );\r\n\r\n const [options, setOptions] = useState();\r\n\r\n useEffect(() => {\r\n let newOptions = {\r\n title: {\r\n text: toggle,\r\n },\r\n };\r\n newOptions = setInitialOptions(\r\n initialOptions(),\r\n data,\r\n { subtitle: toggle },\r\n size,\r\n null,\r\n toggle\r\n );\r\n setOptions(newOptions);\r\n }, [data, size, toggle]);\r\n\r\n const toggleDataSet = (newToggle) => {\r\n setToggle(newToggle);\r\n dispatch({\r\n type: DATA_SET_CHANGE,\r\n payload: {\r\n figureNumber: data.figureNumber,\r\n toggle: newToggle,\r\n },\r\n });\r\n };\r\n\r\n let graph = \r\n
\r\n )\r\n}\r\n\r\nexport default PanelMethods","import React from \"react\";\r\nimport Graph from \"./graphComponents/Graph\";\r\nimport Highcharts from \"./HighchartsMixins\";\r\n\r\nconst Venn = ({ options, size }) => {\r\n return (\r\n <>\r\n \r\n
\r\n );\r\n};\r\n\r\nconst mapTooltopFormats = {\r\n // eslint-disable-next-line\r\n [\"0.001\"]: 3,\r\n // eslint-disable-next-line\r\n [\"0.01\"]: 2,\r\n // eslint-disable-next-line\r\n [\"0.1\"]: 1,\r\n // eslint-disable-next-line\r\n [\"1\"]: 0,\r\n};\r\n\r\nconst countryToHcKey = {\r\n \"South Africa\": \"za\",\r\n Nigeria: \"ng\",\r\n Fiji: \"fj\",\r\n \"China, Mainland\": \"cn\",\r\n Guatemala: \"gt\",\r\n Ukraine: \"ua\",\r\n Bangladesh: \"bd\",\r\n Chile: \"cl\",\r\n Colombia: \"co\",\r\n Iceland: \"is\",\r\n Finland: \"fi\",\r\n Kazakhstan: \"kz\",\r\n China: \"cn\",\r\n Norway: \"no\",\r\n Sweden: \"se\",\r\n Kuwait: \"kw\",\r\n Lithuania: \"lt\",\r\n \"United Kingdom\": \"gb\",\r\n \"England, Wales & Northern Ireland\": \"gb\",\r\n \"Bosnia and Herzegovina\": \"ba\",\r\n Albania: \"al\",\r\n Italy: \"it\",\r\n Qatar: \"qa\",\r\n Turkey: \"tr\",\r\n Argentina: \"ar\",\r\n \"Saudi Arabia\": \"sa\",\r\n France: \"fr\",\r\n Uruguay: \"uy\",\r\n \"Hong Kong\": \"hk\",\r\n Israel: \"il\",\r\n Canada: \"ca\",\r\n Brazil: \"br\",\r\n Indonesia: \"id\",\r\n Portugal: \"pt\",\r\n Malaysia: \"my\",\r\n Greece: \"gr\",\r\n Japan: \"jp\",\r\n \"Rep. of Korea\": \"kr\",\r\n \"Republic of Korea\": \"kr\",\r\n Singapore: \"sg\",\r\n Thailand: \"th\",\r\n \"United States\": \"us\",\r\n Hungary: \"hu\",\r\n Taiwan: \"tw\",\r\n Mexico: \"mx\",\r\n Netherlands: \"nl\",\r\n Montenegro: \"me\",\r\n Australia: \"au\",\r\n \"New Zealand\": \"nz\",\r\n Spain: \"es\",\r\n Poland: \"pl\",\r\n \"Belgium, Dutch speaking\": \"be\",\r\n \"Belgium, French speaking\": \"be\",\r\n Belgium: \"be\",\r\n Romania: \"ro\",\r\n \"North Macedonia\": \"mk\",\r\n \"Czech Republic\": \"cz\",\r\n Latvia: \"lv\",\r\n Estonia: \"ee\",\r\n Serbia: \"rs\",\r\n Russia: \"ru\",\r\n Switzerland: \"ch\",\r\n Denmark: \"dk\",\r\n \"China, mainland\": \"cn\",\r\n Austria: \"at\",\r\n Mongolia: \"mn\",\r\n Belarus: \"by\",\r\n \"El Salvador\": \"sv\",\r\n \"Brunei Darussalam\": \"bn\",\r\n Ethiopia: \"et\",\r\n};\r\n\r\nexport default WorldMap;\r\n","import React from \"react\";\r\nimport Graph from \"./Venn\";\r\n\r\nimport setInitialOptions from \"./setInitialFigureOptions\";\r\nimport initialOptions from \"./initialToggleOptions\";\r\nimport StateMap from \"./StateMap\";\r\nimport CountyMap from \"./CountyMap\";\r\nimport HSAMap from \"./HSAMap\";\r\nimport WorldMap from \"./WorldMap\";\r\n\r\nconst PanelInstance = ({ panel: figData, size, tab, toggle }) => {\r\n if (figData.chartType === \"VENN DIAGRAM\") {\r\n const options = setInitialOptions(\r\n initialOptions(),\r\n figData,\r\n { data: [figData.panel] },\r\n size,\r\n tab,\r\n toggle,\r\n figData.panel.panel\r\n );\r\n return \r\n
\r\n );\r\n } else {\r\n divs.push(\r\n \r\n
\r\n );\r\n }\r\n }\r\n i++;\r\n }\r\n return divs;\r\n };\r\n\r\n return (\r\n <>\r\n {size !== \"micro\" &&\r\n serverdata.toggleType !== \"TAB AND TOGGLE AND PANEL\" ? (\r\n <>\r\n {data && data.length ? (\r\n \r\n
\r\n ) : data ? (\r\n \r\n {panelLayout(data.panel).map((x) => x)}\r\n
\r\n \r\n { tabValues ?\r\n tabValues.map(tab =>\r\n
\r\n )\r\n}\r\n\r\nexport default Tab","import React from \"react\";\r\nimport Highcharts from \"./HighchartsMixins\";\r\n\r\nimport \"./figure.scss\";\r\nimport { useState } from \"react\";\r\nimport setInitialOptions from \"./setInitialFigureOptions\";\r\nimport Header from \"./graphComponents/Header\";\r\nimport Graph from \"./graphComponents/Graph\";\r\nimport Summary from \"./graphComponents/Summary\";\r\nimport TogglePane from \"./graphComponents/TogglePane\";\r\nimport Tab from \"./graphComponents/Tab\";\r\nimport { useDispatch, useSelector } from \"react-redux\";\r\nimport { DATA_SET_CHANGE } from \"../../../../redux/actions/graphs\";\r\nimport HSAMap from \"./HSAMap\";\r\nimport StateMap from \"./StateMap\";\r\nimport CountyMap from \"./CountyMap\";\r\nimport { useEffect } from \"react\";\r\nimport initialToggleOptions from \"./initialToggleOptions\";\r\n\r\nconst TabToggle = ({ serverdata, size, slug }) => {\r\n const data = serverdata;\r\n //data.id = serverdata.figureNumber.replace(/\\s+/g, \"\");\r\n\r\n const dispatch = useDispatch();\r\n const graphState = useSelector(\r\n (state) => state.graphState[data.figureNumber]\r\n );\r\n\r\n // determine current possible tab values and select the default one selected\r\n const tabValues = Array.from(new Set(data.tab.flatMap((x) => x.tab)));\r\n const cTab = graphState && graphState.tab ? graphState.tab : tabValues[0];\r\n const [currentTab, setTab] = useState(cTab);\r\n\r\n // determine possible toggle values from the currently selected tab\r\n const togValues = data.tab.filter((y) => y.tab === currentTab)[0];\r\n const possibleToggleValues = Array.from(\r\n new Set(togValues ? togValues.values.flatMap((x) => x.toggle) : [])\r\n );\r\n\r\n // ugh, I'm so tabDataSet(tab)}>{tab}
\r\n )\r\n : <>}\r\n \r\n
\r\n );\r\n } else {\r\n divs.push(\r\n \r\n
\r\n );\r\n }\r\n }\r\n i++;\r\n }\r\n return divs;\r\n };\r\n\r\n return (\r\n <>\r\n {size !== \"micro\" ? (\r\n <>\r\n \r\n
\r\n \r\n {initPanel && initPanel.values ? (\r\n panelLayout(initPanel.values).map((x) => x)\r\n ) : (\r\n <>\r\n )}\r\n
\r\n \r\n
\r\n )\r\n }\r\n\r\nexport default ErrorFallback;","import React, { Suspense, lazy } from 'react'\r\nimport { useParams } from \"react-router-dom\";\r\nimport DOMPurify from 'dompurify';\r\nimport Header from './graphComponents/Header'\r\nimport Summary from './graphComponents/Summary'\r\nimport LoadingTable from '../tables/LoadingTable';\r\nimport ErrorFallback from \"../../ErrorFallback\";\r\nimport { ErrorBoundary } from \"react-error-boundary\";\r\n\r\nimport '../tables/DataTable.scss'\r\nconst Table = ({ serverdata, size, slug }) => {\r\n const { year } = useParams();\r\n const tableData = () => {\r\n let volume = serverdata.volume === 'chronic-kidney-disease' ? \"CKD\" : \"ESRD\";\r\n let tableName = serverdata.figureNumber.replace(\" \", \"\").replace(\".\", \"\");\r\n const LazyTable = lazy(() => import(`../tables/${year}/${volume}/${tableName}`));\r\n \r\n return (\r\n The application has encountered an unknown error.
\r\nOur technical staff have been automatically notified and will be looking into this right away.
\r\n\r\n {tableData()}\r\n
\r\n \r\n
\r\n \r\n
\r\n );\r\n } else {\r\n divs.push(\r\n \r\n
\r\n );\r\n }\r\n }\r\n i++;\r\n }\r\n return divs;\r\n };\r\n\r\n return (\r\n <>\r\n {size !== \"micro\" ? (\r\n <>\r\n \r\n
\r\n \r\n {initPanel && initPanel.values ? (\r\n panelLayout(initialPanel.values).map((x) => x)\r\n ) : (\r\n <>\r\n )}\r\n
\r\n \r\n {imageData()}\r\n
\r\n \r\n
\r\n \r\n {section.figure && section.figure.figureNumber ? (\r\n <>\r\n ) : (\r\n \r\n {section.title}\r\n \r\n )}\r\n \r\n \r\n \r\n {section.figure && section.figure.figureNumber ? (\r\n \r\n \r\n ) : (\r\n <>\r\n )}\r\n {section.sectionText && section.sectionText.length ? (\r\n section.sectionText.map((x) => (\r\n \r\n ))\r\n ) : (\r\n <>\r\n )}\r\n \r\n
\r\n \r\n \r\n );\r\n}\r\n","import React from \"react\";\r\nimport { useQuery } from \"@apollo/client\";\r\nimport { getSectionsByChapterId } from \"../../queries/sections\";\r\nimport { useEffect } from \"react\";\r\nimport SectionWaypoint from \"./temp/SectionWaypoint\";\r\nimport Octicon, { FileSymlinkFile } from \"@primer/octicons-react\";\r\nimport config from \"../../config/config\";\r\nimport { useParams } from \"react-router\";\r\n\r\nexport default function ChapterDetails({ selectedChapter, selectedVolume }) {\r\n const { data: secData } = useQuery(\r\n getSectionsByChapterId(selectedChapter.id)\r\n );\r\n\r\n const { year } = useParams();\r\n\r\n useEffect(() => {\r\n if (window.location.hash && secData) {\r\n const id = window.location.hash.replace(\"#\", \"\");\r\n const elemToScrollTo = document.getElementById(id);\r\n const main = document.getElementById(\"main\");\r\n if (elemToScrollTo && main) {\r\n main.scrollTop = elemToScrollTo.offsetTop;\r\n }\r\n }\r\n }, [secData]);\r\n\r\n const printer = () => {\r\n const chapNum = selectedChapter.chapterNumber;\r\n const volNum = selectedVolume.order;\r\n const url = `${config.baseUri}/PDF?year=${year}&chapterNumber=${chapNum}&volumeNumber=${volNum}`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n \r\n
\r\n );\r\n}\r\n","import hiddenChaptersDev from '../hiddenChapters.development.json';\r\nimport hiddenChaptersTest from '../hiddenChapters.test.json';\r\nimport hiddenChaptersProd from '../hiddenChapters.production.json';\r\nimport getYear from \"../utils/getYear\";\r\n\r\nexport const isHiddenChapter = (chapter, volume) => {\r\n\r\n let env = process.env.REACT_APP_BUILD;\r\n let hiddenChapters = env === 'development' ? hiddenChaptersDev :\r\n env === 'demo' || env === 'staging' ? hiddenChaptersTest :\r\n hiddenChaptersProd;\r\n\r\n let chapterList = hiddenChapters.find(x => x.year === parseInt(getYear()));\r\n return chapterList?.chapters.find(y => y.volume === volume?.order && y.chapter === chapter?.chapterNumber);\r\n\r\n};\r\n\r\nexport const hiddenVolumeStyle = (volume) => {\r\n return '';\r\n}\r\n\r\nexport default isHiddenChapter\r\n","import React from 'react';\r\nimport { useRouteMatch } from 'react-router-dom'\r\nimport ChapterDetails from './ChapterDetails';\r\nimport isHiddenChapter from '../../utils/hiddenChapter';\r\n\r\nconst ChapterSummary = ({ outline }) => {\r\n\r\n const data = outline\r\n // match up current path with what sections are currently available\r\n const { params: { volume, chapter } } = useRouteMatch('/:year/:volume?/:chapter?')\r\n\r\n const selectedVolume = data && data.volumes && volume ? data.volumes.filter(vol => vol.slug === volume)[0] : null;\r\n\r\n const selectedChapter = selectedVolume && selectedVolume.chapters && chapter ?\r\n selectedVolume.chapters.filter(chap => chap.slug === chapter)[0]\r\n : null;\r\n \r\n return (\r\n isHiddenChapter(selectedChapter, selectedVolume) ?\r\n \"This chapter is currently not available\" :\r\n selectedChapter ?\r\n <>\r\n\r\n\r\n \r\n
\r\n \r\n {selectedVolume.title}: Chapter {selectedChapter.chapterNumber}\r\n
\r\n printer()}>\r\n Download PDF{\" \"}\r\n
\r\n {selectedChapter.title}
\r\n {secData && secData.sections ? (\r\n secData.sections.map((section, idx) => {\r\n return (\r\n\r\n
\r\n ) : (\r\n <>\r\n )}\r\n
\r\n );\r\n })\r\n ) : (\r\n <>\r\n )}\r\n \r\n ) : (\r\n <>\r\n )}\r\n
{selectedVolume.title}
\r\nTable of Contents
\r\n- \r\n {selectedVolume.chapters ? (\r\n selectedVolume.chapters.map((chap) => {\r\n const path = `/${year}/${selectedVolume.slug}/${chap.slug}`;\r\n return (\r\n \r\n
- \r\n {chap.chapterNumber && chap.chapterNumber > 0\r\n ? `${getChapterPrefix(chap, selectedVolume)}${chap.title}`\r\n : chap.title}\r\n \r\n \r\n ); \r\n })\r\n ) : (\r\n <>\r\n )}\r\n
Loading {year} Annual Data Report...
\r\n );\r\n }\r\n\r\n if (error) {\r\n return (\r\n \r\n Could not load {year} Annual Data Report.\r\n
\r\n );\r\n }\r\n\r\n return (\r\n <>\r\n {year} Annual Data Report
\r\nTable of Contents
\r\n {data && data.volumes && data.volumes.length > 0 ? (\r\n data.volumes.map((vol) => {\r\n return (\r\n- \r\n
- \r\n {vol.chapters.length ? (\r\n {vol.title}\r\n ) : (\r\n {vol.title}\r\n )}\r\n
- \r\n {vol.chapters ? (\r\n vol.chapters.map((chap) => {\r\n const path = `/${year}/${vol.slug}/${chap.slug}`;\r\n return (\r\n \r\n
- \r\n {chap.chapterNumber && chap.chapterNumber > 0\r\n ? `${getChapterPrefix(chap, vol)}${chap.title}`\r\n : chap.title}\r\n \r\n \r\n );\r\n })\r\n ) : (\r\n <>\r\n )}\r\n
\r\n
Navigating the {year} ADR
\r\n{year} format
\r\n\r\n
\r\n {year} ADR content\r\n
\r\n\r\n ADR content has also been updated and will continue to evolve in\r\n coming years. We will introduce contemporary topics while\r\n maintaining focus on key surveillance functions. The emerging\r\n topics we introduce this year center on the experiences of\r\n patients with kidney disease and the effects of coronavirus\r\n disease 2019 (COVID-19). A new Patient Experience chapter\r\n focuses on patients’ experience of symptoms, understanding of\r\n prognosis, and end-of-life preferences, and explores\r\n inter-relations among these factors. The COVID-19 pandemic has\r\n presented an unexpected and urgent need for surveillance and\r\n investigation. Although traditional sources of data used in\r\n preparation of the ADR involve an 18-month lag, largely due to\r\n processing of Medicare claims, we have used quarterly data\r\n extracts from the Centers for Medicare & Medicaid Services’\r\n Renal Management Information System—anchored by the ESRD Medical\r\n Evidence Report and the ESRD Death Notification—to examine\r\n changes in mortality, hospitalization, and onset of ESRD during\r\n the early period of the pandemic.\r\n
\r\n\r\n This year represents the beginning of a new phase in data\r\n sharing among government and non-government entities, which\r\n presents challenges and opportunities. As a result, this year’s\r\n ADR does not contain data from private insurers. However, we\r\n anticipate that future ADRs will include these data and will\r\n also incorporate additional data sources to more fully\r\n characterize non-Medicare populations with kidney disease.{\" \"}\r\n
\r\nReference Tables
\r\n- \r\n
- \r\n Volume 1 - CKD:\r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
- \r\n Volume 2 - ESRD:\r\n
- \r\n
- \r\n \r\n \r\n
- \r\n \r\n \r\n
- \r\n
- \r\n \r\n \r\n
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- \r\n \r\n \r\n
- \r\n \r\n \r\n
- \r\n \r\n \r\n
- \r\n \r\n \r\n
- \r\n \r\n \r\n
- \r\n \r\n \r\n
- \r\n
- \r\n \r\n \r\n
\r\n
Reference Tables
\r\n- \r\n
- \r\n Volume 1 - CKD:\r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
- \r\n Volume 2 - ESRD:\r\n
- \r\n
- \r\n
- \r\n
- \r\n
- \r\n
- \r\n
- \r\n
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\r\n
\r\n **Error Notification**
\r\n Reference Tables A.4 and A.9 in the 2021 Annual Data Report were found to contain a small number of errors. \r\n These errors have now been corrected and the updated tables have been posted.\r\n
Reference Tables
\r\n- \r\n
- \r\n Volume 1 - CKD:\r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
- \r\n Volume 2 - ESRD:\r\n
- \r\n
- \r\n
- \r\n
- \r\n
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- \r\n
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- \r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
Reference Tables
\r\n- \r\n
- \r\n Volume 1 - CKD:\r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
- \r\n Volume 2 - ESRD:\r\n
- \r\n
- \r\n
- \r\n
- \r\n
- \r\n
- \r\n
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- \r\n
- \r\n
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- \r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
Reference Tables
\r\n- \r\n
- \r\n Volume 1 - CKD:\r\n
- \r\n
- \r\n
- \r\n
- \r\n
\r\n - \r\n
- \r\n Volume 2 - ESRD:\r\n
- \r\n
- \r\n
- \r\n
- \r\n
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- \r\n
- \r\n
\r\n - \r\n
\r\n Healthy People 2020 CKD Objectives\r\n download(\"HP2020_20\")}\r\n >\r\n Download All Objectives\r\n \r\n
\r\n | Objective | \r\nIndicator | \r\nTarget | \r\n
| CKD-1* | \r\n\r\n Reduce the proportion of the U.S. population with chronic kidney\r\n disease\r\n | \r\n13.30% | \r\n
| CKD-2* | \r\n\r\n Increase the proportion of persons with chronic kidney disease\r\n (CKD) who know they have impaired renal function\r\n | \r\n13.40% | \r\n
| CKD-3 | \r\n\r\n \r\n | \r\n12.30% | \r\n
| CKD-4 | \r\n\r\n Increase the proportion of persons with diabetes and chronic\r\n kidney disease who receive recommended medical evaluation\r\n | \r\n\r\n |
| \r\n | \r\n \r\n | \r\n28.40% | \r\n
| \r\n | \r\n \r\n | \r\n25.30% | \r\n
| CKD-5 | \r\n\r\n \r\n | \r\n74.10% | \r\n
| CKD-6* | \r\n\r\n Improve cardiovascular care in persons with chronic kidney\r\n disease\r\n | \r\n\r\n |
| \r\n | \r\n 6.1 Reduce the proportion of persons with chronic kidney disease\r\n who have elevated blood pressure\r\n | \r\n17.60% | \r\n
| \r\n | \r\n 6.2 Increase the proportion of adults aged 50 years and over\r\n with chronic kidney disease who currently take statins to lower\r\n their blood cholesterol\r\n | \r\n25.60% | \r\n
| CKD-7* | \r\n\r\n Reduce the number of deaths among persons with chronic kidney\r\n disease\r\n | \r\nNot applicable | \r\n
| CKD-8 | \r\n\r\n \r\n | \r\n352.1 PMP | \r\n
| CKD-9 | \r\nReduce kidney failure due to diabetes | \r\n\r\n |
| \r\n | \r\n \r\n | \r\n154.4 PMP | \r\n
| \r\n | \r\n \r\n | \r\n2,352.7 PMP | \r\n
| CKD-10 | \r\n\r\n \r\n | \r\n30.00% | \r\n
| CKD-11 | \r\nImprove vascular access for hemodialysis patients | \r\n\r\n |
| \r\n | \r\n \r\n | \r\n50.60% | \r\n
| \r\n | \r\n \r\n | \r\n26.10% | \r\n
| \r\n | \r\n \r\n | \r\n34.80% | \r\n
| CKD-12 | \r\n\r\n \r\n | \r\n18.70% | \r\n
| CKD-13 | \r\n\r\n Increase the proportion of patients with treated chronic kidney\r\n failure who receive a transplant\r\n | \r\n\r\n |
| \r\n | \r\n \r\n | \r\n20.10% | \r\n
| \r\n | \r\n \r\n | \r\nNot applicable | \r\n
| CKD-14 | \r\n\r\n Reduce deaths in persons with end-stage renal disease (ESRD)\r\n | \r\n\r\n |
| \r\n | \r\n \r\n | \r\n187.3 per 1,000 PY | \r\n
| \r\n | \r\n \r\n | \r\n335.0 per 1,000 PY | \r\n
| \r\n | \r\n \r\n | \r\n81.3 per 1,000 PY | \r\n
| \r\n | \r\n \r\n | \r\n27.8 per 1,000 PY | \r\n
| \r\n | \r\n \r\n | \r\n4.5 per 1,000 PY | \r\n
\r\n Data Source:{\" \"}\r\n
\r\n Abbreviations: CKD, chronic kidney disease; ESRD, end-stage renal\r\n disease; HbA1c, glycosylated hemoglobin; HP2020, Healthy People 2020;\r\n PMP, per million population; PY, patient-years\r\n
\r\n\r\n * These objectives use a data source other than USRDS, and are\r\n therefore not reported in this chapter.\r\n
\r\nIntroduction to Volume 2
\r\nVolume 2 provides data on the incidence and prevalence, characteristics, costs and utilization, and outcomes among individuals with ESRD in the U.S., as well as trends over time in these parameters. The primary sources of information about patients with ESRD are the Centers for Medicare & Medicaid Services (CMS) CROWN/REMIS (Consolidated Renal Operations in Web-Enabled Network/Renal Management Information System), CMS fee-for-service claims data, and the Organ Procurement and Transplantation Network (OPTN). These sources differ from the CMS 5% sample and NHANES data used in Volume 1 of the ADR in that there is a need to combine across multiple data sources. In addition, data on race and ethnicity are collected differently and available in more detail for patients with ESRD.
\r\nBuilding the ESRD Database
\r\nUSRDS assigns a unique identification (USRDS ID) number that allows each patient to be accurately tracked over time in the USRDS database across all associated treatment therapies, hospitalizations, outpatient encounters, and other healthcare events. Linkage across databases and assignment of USRDS IDs must be performed annually, linking new claims and other data to the correct individuals already in the database through comparison of all data sources, identifying new patients, and assigning USRDS IDs. Key patient attributes and identifiers, such as name, date of birth, sex, date of death, SSN, and HIC/BIC (Health Insurance Claim/Beneficiary Identification Code) identifier, have typically been used to uniquely identify each ESRD patient.
\r\nAs the process of building the ESRD database is executed, technical personnel analyze each database for duplicate records, consolidate records, and integrate the databases. Small differences, errors, or missing values for patient identifiers complicate this process, and matching rules must therefore be developed and applied. Overly stringent criteria may result in inclusion of some individuals more than once, whereas overly loose criteria risk combing different individuals into one record. Prior matching strategies appear to have been heavily reliant on requiring a SSN or HIC/BIC for inclusion in the database. However, requiring a SSN match results in exclusion of individuals who do not have SSNs and those whose SSN was entered incorrectly. Furthermore, Medicare has recently discontinued use of SSN as its primary form of identification of beneficiaries to better protect beneficiary privacy and financial information. The Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) required CMS to remove social security numbers (SSNs) from all Medicare cards, a process that was completed in April 2019. CMS has now assigned a randomly-generated alphanumeric Medicare Beneficiary Identification (MBIs) that is unrelated to SSN to all beneficiaries. All claims are required to contain this identifier as of January 1, 2020. By design, SSNs will be less reliably included in CMS databases going forward. For these reasons, USRDS has developed a matching process that does not require a SSN (as long as there is sufficient matching of other identifiers).
\r\nThis change has identified some additional incident and prevalent cases of ESRD, particularly in recent years, compared with the prior matching process. These newly identified individuals differ from the general ESRD population in that they are younger, are more likely to be Hispanic or Latino, and are concentrated in western states. We believe that a large percentage of these individuals may be undocumented immigrants, especially as many reside in states that reimburse maintenance dialysis through emergency Medicaid or through third-party charitable assistance (Cervantes et al., 2019). Thus, these individuals may have been excluded from the database because of missing SSN and Medicare HIC/BIC but are likely true cases of ESRD. We provide this explanation because discerning readers may note slightly higher ESRD incidence and prevalence counts and rates in this year’s ADR than in prior years, particularly from 2013 to 2017.
\r\nRace and ethnicity
\r\nInformation about race in the USRDS comes from several sources, including Form CMS-2728 (ESRD Medical Evidence Report), the CMS Medicare Enrollment Database (EDB), the REMIS patient file, and the CROWNWeb patient roster. The Medical Evidence Report is the primary source of information about race and ethnicity when available. Since the 1995 revision of the Medical Evidence Report, the categories of race recommended in Office of Budget and Management (OMB) guidance (Institute of Medicine, 2009) are included. Specifically, the five race categories are White, Black or African American, American Indian or Alaska Native, Asian, Native Hawaiian or Pacific Islander (and Other was recently added back to the form), with respondents able to designate all that apply. Ethnicity is ascertained separately from race as Hispanic or Latino or not Hispanic or Latino.
\r\nIn 2017, the USRDS reported the incidence and prevalence of ESRD for individuals in the Native Hawaiian or Pacific Islander race group separately (from Asians) for the first time (Saran et al., 2018). The extraordinarily high rates in this population caused concern (Naʻai & Raphael, 2019) and spurred further evaluation (Xiang et al., 2020), which has identified considerable uncertainty about the true rates in this population. Differences in availability of information about multi-racial individuals in the USRDS and the U.S. Census are a major source of this uncertainty. Over half of individuals who identify as Native Hawaiian or Pacific Islander (NHPI) in the U.S. Census also selected at least one other race category (Centers for Disease Control and Prevention, 2019). Thus, rate calculations that include only individuals designated solely as NHPI in the U.S. Census in the denominator will overestimate the incidence and prevalence of ESRD in this population.
\r\nHowever, including all individuals who designate NHPI in the denominator (including multiracial individuals) will almost certainly underestimate the prevalence because the USRDS (effectively) includes only one race. Although the Medical Evidence Report allows individuals to choose more than one race, fewer than 1% of individuals have more than one race category designated in the USRDS, and no one who started dialysis after 2012 has more than one category. Thus, the single race category in the USRDS is unlikely to be capturing all NHPI who self-report more than one race. Because there is no way to ascertain the true rates of ESRD in the NHPI population at present, and because the possible range is extremely wide, we do not report incidence and prevalence of ESRD for this race group in the text of the 2020 ADR.
\r\nWe calculated incidence and prevalence rates for other race groups using all individuals in the U.S. Census who designated that race (including multi-racial individuals) in the denominator for each group. This strategy results in a small decrease in rates because few individuals in these race groups designate more than one race. The problem of incomplete data on race in the USRDS is one that needs further exploration as the number of multiracial individuals in the U.S is expected to increase over time.
\r\nWe have treated ethnicity separately from race in the Volume 2 of the ADR rather than creating combined race and ethnicity categories. (Race and ethnicity were combined in some analyses in Volume 1 because they are not reported separately in the Medicare 5% sample.) In recognition of the overlapping but non-identical populations included in Hispanic and Latino groups, we have used both terms in the text of the ADR (Hispanic or Latino), but we have continued to use Hispanic in tables and figures in this year’s ADR to avoid the need to use non-standard abbreviations.
\r\nReferences
\r\n- \r\n
- Centers for Disease Control and Prevention. (2019). U.S. Census populations with bridged race categories. Retrieved August 4, 2020 from https://www.cdc.gov/nchs/nvss/bridged_race.htm \r\n
- Cervantes, L., Mundo, W., & Powe, N. R. (2019, Aug 7). The Status of Provision of Standard Outpatient Dialysis for US Undocumented Immigrants with ESKD. Clin J Am Soc Nephrol, 14(8), 1258-1260. https://doi.org/10.2215/cjn.03460319 \r\n
- IOM (Institute of Medicine). (2009). Race, ethnicity, and language data: standardization for health care quality improvement. T. N. A. Press. \r\n
- Naʻai, D., & Raphael, K. L. (2019, Nov 7). CKD in Native Hawaiians and Pacific Islanders: Trouble in Paradise. Clin J Am Soc Nephrol, 14(11), 1661-1663. https://doi.org/10.2215/cjn.03260319 \r\n
- Saran, R., Robinson, B., Abbott, K. C., Agodoa, L. Y. C., Bhave, N., Bragg-Gresham, J., Balkrishnan, R., Dietrich, X., Eckard, A., Eggers, P. W., Gaipov, A., Gillen, D., Gipson, D., Hailpern, S. M., Hall, Y. N., Han, Y., He, K., Herman, W., Heung, M., Hirth, R. A., Hutton, D., Jacobsen, S. J., Jin, Y., Kalantar-Zadeh, K., Kapke, A., Kovesdy, C. P., Lavallee, D., Leslie, J., McCullough, K., Modi, Z., Molnar, M. Z., Montez-Rath, M., Moradi, H., Morgenstern, H., Mukhopadhyay, P., Nallamothu, B., Nguyen, D. V., Norris, K. C., O'Hare, A. M., Obi, Y., Park, C., Pearson, J., Pisoni, R., Potukuchi, P. K., Rao, P., Repeck, K., Rhee, C. M., Schrager, J., Schaubel, D. E., Selewski, D. T., Shaw, S. F., Shi, J. M., Shieu, M., Sim, J. J., Soohoo, M., Steffick, D., Streja, E., Sumida, K., Tamura, M. K., Tilea, A., Tong, L., Wang, D., Wang, M., Woodside, K. J., Xin, X., Yin, M., You, A. S., Zhou, H., & Shahinian, V. (2018, Mar). US Renal Data System 2017 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am J Kidney Dis, 71(3 Suppl 1), A7. https://doi.org/10.1053/j.ajkd.2018.01.002 \r\n
- Xiang, J., Morgenstern, H., Li, Y., Steffick, D., Bragg-Gresham, J., Panapasa, S., Raphael, K. L., Robinson, B. M., Herman, W. H., & Saran, R. (2020, May 5). Incidence of ESKD Among Native Hawaiians and Pacific Islanders Living in the 50 US States and Pacific Island Territories. Am J Kidney Dis. https://doi.org/10.1053/j.ajkd.2020.01.008 \r\n
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\r\n );\r\n};\r\n\r\nexport default ESRDAnalyticalMethods2020;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router\";\r\n\r\nimport config from \"../../../config/config\";\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst ESRDAnalyticalMethods2021 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=2`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
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\r\n );\r\n};\r\n\r\nexport default ESRDAnalyticalMethods2021;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router\";\r\n\r\nimport config from \"../../../config/config\";\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst ESRDAnalyticalMethods2022 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=2`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
\r\n- \r\n
- \r\n \r\n \r\n
- download(\"Cause of Death – ESRD Volume\")}>\r\n \r\n \r\n
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\r\n );\r\n};\r\n\r\nexport default ESRDAnalyticalMethods2022;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router\";\r\n\r\nimport config from \"../../../config/config\";\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst ESRDAnalyticalMethods2023 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=2`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
\r\n- \r\n
- \r\n \r\n \r\n
- download(\"Cause of Death - ESRD Volume\")}>\r\n \r\n \r\n
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\r\n );\r\n};\r\n\r\nexport default ESRDAnalyticalMethods2023;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router\";\r\n\r\nimport config from \"../../../config/config\";\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst ESRDAnalyticalMethods2024 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=2`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
\r\n- \r\n
- \r\n \r\n \r\n
- download(\"Cause_of_Death_-_ESRD_Volume_2023\")}>\r\n \r\n \r\n
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\r\n );\r\n};\r\n\r\nexport default ESRDAnalyticalMethods2024;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router\";\r\nimport ESRDAnalyticalMethods2020 from \"./ESRDAnalyticalMethods2020\";\r\nimport ESRDAnalyticalMethods2021 from \"./ESRDAnalyticalMethods2021\";\r\nimport ESRDAnalyticalMethods2022 from \"./ESRDAnalyticalMethods2022\";\r\nimport ESRDAnalyticalMethods2023 from \"./ESRDAnalyticalMethods2023\";\r\nimport ESRDAnalyticalMethods2024 from \"./ESRDAnalyticalMethods2024\";\r\n\r\nconst ESRDAnalyticalMethods = () => {\r\n const { year } = useParams();\r\n if (year === \"2020\") {\r\n return Analytical Methods
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- download(\"Cause_of_Death___ESRD_Volume_2024\")}>\r\n \r\n \r\n
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\r\n );\r\n};\r\n\r\nexport default CKDAnalyticalMethods2020;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router-dom\";\r\n\r\nimport config from \"../../../config/config\";\r\n\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst CKDAnalyticalMethods2021 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=1`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
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\r\n );\r\n};\r\n\r\nexport default CKDAnalyticalMethods2021;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router-dom\";\r\n\r\nimport config from \"../../../config/config\";\r\n\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst CKDAnalyticalMethods2022 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=1`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
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\r\n );\r\n};\r\n\r\nexport default CKDAnalyticalMethods2022;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router-dom\";\r\n\r\nimport config from \"../../../config/config\";\r\n\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst CKDAnalyticalMethods2023 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=1`;\r\n window.location = url;\r\n };\r\n\r\n return (\r\n Analytical Methods
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\r\n );\r\n};\r\n\r\nexport default CKDAnalyticalMethods2023;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router-dom\";\r\n\r\nimport config from \"../../../config/config\";\r\n\r\nimport \"./AnalyticalMethods.scss\";\r\n\r\nconst CKDAnalyticalMethods2024 = () => {\r\n const { year } = useParams();\r\n\r\n const download = (refNum) => {\r\n const url = `${config.baseUri}/analyticalMethods?year=${year}&fileName=${refNum}&volumeNumber=1`;\r\n window.location = url;\r\n };\r\n \r\n return (\r\n Analytical Methods
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\r\n );\r\n};\r\n\r\nexport default CKDAnalyticalMethods2024;\r\n","import React from \"react\";\r\nimport { useParams } from \"react-router\";\r\nimport CKDAnalyticalMethods2020 from \"./CKDAnalyticalMethods2020\";\r\nimport CKDAnalyticalMethods2021 from \"./CKDAnalyticalMethods2021\";\r\nimport CKDAnalyticalMethods2022 from \"./CKDAnalyticalMethods2022\";\r\nimport CKDAnalyticalMethods2023 from \"./CKDAnalyticalMethods2023\";\r\nimport CKDAnalyticalMethods2024 from \"./CKDAnalyticalMethods2024\";\r\n\r\n\r\nconst CKDAnalyticalMethods = () => {\r\n const { year } = useParams();\r\n if (year === \"2020\") {\r\n return Analytical Methods
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\r\n Healthy People 2030 CKD Objectives\r\n \r\n Download All Objectives\r\n \r\n
\r\n | Objective | \r\nIndicator | \r\nTarget | \r\n
| Chronic Kidney Disease — General | \r\n||
| CKD-03 | \r\n\r\n | \r\n 16.4% | \r\n
| CKD-04 | \r\n\r\n | \r\n 48.8% | \r\n
| CKD-07 | \r\n\r\n {\" \"}\r\n | \r\n 290.0 PMP | \r\n
| CKD-08 | \r\n\r\n | \r\n 10% | \r\n
| CKD-09 | \r\n\r\n | \r\n 19.7% | \r\n
| CKD-10 | \r\n\r\n | \r\n 117.2 per 1,000 PY | \r\n
| Diabetes | \r\n||
| D-05 | \r\n\r\n | \r\n 66.4% | \r\n
\r\n Data Source:{\" \"}\r\n
\r\n Abbreviations: CKD, chronic kidney disease; HP2030, Healthy People\r\n 2030; PMP, per million population; PY, patient-years\r\n
\r\n\r\n Healthy People 2030 CKD Objectives\r\n \r\n Download All Objectives\r\n \r\n
\r\n | Objective | \r\nIndicator | \r\nTarget | \r\n
| Chronic Kidney Disease — General | \r\n||
| CKD-03 | \r\n\r\n | \r\n 16.4% | \r\n
| CKD-04 | \r\n\r\n | \r\n 48.8% | \r\n
| CKD-07 | \r\n\r\n {\" \"}\r\n | \r\n 290.0 PMP | \r\n
| CKD-08 | \r\n\r\n | \r\n 10% | \r\n
| CKD-09 | \r\n\r\n | \r\n 19.7% | \r\n
| CKD-10 | \r\n\r\n | \r\n 117.2 per 1,000 PY | \r\n
| Diabetes | \r\n||
| D-05 | \r\n\r\n | \r\n 66.4% | \r\n
\r\n Data Source:{\" \"}\r\n
\r\n Abbreviations: CKD, chronic kidney disease; HP2030, Healthy People\r\n 2030; PMP, per million population; PY, patient-years\r\n
\r\n\r\n Healthy People 2030 CKD Objectives\r\n \r\n Download All Objectives\r\n \r\n
\r\n | Objective | \r\nIndicator | \r\nTarget | \r\n
| Chronic Kidney Disease — General | \r\n||
| CKD-03 | \r\n\r\n | \r\n 16.4% | \r\n
| CKD-04 | \r\n\r\n | \r\n 49.5%^ | \r\n
| CKD-07 | \r\n\r\n {\" \"}\r\n | \r\n 290.0 PMP | \r\n
| CKD-08 | \r\n\r\n | \r\n 9.7%^ | \r\n
| CKD-09 | \r\n\r\n | \r\n 19.7% | \r\n
| CKD-10 | \r\n\r\n | \r\n 117.2 per 1,000 PY | \r\n
| Diabetes | \r\n||
| D-05 | \r\n\r\n | \r\n 66.4% | \r\n
\r\n Data Source:{\" \"}\r\n
\r\n Abbreviations: CKD, chronic kidney disease; HP2030, Healthy People\r\n 2030; PMP, per million population; PY, patient-years\r\n
\r\n\r\n ^Target has been revised in 2023\r\n
\r\n\r\n Healthy People 2030 CKD Objectives\r\n \r\n Download All Objectives\r\n \r\n
\r\n | Objective | \r\nIndicator | \r\nTarget | \r\n
| Chronic Kidney Disease — General | \r\n||
| CKD-03 | \r\n\r\n | \r\n 16.4% | \r\n
| CKD-04 | \r\n\r\n | \r\n 49.5%^ | \r\n
| CKD-07 | \r\n\r\n {\" \"}\r\n | \r\n 290.0 PMP | \r\n
| CKD-08 | \r\n\r\n | \r\n 9.7%^ | \r\n
| CKD-09 | \r\n\r\n | \r\n 19.7% | \r\n
| CKD-10 | \r\n\r\n | \r\n 117.2 per 1,000 PY | \r\n
| Diabetes | \r\n||
| D-05 | \r\n\r\n | \r\n 66.4% | \r\n
\r\n Reference:{\" \"}\r\n
\r\n Abbreviations: CKD, chronic kidney disease; HP2030, Healthy People\r\n 2030; PMP, per million population; PY, patient-years\r\n
\r\n\r\n ^Target was revised in 2023\r\n
\r\nIntroduction
\r\n\r\n The 2021 United States Renal Data System Annual Data Report (ADR) is\r\n again presented in an interactive format, which we introduced with the\r\n 2020 ADR. However, the content has been improved, restructured, and\r\n expanded. Building on the COVID-19 Supplement (coronavirus disease\r\n 2019) introduced in the 2020 ADR, we continue the ADR’s critical\r\n surveillance mission by including an updated COVID-19 Supplement that\r\n presents many outcomes through the end of 2020 and some through the\r\n second quarter of 2021. We utilize quarterly claims data from payment\r\n year 2020 to describe COVID testing and cases, incidence of\r\n COVID-related AKI, utilization of therapeutic interventions (e.g.,\r\n hospitalization, ICU care, mechanical ventilation), and post-discharge\r\n outcomes in COVID survivors.\r\n
\r\n\r\n The 2021 ADR includes a new chapter focused on racial and ethnic\r\n disparities in healthcare delivery and outcomes in the CKD and ESRD\r\n populations. This chapter does not replace material presented\r\n elsewhere in the ADR reporting incidence, prevalence, and outcome data\r\n by race and ethnicity. Rather, this chapter examines possible\r\n contributors to the observed disparities with an emphasis on social\r\n determinants of health and access to care. This chapter examines\r\n disparities in the context of CKD, AKI, dialysis, and kidney\r\n transplantation, and because it spans the continuum of kidney disease,\r\n we present it as a supplement rather than as part of the CKD or ESRD\r\n volume.\r\n
\r\n\r\n We have also included a new chapter on home dialysis. Many other\r\n chapters in the ESRD volume present outcomes by modality, but this\r\n chapter delves into greater detail and presents information not\r\n previously captured in the ADR. For example, we examine\r\n characteristics of patients performing home dialysis, the way in which\r\n home dialysis is delivered, complications experienced by patients\r\n performing home dialysis, and switches between home modalities and\r\n in-facility hemodialysis.\r\n
\r\n\r\n We have eliminated the chapters dedicated to cardiovascular disease,\r\n dispersing much of their content into the relevant remaining chapters.\r\n For example, data on cardiovascular events is presented in the\r\n hospitalization chapters, and medication utilization among patients\r\n with cardiovascular conditions is reported in the prescription drug\r\n chapters.\r\n
\r\n- \r\n
- \r\n \r\n Optum® de-identified Clinformatics® Data\r\n Mart database:\r\n {\" \"}\r\n Optum® de-identified Clinformatics\r\n ® Data Mart database, reintroduced in the 2021 ADR,\r\n provides paid medical and prescription claims and enrollment\r\n information for participants in commercial insurance plans and\r\n Medicare Advantage plans of a large U.S. managed-care health\r\n insurance company. Included plan members are enrolled in both a\r\n medical and a prescription plan, and the sample represents all\r\n areas of the country. Optum data from 2019 are used in\r\n estimating CKD prevalence, assessing the burden of illness and\r\n hospitalizations in CKD patients in the CKD volume.\r\n \r\n
- \r\n \r\n CMS Medicaid T-MSIS Analytic Files:\r\n {\" \"}\r\n The CMS Transformed Medicaid Statistical Information System\r\n (T-MSIS) analytical file contains information on Medicaid\r\n beneficiaries and CHIP program enrollees. The information\r\n includes enrollment records, service utilization, claims, and\r\n management care. New in this year’s ADR, the USRDS requested the\r\n T-MSIS files for beneficiaries with advanced CKD and AKI\r\n diagnosis/procedure codes in 2018-2019. These data are used in\r\n various chapters in the CKD volume.\r\n \r\n
- \r\n \r\n The ESRD Quality Reporting System (EQRS) data:\r\n {\" \"}\r\n The ESRD Quality Reporting System (EQRS)replaces and updates the\r\n legacy CROWNWeb/REMIS. EQRS is a national registry for ESRD\r\n patients in the U.S. EQRS captures clinical and administrative\r\n data for all ESRD patients, including the CMS-2728 Medical\r\n Evidence Report, CMS-2746 ESRD Death Notification, ESRD\r\n treatment modalities, and inpatient stays. Recently acquired\r\n EQRS data include information through the second quarter of\r\n 2021. These data are used to track COVID-19 among ESRD patients\r\n and are presented in the COVID-19 supplement of this year’s ADR.\r\n \r\n
- \r\n \r\n The Medicare Provider Analysis and Review (MedPAR) data:\r\n {\" \"}\r\n New in this year’s ADR, MedPAR data contains inpatient and\r\n Skilled Nursing Facility (SNF) stay records for Medicare\r\n beneficiaries from the National Claims History (NCH). We use\r\n MedPAR data to estimate rates of all cause and cause-specific\r\n hospitalization among adult patients receiving dialysis who were\r\n covered by Medicare Advantage plans in 2019 and to compare these\r\n rates with those among the Medicare FFS population.\r\n \r\n
\r\n The need to process and finalize medical claims introduces an\r\n unavoidable lag between enrollees’ receipt of clinical care and\r\n availability of claims data. Thus, 2019 is the most recent year for\r\n which data are available for most analyses in the 2021 ADR. We note\r\n that data for 2019 – and trends over the decade leading up to 2019 –\r\n are likely to form an important “baseline” upon which to examine\r\n substantial clinical and policy changes that began in 2020. Most\r\n notably, preliminary data have already shown that the COVID-19\r\n pandemic led to substantial mortality in the ESRD population\r\n (Weinhandl, Wetmore, et al., 2021) and a simultaneous decline in rates\r\n of incident ESRD (Wetmore et al., 2021) (see the COVID-19 Supplement\r\n for updated data). Together, these events brought about the first\r\n substantial shrinkage in the ESRD population (Weinhandl, Gilbertson,\r\n et al., 2021). Initiation of in-facility hemodialysis declined to a\r\n greater extent than initiation of peritoneal dialysis, leading to an\r\n increase in the percentage of new ESRD patients starting peritoneal\r\n dialysis that was not accompanied by an increase in new peritoneal\r\n dialysis starts (Wetmore et al., 2021).\r\n
\r\n\r\n On July 10, 2019, the White House and the Department of Health and\r\n Human Services unveiled the Advancing American Kidney Health (AAKH)\r\n initiative with the objectives of preventing kidney failure and\r\n improving access to person-centered care and transplantation among\r\n patients with ESRD (U.S. Department of Health and Human Services,\r\n 2019). The president’s Executive Order announcing the initiative set\r\n forth ambitious targets for increasing the use of home dialysis\r\n therapies and kidney transplantation, directed Medicare to develop and\r\n test payment models to create incentives aligned with these\r\n objectives, and introduced revisions (which were finalized in December\r\n 2020) to the performance outcome measures for organ procurement\r\n organizations. Although the Kidney Care Choices models were delayed\r\n until January 2022, ESRD Treatment Choices (ETC) launched in January\r\n 2021. Although CMS and its contractors will perform formal monitoring\r\n of the impact of these programs, the USRDS will also present changes\r\n in care of patients with CKD and ESRD in upcoming ADRs as the\r\n nephrology community enters the post-COVID, AAKH era. Data from this\r\n year’s ADR – and from 2019 in particular – will serve as a reference\r\n point for assessments of the impact of these policy initiatives.\r\n
\r\n\r\n Although 2020 truly marks the end of the decade of the 2010s, it may\r\n be appropriate to summarize the progress in the last decade ending\r\n with 2019 given the upheavals that will become apparent in 2020 and\r\n the changes in provision and reimbursement of care of dialysis\r\n patients that occurred in the last decade. Providers have been\r\n preparing for or operating under an evolving bundled payment system\r\n and the Quality Improvement Program (QIP) that came with it for most\r\n of the decade (since 2011). As providers adapted to these large\r\n changes in reimbursement and searched for financial efficiencies,\r\n there have been a number of changes in dialysis patient care that have\r\n had clear financial consequences. Examples include the transition from\r\n epoetin alfa to pegylated epoetin beta as the leading agent for the\r\n treatment of anemia; the steady growth of iron-based phosphate binders\r\n despite the concurrent arrival of inexpensive, generic sevelamer;\r\n rapid uptake of etelcalcetide while transitional add-on payments to\r\n Medicare reimbursement for dialysis were available; and introduction\r\n of oral calcitriol as a substitute for intravenous vitamin D receptor\r\n activators. To date, the effects of these changes on patient outcomes\r\n are not clear. The supply and cost of labor (including nurses and\r\n technicians) may be the next big driver of evolution of care delivery\r\n in the coming decade.\r\n
\r\n- \r\n
- \r\n CKD outcomes\r\n
- \r\n
- \r\n A 22% reduction in adjusted all-cause mortality among\r\n Medicare fee-for-service (FFS) beneficiaries ≥66 years of\r\n age with CKD that was more than twice as large as the\r\n reduction in mortality observed among beneficiaries without\r\n CKD.\r\n \r\n
- \r\n A 29% reduction in the adjusted rate of all-cause\r\n hospitalization among Medicare FFS beneficiaries aged 66\r\n years or older with CKD.\r\n \r\n
- \r\n A 14% reduction in readmission after hospital discharge\r\n among older Medicare FFS beneficiaries with CKD.\r\n \r\n
\r\n - \r\n ESRD outcomes\r\n
- \r\n
- \r\n An increase in the percentage of older Medicare\r\n beneficiaries with prior CKD initiating dialysis outside of\r\n the hospital since 2014, reaching almost 60%.\r\n \r\n
- \r\n A 7% reduction in adjusted ESRD incidence to 373 per million\r\n population in 2019.\r\n \r\n
- \r\n A 25% reduction in the percentage of patients initiating\r\n dialysis with eGFR ≥15 ml/min/1.73m2.\r\n \r\n
- \r\n An 85% increase in the percentage of incident dialysis\r\n patients starting home dialysis, and a 73% increase in the\r\n percentage of patients performing home dialysis one year\r\n after dialysis initiation.\r\n \r\n
- \r\n A 61% reduction in the rate of hospitalization for\r\n peritonitis and a 36% reduction in the rate of\r\n hospitalization for catheter complications among patients\r\n performing peritoneal dialysis.\r\n \r\n
- \r\n A 13% reduction in adjusted rate of all-cause\r\n hospitalization among prevalent hemodialysis patients, 14%\r\n reduction among prevalent peritoneal dialysis patients, and\r\n 11% reduction among kidney transplant recipients. Reductions\r\n in the rate of all-cause hospitalization in the first year\r\n after dialysis initiation were even larger at 18% for\r\n patients treated with hemodialysis and 20% among those\r\n performing peritoneal dialysis.\r\n \r\n
- \r\n A 17.5% reduction in adjusted all-cause mortality among\r\n patients on hemodialysis and a 21% reduction among patients\r\n performing peritoneal dialysis.\r\n \r\n
- \r\n Increase in the rate of kidney transplantation among\r\n patients with ESRD that began in the second half of the\r\n decade – a reversal that followed a period of decline during\r\n the first half of the decade.\r\n \r\n
\r\n
\r\n These developments should be celebrated. However, progress on several\r\n of these metrics slowed or stalled during the second half of the\r\n decade. This was true for rates of hospitalization among patients with\r\n CKD, receiving maintenance dialysis, and with a functioning kidney\r\n transplant. The downward trajectory of mortality among patients\r\n receiving maintenance dialysis also flattened after about 2014, and\r\n there has been no further reduction in early dialysis initiation in\r\n the last few years. Furthermore, important metrics, such as rates of\r\n acute kidney injury among patients with CKD and rates of catheter use\r\n among incident hemodialysis patients, have not improved.\r\n
\r\n\r\n The extensive characterization of changes over the last decade and of\r\n the state of healthcare utilization and outcomes in the CKD and ESRD\r\n populations in 2019 presented in this year’s ADR will form the\r\n backdrop upon which the effects of the COVID-19 pandemic and new\r\n payment models can be reported in subsequent ADRs.\r\n
\r\nNotes about race and ethnicity
\r\n\r\n In the 2021 ADR, we present data in the CKD and ESRD volumes using\r\n combined categories defined by race and ethnicity. Hispanic\r\n individuals are considered as a separate category (that includes\r\n Hispanics of all races). Other race groups include non-Hispanic\r\n individuals within those groups (e.g., non-Hispanic White,\r\n non-Hispanic Black). This strategy is consistent with race and\r\n ethnicity categories available within Medicare claims data but\r\n represents a change from how race and ethnicity have been previously\r\n presented in the ESRD volume. This change serves to better align race\r\n and ethnicity categories in the CKD and ESRD volumes. In addition,\r\n this strategy facilitates direct comparisons among Hispanic and\r\n non-Hispanic individuals in different race groups that were not\r\n possible previously for those with ESRD. In other words, rather than\r\n simply displaying data for Hispanic individuals alongside data for a\r\n multiracial group of non-Hispanic individuals, figures display\r\n Hispanic, non-Hispanic White, non-Hispanic Black, and often other race\r\n groups as separate categories. However, to avoid using abbreviations\r\n in figure tabs and to streamline descriptions of findings, we do not\r\n include “non-Hispanic” in the names of each race category. We present\r\n data for Hispanic individuals and individuals of smaller\r\n race/ethnicity categories whenever possible, but in many instances,\r\n stable estimates of outcomes cannot be generated for smaller\r\n race/ethnicity categories. This occurs most often among children and\r\n for some relatively rare outcomes among patients with CKD. In\r\n addition, we do not stratify by race/ethnicity in analyses using\r\n Medicaid data because race/ethnicity information is missing entirely\r\n in many states and is missing for the majority of beneficiaries in\r\n many other states. Therefore, it is not possible to examine\r\n race/ethnicity groups that are representative of the U.S. population\r\n using Medicaid data.\r\n
\r\n\r\n In 2017, the USRDS reported incidence and prevalence of ESRD for\r\n individuals in the Native Hawaiian or Pacific Islander (NHPI) race\r\n group separately (from Asians) for the first time (Saran et al.,\r\n 2018). The extraordinarily high rates in this population caused\r\n concern (Naʻai & Raphael, 2019) and spurred further evaluation\r\n (Xiang et al., 2020, Johansen et al., 2022), which has identified\r\n considerable uncertainty about the true rates in this population.\r\n Differences in availability of information about multi-racial\r\n individuals in the USRDS and the U.S. Census are a major source of\r\n this uncertainty. Over half of individuals who identify as NHPI in the\r\n U.S. Census also selected at least one other race category (Centers\r\n for Disease Control and Prevention, 2019). Thus, rate calculations\r\n that include only individuals designated solely as NHPI in the U.S.\r\n Census in the denominator will overestimate the incidence and\r\n prevalence of ESRD in this population.\r\n
\r\n\r\n However, including all individuals who designate NHPI in the\r\n denominator (including multiracial individuals) will almost certainly\r\n underestimate the prevalence because the USRDS (effectively)\r\n designates individuals as belonging in only one race category.\r\n Although the Medical Evidence Report (form CMS 2728) allows\r\n individuals to choose more than one race, fewer than 1% of individuals\r\n have more than one race category designated in the USRDS, and no one\r\n who started dialysis after 2012 has more than one category. (This\r\n situation is the result of data entry into and retrieval and\r\n processing of data from CROWNWeb, the ultimate source of race data for\r\n the ESRD population in the USRDS.) Thus, the single race category in\r\n the USRDS is unlikely to be capturing all NHPI who self-report more\r\n than one race. Because there is no way to ascertain the true rates of\r\n ESRD in the NHPI population at present, and because the possible range\r\n is extremely wide, we do not report incidence and prevalence of ESRD\r\n for this race group in the text of the 2020 ADR. However, we do report\r\n outcomes among this race group when sample size allows stable\r\n estimates.\r\n
\r\n\r\n We calculated incidence and prevalence rates for other race groups\r\n using all individuals in the U.S. Census who designated that race\r\n (including multi-racial individuals) in the denominator for each\r\n group. This strategy results in a small decrease in rates because few\r\n individuals in these race groups designate more than one race. The\r\n problem of incomplete data on race in the USRDS is one that needs\r\n further exploration as the number of multiracial individuals in the\r\n U.S has increased over time. Specifically, the 2020 Census reports a\r\n 276% increase in the Multiracial population of the United States since\r\n 2010 (Jones et al., 2021).{\" \"}\r\n
\r\nReferences
\r\n- \r\n
- \r\n Centers for Disease Control and Prevention. (2019). U.S. Census\r\n populations with bridged race categories. Retrieved August 4, 2020\r\n from{\" \"}\r\n
- \r\n Johansen KL, Wetmore JB, Peng Y, Liu J, Weinhandl ED, Gilbertson DT.\r\n Variation in incidence of ESKD among individuals of Native\r\n Hawaiian/Pacific Islander race based on data from the United States\r\n Renal Data System. Am J Kidney Dis, 2022, in press.\r\n \r\n
- \r\n Jones, N., Marks, R., Ramirez, R., & Rios-Vargas, M. (2021).{\" \"}\r\n \r\n 2020 Census illuminates racial and ethnic composition of the\r\n country.\r\n {\" \"}\r\n United States Census Bureau. Retrieved November 19, 2021 from{\" \"}\r\n
- \r\n Naʻai, D., & Raphael, K. L. (2019, Nov 7). CKD in Native Hawaiians\r\n and Pacific Islanders: Trouble in Paradise. Clin J Am Soc Nephrol,\r\n 14(11), 1661-1663.{\" \"}\r\n
- \r\n Saran, R., Robinson, B., Abbott, K. C., Agodoa, L. Y. C., Bhave, N.,\r\n Bragg-Gresham, J., Balkrishnan, R., Dietrich, X., Eckard, A., Eggers,\r\n P. W., Gaipov, A., Gillen, D., Gipson, D., Hailpern, S. M., Hall, Y.\r\n N., Han, Y., He, K., Herman, W., Heung, M., Hirth, R. A., Hutton, D.,\r\n Jacobsen, S. J., Jin, Y., Kalantar-Zadeh, K., Kapke, A., Kovesdy, C.\r\n P., Lavallee, D., Leslie, J., McCullough, K., Modi, Z., Molnar, M. Z.,\r\n Montez-Rath, M., Moradi, H., Morgenstern, H., Mukhopadhyay, P.,\r\n Nallamothu, B., Nguyen, D. V., Norris, K. C., O'Hare, A. M., Obi, Y.,\r\n Park, C., Pearson, J., Pisoni, R., Potukuchi, P. K., Rao, P., Repeck,\r\n K., Rhee, C. M., Schrager, J., Schaubel, D. E., Selewski, D. T., Shaw,\r\n S. F., Shi, J. M., Shieu, M., Sim, J. J., Soohoo, M., Steffick, D.,\r\n Streja, E., Sumida, K., Tamura, M. K., Tilea, A., Tong, L., Wang, D.,\r\n Wang, M., Woodside, K. J., Xin, X., Yin, M., You, A. S., Zhou, H.,\r\n & Shahinian, V. (2018, Mar). US Renal Data System 2017 Annual Data\r\n Report: Epidemiology of Kidney Disease in the United States. Am J\r\n Kidney Dis, 71(3 Suppl 1), A7.{\" \"}\r\n
- \r\n U.S. Department of Health and Human Services. (2019). Advancing\r\n American Kidney Health.{\" \"}\r\n
- \r\n Weinhandl, E. D., Gilbertson, D. T., Wetmore, J. B., & Johansen,\r\n K. L. (2021, Oct). COVID-19-Associated Decline in the Size of the\r\n End-Stage Kidney Disease Population in the United States. Kidney Int\r\n Rep, 6(10), 2698-2701.{\" \"}\r\n
- \r\n Weinhandl, E. D., Wetmore, J. B., Peng, Y., Liu, J., Gilbertson, D.\r\n T., & Johansen, K. L. (2021, Jun 1). Initial Effects of COVID-19\r\n on Patients with ESKD. J Am Soc Nephrol, 32(6), 1444-1453.{\" \"}\r\n
- \r\n Wetmore, J. B., Johansen, K. L., Liu, J., Peng, Y., Gilbertson, D. T.,\r\n & Weinhandl, E. D. (2021, Nov). Changes in Treatment of Patients\r\n with Incident ESKD during the Novel Coronavirus Disease 2019 Pandemic.\r\n J Am Soc Nephrol, 32(11), 2948-2957.{\" \"}\r\n
- \r\n Xiang, J., Morgenstern, H., Li, Y., Steffick, D., Bragg-Gresham, J.,\r\n Panapasa, S., Raphael, K. L., Robinson, B. M., Herman, W. H., &\r\n Saran, R. (2020, May 5). Incidence of ESKD Among Native Hawaiians and\r\n Pacific Islanders Living in the 50 US States and Pacific Island\r\n Territories. Am J Kidney Dis.{\" \"}\r\n
Introduction
\r\n\r\n The United States Renal Data System 2022 Annual Data Report (ADR) contains data \r\n from medical claims through 2020 and for some ESRD-related metrics through the first \r\n half of 2021. As such, this is the first year in which the wide-ranging effects of \r\n the coronavirus disease 2019 (COVID-19) pandemic on the CKD and ESRD populations \r\n can be placed into the full context of the years that preceded its onset. Another \r\n important aspect of this year’s ADR is a continued focus on racial, ethnic, and \r\n socioeconomic disparities in access to healthcare and outcomes. Unfortunately, these \r\n two topics intersect in the form of racial and ethnic disparities in vulnerability \r\n and susceptibility to COVID-19 that further exposed and exacerbated pre-existing \r\n disparities in incidence, prevalence, and care of patients with kidney disease.\r\n
\r\n\r\n Direct and indirect effects of COVID-19 on the CKD and ESRD populations\r\n
\r\n\r\n The devastating effects of the COVID-19 pandemic on the CKD and ESRD populations \r\n permeate the 2022 ADR. The 2022 ADR includes data on medical care and outcomes \r\n through calendar year 2020 (although some data for the first half of 2021 for the \r\n ESRD population are included). Although we presented early views into the impact \r\n of the COVID-19 pandemic on the ESRD population in the 2020 ADR and expanded these \r\n analyses to include examination of COVID-19 diagnoses and outcomes in the CKD \r\n population in the 2021 ADR, the full magnitude of the direct and indirect effects \r\n of the pandemic on these populations comes into sharp focus throughout this year’s \r\n report.\r\n
\r\n\r\n The direct effects of COVID-19 can be measured by examining patterns of patient \r\n testing, hospitalization, and mortality. Over 10% of patients with CKD, 13% of \r\n patients with a kidney transplant, and 20% of patients on dialysis in January of \r\n 2020 were diagnosed with COVID-19 by the end of June 2021, rates that were \r\n approximately 50%, 100%, and 200% higher than that of Medicare beneficiaries \r\n without CKD, respectively. Although the incidence of COVID-19 testing was higher \r\n among individuals with CKD, the incidence of hospitalization after COVID-19 \r\n diagnosis among patients with CKD was more than double that of patients those \r\n without CKD in 2020; patients receiving dialysis consistently had hospitalization \r\n rates higher still than those with CKD. Mortality at 14, 30, and 90 days after \r\n diagnosis of COVID-19 was more than twice as high among beneficiaries with CKD \r\n as among those without. Nearly one-quarter of patients with CKD who were diagnosed \r\n with COVID-19 died within 90 days. Mortality after COVID-19 diagnosis was even \r\n higher for patients with ESRD, reaching 40.5% for patients on dialysis and 44.1% \r\n among kidney transplant recipients 90 days after diagnosis. \r\n
\r\n\r\n The ultimate result of the higher incidence of COVID-19 and higher mortality after \r\n diagnosis of COVID-19 among patients with CKD and ESRD was the unprecedented shrinking \r\n of the prevalence of diagnosed CKD (CKD Volume, Figure 2.1) and ESRD (ESRD Volume, \r\n Figure 1.5) in 2020. For example, the absolute increase in mortality in 2020 among \r\n patients with CKD was 8.9 deaths per 1,000 person-years compared with 6.1 per 1,000 \r\n person-years among individuals without CKD (Figure 3.2a). By the end of 2020, the \r\n population with diagnosed CKD had decreased by 4.3% from 2019. Some of the decline \r\n in the CKD population in 2020 may have been an artifact of fewer opportunities to \r\n accrue CKD diagnoses given the lower rates of hospitalization that occurred in 2020, \r\n combined with a general reduction in overall interaction with the healthcare system \r\n that occurred across the U.S. However, this is not true of the ESRD population, whose \r\n tracking through EQRS and OPTN does not rely on diagnosis claims. As a result of fewer \r\n patients reaching diagnosed ESRD and the increase in mortality rate among patients with \r\n ESRD attributable to the pandemic and its effects, the rate of prevalent ESRD decreased \r\n by almost 2% in 2020.\r\n
\r\n\r\n Indirect pandemic effects may have also affected patients with CKD to a greater extent \r\n than patients without kidney disease. Rates of emergency department encounters and \r\n hospitalizations decreased substantially in 2020 among patients with and without CKD \r\n and ESRD. However, the negative consequences of forgoing this medical care may have \r\n led to a disproportionate increase in mortality among patients with CKD because of \r\n their higher comorbidity burden and higher a priori risk of adverse outcomes. For \r\n example, mortality increased more in 2020 among patients with stage 4 and 5 CKD than \r\n among patients with stage 3 CKD. \r\n
\r\n\r\n Mortality after COVID-19 was higher among Black and Hispanic Medicare beneficiaries \r\n with CKD than among White beneficiaries (Figure 13.5). As a direct result of this \r\n higher COVID-19-related mortality and, possibly, more limited access to non-COVID-19-related \r\n medical care, mortality increased more among Black than among White beneficiaries with \r\n stage 4 and 5 CKD in 2020. This resulted in a reversal of the longstanding observation \r\n of lower mortality among Black patients. In other words, whereas Black beneficiaries had \r\n lower mortality than White ones in 2019 and prior years, they had higher mortality than \r\n their White counterparts in 2020 (Figure 3.2b). Although unadjusted mortality was not \r\n higher among Black than among White patients with ESRD, rates of COVID-19 diagnosis were \r\n higher (Figure 13.2b). A similar reversal of the Black-White mortality difference occurred \r\n in transplant recipients: mortality was higher among White recipients in 2019 but among \r\n Black recipients in 2020 (Figure 6.5b). The mortality difference did not reverse among \r\n patients treated with dialysis, but it did narrow from 43% higher mortality among White \r\n patients in 2019 to only 30% higher mortality in 2020.\r\n
\r\n\r\n Other direct and indirect effects of COVID-19 and the changes in availability and delivery \r\n of healthcare that occurred in 2020 can be seen throughout the ADR and in many metrics \r\n typically tracked in the CKD and ESRD populations.\r\n
\r\n \r\n- \r\n
- \r\n Among patients with CKD, there was a particularly steep reduction in the rate of all-cause \r\n hospitalization in 2020 (14.9%); this single-year decrease was larger than the cumulative \r\n change over the previous 6-year period from 2013 to 2019 (Figure 3.4). Rates of emergency \r\n department encounters were also considerably lower in 2020 (Figure 3.15d).\r\n \r\n
- \r\n Although rates of readmission within 30 days of hospital discharge remained stable in 2020 \r\n among patients with CKD, the rate of death within 30 days of hospital discharge (without \r\n rehospitalization) increased by almost 20% (Figures 3.13, 3.14d). \r\n \r\n
- \r\n Although the overall rate of hospitalization with acute kidney injury (AKI) decreased in \r\n 2020 (likely related to the overall reduction in hospitalization rate; Figure 4.1), AKI \r\n events worsened, as indicated by a 16% increase in the need for dialysis among those with \r\n AKI (Figure 4.2). This increase occurred after a sustained period of decreasing need for \r\n dialysis during hospitalization with AKI.\r\n \r\n
- \r\n Outcomes after AKI requiring dialysis (AKI-D) during a COVID-19 hospitalization in 2020-2021 \r\n were substantially worse than outcomes after AKI-D without COVID-19: almost three-quarters \r\n (74.1%) of those with COVID-19 and AKI-D died during hospitalization or were discharged to \r\n hospice care compared with 35.2% of those without COVID-19 (Figure 4.4c). \r\n \r\n
- \r\n Inflation-adjusted overall Medicare fee-for-service (FFS) spending for older (≥66 years) \r\n beneficiaries with nondialysis-dependent CKD decreased by almost 3% in 2020, or by ~$2.2B \r\n (Figure 6.3). Inpatient spending decreased by 4%, which was a combination of a ~$2.4B \r\n decrease in spending on non-COVID-19 hospitalization plus approximately $1.4B in spending \r\n for COVID-19 hospitalization (Figure 6.4).\r\n \r\n
- \r\n Hydroxychloroquine and chloroquine use among older Medicare Part D beneficiaries with CKD \r\n spiked in March and April 2020 (Figure 7.13), at a time when rates of receipt of many common \r\n drugs used to treat hypertension or CKD transiently declined (Figure 7.10). Rates of \r\n ivermectin use increased dramatically in November and December of 2020 among older Medicare \r\n Part D beneficiaries with CKD (Figure 7.14).\r\n \r\n
- \r\n
- \r\n The percentage of patients with incident ESRD in 2020 starting in-center HD decreased, and \r\n the corresponding percentage starting PD increased (Figure 1.2).\r\n \r\n
- \r\n The percentage of older Medicare beneficiaries with ESRD and diabetes who received preventive \r\n care, including glycated hemoglobin (A1c) testing, lipid testing and eye examination decreased \r\n in 2020 (Figure 3.15). Only about 25.6% of patients received all three of these examinations, \r\n compared with 31.4% in 2019.\r\n \r\n
- \r\n The percentage of patients initiating HD with a catheter increased in 2020 to 71.2%, and the \r\n corresponding percentage initiating with an AVF decreased to 25% overall (including AVFs that \r\n were maturing or were in use, or 14.1% for AVFs used at dialysis initiation; Figure 4.1).\r\n \r\n
- \r\n The number of patients with ESRD newly added to the kidney transplant waitlist in 2020 decreased \r\n by 12% (Figure 7.1). There was a corresponding decrease in the total number and of patients with \r\n ESRD on the waitlist that was particularly pronounced for those listed with active status (Figure \r\n 7.2). The percentage of dialysis patients on the kidney transplant waitlist also declined in 2020 \r\n (Figure 7.3).\r\n \r\n
- \r\n The rate of receipt of living donor kidney transplants among patients on dialysis decreased by \r\n 27.3% in 2020 (Figure 7.10a).\r\n \r\n
- \r\n Adjusted 1-year post-kidney transplant patient and allograft survival decreased in 2020 among \r\n recipients of living and deceased donor kidney transplants (Figures 7.19a, 7.20a).\r\n \r\n
- \r\n The number of children with incident ESRD decreased in 2020, driven primarily by a reduction in \r\n the number who received a preemptive kidney transplant (Figures 8.1, 8.3b).\r\n \r\n
- \r\n The rates of kidney transplantation among children receiving dialysis decreased by 6% in 2020 \r\n (Figure 8.13).\r\n \r\n
- \r\n Total Medicare spending for beneficiaries with ESRD decreased by $2.2B in 2020 (Figure 9.1). \r\n Medicare FFS spending for ESRD beneficiaries as a percentage of total FFS spending decreased to \r\n 6.1% in 2020 after 10 years at 7.1-7.2% (Figure 9.3). The biggest (inflation-adjusted) decrease \r\n in FFS spending for ESRD was for outpatient spending (-$1B), and inpatient spending decreased by \r\n $0.6B (Figure 9.5). \r\n \r\n
- \r\n Hydroxychloroquine and chloroquine use among Medicare Part D beneficiaries with ESRD spiked in \r\n March and April 2020 (Figure 10.13). Rates of ivermectin use increased dramatically in November \r\n and December of 2020 among Medicare Part D beneficiaries with ESRD (Figure 10.14).\r\n \r\n
\r\n Racial, ethnic, and socioeconomic disparities\r\n
\r\n \r\n\r\n In the 2021 ADR, we did not observe disparities in rates of outpatient nephrology visits or \r\n receipt of medications to treat CKD or its complications, including angiotensin converting \r\n enzyme inhibitors or angiotensin receptor blockers, oral potassium or phosphorus binders, or \r\n sodium-glucose cotransporter-2 inhibitors, by race/ethnicity. Rates of nephrology encounters \r\n also differed little by level of neighborhood deprivation. These results suggest that Medicare \r\n coverage, including Part D and the Low Income Subsidy, appeared to provide comparable access to \r\n care for CKD across race/ethnicity groups and across levels of neighborhood deprivation. We \r\n hypothesized that barriers to access to care prior to Medicare eligibility likely contribute to \r\n the higher rates and earlier onset of diabetes and hypertension among Black and Hispanic individuals \r\n as well as to the higher risk of subsequent CKD and ESRD. To address this question, this year’s \r\n ADR includes data on younger Medicaid beneficiaries aged 18 to 64 years, in which we examined access \r\n to medications and nephrology care in these younger patients. We again found little disparity by \r\n race/ethnicity or by neighborhood in receipt of medications or nephrology encounters. However, rates \r\n of nephrology encounters among younger Medicare beneficiaries were less than half those among older \r\n Medicare beneficiaries. Thus, the younger, more heavily Black, Hispanic, and lower socioeconomic \r\n status (SES) Medicaid population appeared to have considerably less access to nephrology care. \r\n Medicaid coverage may provide less access to nephrology care than Medicare coverage, or insurance \r\n coverage may be insufficient to overcome barriers to accessing care experienced by younger patients \r\n with low SES, such as transportation or concerns about loss of work income. Furthermore, limitations \r\n in access to Medicaid (e.g., across U.S. states) likely introduce further disparities that cannot be \r\n examined using medical claims, as uninsured patients almost certainly have more limited access to care. \r\n Further examination of these issues using more detailed data sources will be critical to developing and \r\n implementing strategies to address healthcare disparities.\r\n
\r\nIntroduction
\r\n\r\n The United States Renal Data System 2023 Annual Data Report (ADR) contains updated information about the CKD and ESRD populations in the U.S. through the end of 2021. As such, it offers information about ESRD incidence, prevalence, and outcomes during the second year of the COVID-19 pandemic, in which the more transmissible delta variant became dominant, and during the first year of implementation of the ESRD Treatment Choices (ETC) payment model. \r\n
\r\n\t\t\t\t \r\n\r\n Changes to the ADR format\r\n
\r\n\t\t\t\t \r\n\r\n\tWe use the interactive format that was introduced with the 2020 ADR, but with some enhancements. First, we have added a search function (in the upper left corner at the top of the Table of Contents) that will search the entire ADR rather than only the current chapter. The search tool has the capability of searching prior ADRs back to 2020, but the default view limits search results to the current ADR. To make navigation easier, we have also inserted direct links into the text when it references material from another chapter, allowing the reader to jump straight to the referenced chapter. Finally, we took advantage of the interactive platform’s ability to show data across many patient characteristics in each figure to add additional relevant stratifications to some figures. For example, some outcomes in the Transplant chapter are stratified by whether patients live in rural or urban areas and some in the Home Dialysis chapter are stratified by dialysis facility size. \r\n
\r\n\r\n\t\t\t\t\r\n \t\t New data in this year's ADR\t\t \r\n
\r\n\t\t\t\t \r\n\t\t\t\t\r\n \t\t This year’s ADR contains data from medical claims through 2021 and for some ESRD-related metrics through 2022. In addition to updating data from Medicare, we now present new data for beneficiaries with ESRD covered by Medicare Advantage (MA) about hospitalization and mortality (CKD Volume, Chapter 3 and ESRD Volume, Chapter 5). Given the growing percentage of incident dialysis patients with MA and the first-ever opportunity for prevalent ESRD patients to switch to MA in 2021 (ESRD Volume, Chapter 9), we have been requesting and receiving MA data for the ESRD population for the last several years. However, our method of ascertaining which patients have comorbidities relevant in adjusted models requires a one-year “look back” period. Furthermore, MA data lag FFS claims data by an additional year because of additional required processing time. Thus, it is only this year that data are available to begin to show (very) short-term trends (2019-2020) in the MA population. We continue our use of Medicaid claims data to examine outcomes in patients with CKD. \t \r\n
\r\n\t\t\t\t \r\n\r\n\t\t New in this year’s ADR, we introduce a cohort of patients with CKD obtained from electronic health records of the M Health Fairview system. M Health Fairview is an academic health system in Minnesota that comprises 10 hospitals, 48 primary care clinics, and numerous specialty clinics. The electronic health record database contains data on over 4.5 million patients since 2011. We use data from this cohort in the Transitions of Care in Chronic Kidney Disease chapter to examine treatment of anemia, vascular access placement, and dialysis initiation. \r\n
\r\n\t\t\t\t \r\n\r\n\t\t Although we have presented data from the USRDS Study of Treatment Preferences (USTATE), conducted by a USRDS Special Studies Center, in previous ADRs, this year, we move beyond presentation of survey data to direct presentation of patient narratives. We believe that hearing directly from patients about their experiences of the care we provide can help the nephrology community identify areas of success as well as areas that need improvement in our quest to provide high quality, patient-centered care for individuals with kidney disease. This year, we highlight the experiences of patients receiving in-center hemodialysis, but we envision that this approach can be applied to patients performing dialysis at home, navigating the kidney transplant process, or living with a functioning kidney transplant in future ADRs.\r\n
\r\n\t\t\t\t \r\n\t\t\t\t\r\n\t\t Key findings in the 2023 ADR\t\t \r\n\t\t\t\t
\r\n\t\t\t\t \r\n\t\t\t\t\r\n\t\t COVID-19\t \r\n\t\t\t\t
\r\n\t\t\t\t \r\n\t\t \r\n\t\t The epidemiologic implications of the COVID-19 pandemic continue to be a major theme of the ADR. ADRs published prior to 2022 reported gradual but consistent improvements in hospitalization and mortality over the preceding decade for people with CKD and ESRD. However, 2020 proved to be a watershed year that witnessed a reversal of many long-term improvements for patients with CKD and ESRD, as reported in the 2022 ADR. The 2023 ADR reports on 2021 events that occurred as the pandemic continued to unfold. The most alarming development was continued high mortality rates. Although adjusted mortality decreased among FFS beneficiaries with CKD in 2021 (CKD Volume, Figure 3.1a), it did not return to pre-pandemic levels. Worse, mortality did not improve among Medicaid enrollees with CKD (CKD Volume, Figure 3.1b), who are much younger than Medicare beneficiaries. Graver still, the mortality rate was higher in 2021 than in 2020 among patients with ESRD (ESRD Volume, Figure 6.1). The HD population was hit particularly hard, to the extent that the prevalent HD population decreased in 2021 for the second year in a row (ESRD Volume, Figure 1.6). Overall and COVID-19 related mortality also increased substantially in 2021 for kidney transplant recipients. \r\n
\r\n\t\t\t\t \r\n\r\n\t\t This year’s ADR also examined treatment of COVID-19 and outcomes following COVID-19 infection. Despite being more likely to be diagnosed with COVID-19 and substantially more likely to be hospitalized and to die after a COVID-19 diagnosis, patients with CKD and ESRD were less likely to receive remdesivir than those without CKD (CKD Volume, Figure 7.17; ESRD Volume, Figure 10.16). Patients with kidney disease were also less likely to receive monoclonal antibody therapy than individuals without (CKD Volume, Figure 7.18; ESRD Volume, Figure 10.17). \r\n
\r\n\r\n\r\nIn the first 4 months of availability of a new ICD-10-CM code for long COVID (October to December 2021), the incidence of long COVID diagnosis was twice as high among Medicare beneficiaries with CKD as among those without; the incidence was two-and-a-half times as high among beneficiaries treated with dialysis and over three times as high among kidney transplant recipients. It is possible that the short period during which patients could be diagnosed with long COVID in 2021 could have led to higher rates among patients receiving more frequent medical care –warranting close monitoring going forward. Nevertheless, it is extremely concerning that patients with kidney disease were simultaneously more vulnerable to COVID-19 diagnosis, hospitalization, and mortality and also less likely to receive effective treatments. Undertreatment of COVID-19 may also have contributed to initially high rates of long COVID diagnoses as well. Although there may have been some concern in 2021 about the safety of remdesivir among patients with CKD, the FDA recently approved the use of remdesivir for patients with severe kidney impairment, including those receiving dialysis (Gilead, 2023). The USRDS and the nephrology community must continue to monitor treatment for COVID-19 among patients with kidney disease and to advocate for appropriate and adequate access for our patients if we are to combat the high rates of mortality and possibly high rates of long COVID among survivors.\r\n
\r\n\t\t\t\t \r\n\t\t\t\t\r\n\t\t CKD population\t \r\n\t\t\t\t
\t\r\n\t\t\t\t \r\n\r\n\t\t Aside from the ongoing impact of the COVID-19 pandemic, there were several new findings in the CKD population that deserve emphasis. \r\n
\r\n\t\t\t\t \r\n\r\n\t\t\tAnemia management\t \r\n\t\t\t\t
\r\n\t\t\t\t \r\n\r\n\t\t We built on the observation in the 2022 ADR that less than 10% of Medicare FFS beneficiaries with stage 4 or 5 CKD (based on claims data) received erythropoiesis stimulating agents (ESAs) and only 5% received intravenous (IV) iron to delve further into anemia treatment. Examining ESA use by stage of CKD revealed that although ESA use remained <10% in 2021 among beneficiaries with stage 4 CKD, it was slightly higher (14.4%) among those with stage 5 CKD. IV iron use was also higher among those with stage 5 than among those with stage 4 CKD. Remarkably, blood transfusions were more common than ESA therapy among patients with stage 4 CKD in 2021; for individuals with stage 5 CKD, the rate of blood transfusion was similar to that of ESA use. These findings suggest that anemia management appears to be suboptimal, but without laboratory results for the Medicare population, it is not possible to derive a full picture of whether indicated treatments are being delivered and whether transfusions could be avoided.\r\n
\t\r\n\t\t\t\t \r\n\r\n\t\t Inclusion of data from the M Health Fairview system this year allowed us to examine receipt of treatment for anemia and iron deficiency based on relevant laboratory data. Some key take-aways were:\r\n
\r\n\r\n- \r\n
- \r\nAbout 1 in 5 patients with stage 4 CKD and almost 2 in 5 with stage 5 CKD had Hb <10 g/dL (CKD Volume, Figure 8.3a). Just over half of patients with stage 4 CKD and 43% of those with stage 5 CKD had iron deficiency, as indicated by TSAT ≤20% or ferritin ≤100 ng/mL. \r\n \r\n
- \r\nA minority of patients received relevant treatment. Specifically, less than 20% of patients with stages 4-5 CKD who had Hb <9 g/dL and less than 15% of those with Hb 9 to <10 g/dL received erythropoiesis stimulating agents (ESAs) (CKD Volume, Figure 8.3b). Just over 10% of those with iron deficiency received IV iron, and less than half received any iron at all. \r\n \r\n
- \r\nThese results are important because over 15% of individuals with Hb <9 g/dL received a blood transfusion, whereas only 1.2% of those with Hb ≥10 g/dL did (CKD Volume, Figure 8.4b). \r\n \r\n
\r\nThese results indicate that patients with anemia are being undertreated and that undertreatment with medications may be contributing to use of RBC transfusion. This is concerning, particularly for younger patients, because receipt of even a single RBC transfusion can lead to sensitization to HLA antigens (Leffell et al., 2014). Sensitization, in turn, can reduce access to kidney transplant, particularly to living donor transplant, as patients are more likely to react to a limited pool of available donors. Sensitized patients then wait longer on dialysis for a deceased donor transplant, during which time they are exposed to a higher risk of mortality than after transplant. Sensitization can also lead to exposure to higher levels of immunosuppression because many transplant center protocols call for more aggressive induction therapy among recipients with high panel reactive antibody (PRA) levels, thereby increasing risk of infections and malignancies.\r\n
\r\n\t\t\t\t \r\n\r\n\t\t\tRacial differences in outpatient dialysis for AKI\t \r\n\t\t\t\t
\r\n\t\t\t\t \r\n\r\n\t\t The number of Medicare FFS beneficiaries who initiated outpatient hemodialysis for AKI has grown since 2017 to reach almost 12,000 individuals each year over the last three years, constituting almost 10% of the total new in-center HD starts in 2021. For the first time this year, we examined the demographic characteristics and limited comorbidity (CKD and heart failure) of these beneficiaries (CKD Volume, Figure 4.9). Not surprisingly, almost all had a prior diagnosis of CKD. However, the distribution of race/ethnicity was very different among these beneficiaries compared with those initiating in-center HD for ESRD. A much higher proportion of beneficiaries initiating dialysis for AKI was White (~74%) than the proportion among FFS beneficiaries initiating HD for ESRD in 2021 (~58%). Correspondingly, a smaller percentage was Black (~16%) compared with the incident dialysis population (~24%). This is surprising given the higher rates of hospitalization with AKI and AKI-D among Black beneficiaries. In contrast, Black beneficiaries were more likely to receive dialysis for ESRD within one week of discharge from a hospitalization with AKI than their White counterparts (CKD Volume, Figure 4.3c). The reasons for this apparent difference in perceived likelihood of recovery of kidney function for Black and White beneficiaries with dialysis-requiring AKI – and any associated differences in outcomes – deserve exploration. \r\n
\t\r\n\t\t\t\t \r\n\t\t\t\t\r\n\t\t ESRD population\t \r\n\t\t\t\t
\t\r\n\t\t\t\t\r\n\r\nSeveral new developments in the ESRD population also deserve emphasis. Some of these developments may be directly or indirectly related to the COVID-19 pandemic, whereas others are related to changes in practices, policies, or payment models. \r\n\r\n
\t\t\t\t \r\n\t\t\t\t\r\n\t\t Increase in post-hospitalization mortality\r\n\t\t\t\t
\t\r\n\t\t\t\t \r\n\r\n\t\t Mortality following hospitalization (that is, after a live discharge) increased in 2020 relative to 2019, and then worsened further in 2021 among Medicare beneficiaries with ESRD (ESRD Volume, Figures 5.9 and 5.11a). Furthermore, the percentage of patients with ESRD who died without rehospitalization increased from 7.5% in 2019 to 9.4% in 2021 – a prodigious relative increase of over 25% (ESRD Volume, Figure 5.9). That over 1 in 11 live discharges among patients with ESRD in 2021 resulted in death (without rehospitalization) in the subsequent 30 days raises several possible explanations: that hospitalization avoidance (in this case following an initial hospitalization) occurred; that patients were discharged prematurely from their index hospitalization; that COVID-19 hospitalization conferred a higher risk of mortality that extended beyond the period of hospitalization (Xie et al., 2022); or that patients had difficulty receiving post-discharge outpatient care. A combination of these is highly plausible.\r\n
\t\t\r\n\r\n\r\n\t\t Vascular access among incident hemodialysis patients\r\n\t\t\t\t
\t\r\n\t\t\t\t \r\n\r\n\t\t In 2021, over 85% of individuals who initiated HD did so with a catheter. Further, almost three-quarters of individuals had no permanent access in place when initiating HD, a striking increase from about 65% in 2018. This dramatic shift in clinical practice over a very short time bears further scrutiny because it is unclear whether it was driven by pandemic-related limitations in capacity to perform vascular access procedures or whether it may have been a response to new clinical practice guidelines suggesting that some patients may be better served with an arteriovenous graft or catheter than an arteriovenous fistula (AVF) (Lok et al., 2020); a combination of these two forces is possible. Continued monitoring of trends in vascular access use and of outcomes among patients with different types of vascular access will be needed to clarify the reasons for the shift away from AVF and towards catheters and the effects of this shift on the HD population.\r\n
\t\t\t\t\t \t\t\t \r\n\r\n\t\t\t\t\r\n\t\t Examination of Medicaid expansion and ESRD incidence\r\n\t\t\t\t
\r\n\r\n\r\n\t\t Medicaid expansion under the Patient Protection and Affordable Care Act provided a natural experiment of sorts. Numerous states expanded Medicaid access to all individuals with incomes up to 138% of the federal poverty level beginning in 2014, but many others delayed implementation or never implemented this expansion. Thus, in some states, all low-income individuals have had access to Medicaid since 2014, while in others, many low-income individuals remain uninsured. Given that outcome data are now available for several years, we examined whether there were differences in ESRD incidence among states that expanded Medicaid access in 2014 and those that did not. We reasoned that access to care in expansion states might lead to lower rates of ESRD onset (or, more likely, less of an increase) than in non-expansion states, particularly for individuals under 65 years of age who are (mostly) not covered by Medicare.\r\n
\r\n \t\t\r\n\t\t We found that ESRD incidence was higher among younger individuals (aged <65 years) in non-expansion states even before 2014, which could be related to the location of several of these states in the Deep South, which has a larger Black population and higher poverty rates than other parts of the country. In addition, there may have been more stringent Medicaid eligibility requirements in these states even before other states expanded eligibility. After Medicaid expansion, ESRD incidence increased in non-expansion and expansion states but increased more in non-expansion states, widening the gap in incidence by about 10 cases per million population. Interestingly, however, this divergence in ESRD incidence after 2014 was driven almost entirely by changes among White individuals. Whereas ESRD incidence among White individuals had been increasing in both non-expansion and expansion states from 2011 to 2014, it flattened in expansion states and continued to rise through 2018 in non-expansion states. Both expansion and non-expansion states saw steep decreases in ESRD incidence in 2020, and it remains to be determined whether these were the result of delay of onset of ESRD during the COVID-19 pandemic or higher death rates among individuals with advanced kidney disease.\r\n
\t\r\n\t\t\t\t \r\n\t\t\t\t\r\n\t\t Effects of payment models\r\n\t\t\t\t
\t\t\t\t \r\n\t\t\t\t \r\n\r\n\t\t Data presented in the first two chapters of the ESRD Volume of the ADR demonstrate that expansion of home dialysis occurred during the entire period from 2011 to 2021 – even during the initial two years of the COVID-19 pandemic. However, it is still important to examine whether current payment models, such as the ESRD Treatment Choices (ETC) model and the Kidney Care Choices models are succeeding in increasing use of home dialysis and are increasing access to kidney transplant. This year’s ADR presents evidence that home dialysis use among incident dialysis patients increased in early 2021 in parts of the country participating in ETC (ESRD Volume, Figure 2.2). Whereas rates had been lower in ETC markets prior to 2021, they were similar in ETC and non-ETC markets in 2021, indicating a small increase ETC relative to non-ETC markets. A more detailed investigation of trends in home dialysis utilization among incident patients (including both Medicare FFS beneficiaries and non-FFS beneficiaries) over the first 18 months of the implementation of ETC found that the overall growth in home dialysis among patients new to dialysis (that is, incident patients with ESRD) nearly doubled compared with the period prior to ETC implementation (Johansen et al., 2023). Furthermore, the increase was not confined to ETC markets or even to Medicare FFS beneficiaries. However, a recent evaluation commissioned by CMS reported no significant increase in the uptake of home dialysis among prevalent Medicare FFS beneficiaries (Negruse et al., 2023). Taken together, published evidence suggests that ETC may eventually prove more effective at increasing uptake in home-based dialysis modalities in incident, rather than prevalent, ESRD patients. Unfortunately, however, the growth in use of home dialysis among incident patients has not resulted in an appreciable increase in the prevalent home dialysis population and is clearly insufficient to meet ambitious targets established by the Executive Order. Unfortunately, however, the growth in use of home dialysis among incident patients has not resulted in an appreciable increase in the prevalent home dialysis population and is clearly insufficient to meet ambitious targets established by the Executive Order. \r\n
\t\t\t\t \r\n\t\t\r\n\t\t The effect of ETC on home dialysis growth (and growth in kidney transplant) will be a focus of ongoing USRDS surveillance. Future reports should also evaluate differences in use of home dialysis in prevalent dialysis populations and differences in rates of kidney transplant among participants in various payment models. However, it is important to recognize that it may prove difficult to separate effects of new payment models from effects of the COVID-19 pandemic, given that they coincided. COVID-19 mortality was higher among patients receiving in-center HD than among patients performing dialysis at home in 2020 and 2021 (Weinhandl et al., 2022), resulting in a shrinkage in the prevalent in-center HD population in both years (ESRD Volume, Figure 1.6). A larger reduction in the in-center HD population than in the home dialysis population would be expected to increase the percentage of prevalent dialysis patients treated with home dialysis even if payment models have had no effect. Thus, it will be important to focus on differences between model participants and non-participants rather than solely on overall changes in dialysis modality during this tumultuous period. \r\n
\t\r\n\t\t\t\t\r\n\t\t Implementation of the 21st Century Cures Act\r\n\t\t\t\t
\t\t\t\t \r\n\t\t\t\t \r\n\r\n\t\t Prior to 2021, Medicare FFS beneficiaries with CKD were precluded from switching to Medicare Advantage (MA) plans, but those with pre-existing MA coverage were allowed to continue it. As a result, the number of patients with ESRD with MA coverage was growing only slowly. However, with the implementation of the 21st Century Cures Act, all Medicare beneficiaries with ESRD became eligible to enroll in MA plans beginning in the 2021 open enrollment period. As a result, MA enrollment in the prevalent ESRD population grew by a remarkable one-third in 2021 in relative terms (and from 18.3% in 2020 to 24.5% in absolute terms; ESRD Volume, Figure 9.4b). As a result, MA spending for ESRD increased by a prodigious 46.4% in a single year (ESRD Volume, Figure 9.1), and Medicare FFS spending decreased correspondingly. Future ADRs should track the influence of this shift on Medicare spending for patients with ESRD and should also compare outcomes among those insured under FFS and MA programs.\r\n
\t\t\t\t\t \r\n\t\t\t\t \r\n\t\t\t\t\r\n\t\t Racial and ethnic disparities in access to home dialysis and living donor kidney transplant\r\n\t\t\t\t
\t\r\n\r\n\t\t Large racial/ethnic and socioeconomic disparities in access to home dialysis were evident (Figure 14.12). Black and Hispanic patients were much less likely to start dialysis at home as White patients; this was true across all levels of neighborhood deprivation. However, outcomes did not mirror these differences in access. Conversion to in-center HD within one year varied little by race/ethnicity or neighborhood deprivation, and mortality was higher among White patients. Thus, although prior studies suggested that Black patients were more likely to convert to in-center HD than White patients (Mehrotra et al, 2014), in the modern era, Black and Hispanic patients were more likely to remain on home dialysis after one year than White patients regardless of neighborhood deprivation. \r\n
\r\n\t\r\n\r\n\t\t Considering access to preemptive kidney transplant, Black race, Hispanic ethnicity, and higher neighborhood deprivation were all associated with lower rates of preemptive waitlisting for a kidney transplant and of receiving a kidney transplant from a living donor in 2021. These disparities are important because outcomes are superior for preemptive and living donor kidney transplants compared with deceased donor kidney transplants after ESRD onset. In addition, these disparities lead to longer waiting times for a kidney transplant for disadvantaged groups. There has been some reduction in disparities in access to deceased donor kidney transplants among patients with ESRD in recent years. Differences in the rate of deceased donor transplant by race and ethnicity were small in 2021 after considering neighborhood deprivation. However, patients living in more deprived neighborhoods had lower rates of receipt of deceased donor kidney transplants. Thus, important disparities in access to kidney transplant remain for patients with ESRD, compounding the large disparities in incidence of ESRD. \r\n
\t\r\n\r\n\r\n\t\t Racial and ethnic disparities among children with ESRD\r\n\t\t\t\t
\t\r\n\r\nRacial disparities in children deserve particular attention. Noticeable disparities are present despite a very different distribution of causes of ESRD than among adults and a shorter time horizon to develop ESRD (prior to age 18). Incident ESRD was 42% higher among Black children, at 14.8 cases per million population (pmp), than among White children, for whom the rate of incident ESRD was 10.4 pmp (ESRD Volume, Figure 8.2). Although some of this difference may be due to more glomerulonephritis (ESRD Volume, Table 8.1) among Black children and a worse prognosis among patients with GN than among those with other causes of CKD, disparities in access to care may also contribute. The disparity in ESRD incidence is compounded by a large disparity in access to preemptive kidney transplant. Rates of preemptive kidney transplant among Black children (12.0%) were less than half those of White children (27.9%). Examining and addressing these disparities is critical as the combination of more ESRD and less access to transplant as initial kidney replacement therapy adds an enormous burden of morbidity and mortality to Black children with kidney disease.\r\n
\r\n\r\n \t\t\r\n\t\t Patient experience chapter\r\n\t\t\t\t
\t\t\t\t \r\n\t\t\t\t \r\n\r\n\t\t In this year’s Patient Experience chapter, we present interviews with patients about their experiences undergoing in-center hemodialysis. The patients had started dialysis under varied circumstances and with differing levels of preparation and involvement in decision-making. Most experienced dialysis as a major disruption to the lives they had been living and the futures they had hoped for. They saw dialysis as something they had to do if they wanted to continue living, and this understanding of dialysis as a lifeline in the face of existential threat was instrumental in helping them tolerate a time-consuming and sometimes uncomfortable and painful treatment that had seriously disrupted their lives. Our interviews also shed light on patients’ interactions with nephrologists and dialysis facility staff members as well as with other patients receiving dialysis care.\r\n
\t\r\n\r\n\r\n\t\t Clinicians and staff working in dialysis facilities should recognize that many of the patients under their care have experienced substantial trauma and loss, see dialysis as a lifeline in the face of existential threat, have a limited sense of community with other patients dialyzing alongside them, and often feel vulnerable and powerless in their relationships with staff and clinicians. Collectively, these interviews highlight the critical importance of care that is “careful and kind” (Montori, 2020) and person-centered (O'Hare, 2018) for people with kidney failure, which includes taking time to get to know patients as people, building relationships and establishing trust, and caring for patients in ways that uphold their personhood, support their goals, and improve their experiences of illness and care. The insights shared by the patients we interviewed offer a powerful illustration of why patients and families must have a voice in shaping efforts to improve dialysis care. \r\n
\t\r\n\r\n \t\t\r\n\t\t Conclusion\t \r\n\t\t\t\t
\r\n\r\n\t\t\t\t \r\n\r\n\t\t The 2023 ADR presents critical information about the state of the CKD and ESRD populations after the first two years of the COVID-19 pandemic and the initial years of implementation of new payment models for advanced CKD and ESRD. In the coming years, we can expect to continue to track these developments as well as to further examine the impact of new treatments for CKD and ESRD. \r\n
\t\r\n\r\n\t\t\r\n\t\t\r\n\t\t References\r\n\t\t\t\t
\r\n- \r\n\t\t\t\t\t \r\n
- \t\t\t\r\n Gilead. (2023, July 14, 2023). FDA approves Veklury (remdesivir) for COVID-19 treatment in \r\n\t\t patients with severe renal impairment, including those on dialysis. \r\n\t\t https://www.gilead.com/news-and-press/press-room/press-releases/2023/7/fda-approves-veklury-remdesivir-for-covid19-treatment-in-patients-with-severe-renal-impairment-including-those-on-dialysis \r\n\t\t\t\t\t\t \r\n\r\n
- \t\t\t\r\n Johansen, K. L., Li, S., Liu, J., Weinhandl, E. D., Gilbertson, D. T., Kou, I., Knapp, C., & Wetmore, J. B. (2023, Feb 1). Association of the End-Stage Renal Disease Treatment Choices Payment Model With Home Dialysis Use at Kidney Failure Onset From 2016 to 2022. JAMA Netw Open, 6(2), e230806. https://doi.org/10.1001/jamanetworkopen.2023.0806\r\n\t\t\t\t\t\t \r\n\t\t\t\t\t\t\r\n
- \r\n Leffell, M. S., Kim, D., Vega, R. M., Zachary, A. A., Petersen, J., Hart, J. M., Rossert, J., \r\n\t\t & Bradbury, B. D. (2014, Mar 15). Red blood cell transfusions and the risk of allosensitization \r\n\t\t in patients awaiting primary kidney transplantation. Transplantation, 97(5), 525-533. \r\n\t\t https://doi.org/10.1097/01.tp.0000437435.19980.8f\r\n \r\n\r\n
- \t\t\t\t\t\t\r\n Lok, C. E., Huber, T. S., Lee, T., Shenoy, S., Yevzlin, A. S., Abreo, K., Allon, M., Asif, A., \r\n\t\t Astor, B. C., Glickman, M. H., Graham, J., Moist, L. M., Rajan, D. K., Roberts, C., Vachharajani, T. J., & Valentini, R. P. (2020, Apr). KDOQI Clinical Practice Guideline for Vascular Access: 2019 Update. Am J Kidney Dis, 75(4 Suppl 2), S1-s164. https://doi.org/10.1053/j.ajkd.2019.12.001\r\n \r\n\r\n
- \t\t\t\t\t\t\r\n Montori, V. M. (2020). Why we revolt : a patient revolution for careful and kind care (2nd edition. ed.). Mayo Clinic Press. \r\n \r\n\r\n
- \r\nMehrotra, R., Soohoo, M., Rivara, M. B., Himmelfarb, J., Cheung, A. K., Arah, O. A., Nissenson, A. R., Ravel, V., Streja, E., Kuttykrishnan, S., Katz, R., Molnar, M. Z., Kalantar-Zadeh, K. (2016). Racial and Ethnic Disparities in Use of and Outcomes with Home Dialysis in the United States. J Am Soc Nephrol, 27(7) 2123-2134. https://doi.org/10.1681/ASN.2015050472\r\n \r\n\r\n
- \t\t\t\t\t\t\r\n Negruse, B., Wiens, J., Ullman, D., Turenne, M., Mukhopadhyay, P., Young, E., Pozniak, A., Gotat, R., Wang, D., Wiseman, J., Tian, S., Milkovich, K., Cahlerus, C., & Hirth, R. (2023). End-Stage Renal Disease (ESRD) Treatment Choices (ETC) Model. First Annual Evaluation Report. C. f. M. M. Services. https://www.cms.gov/priorities/innovation/data-and-reports/2023/etc-1st-eval-report-app\r\n \r\n\r\n
- \t\t\t\t\t\t\r\n O'Hare, A. M. (2018, May). Patient-Centered Care in Renal Medicine: Five Strategies to Meet the Challenge. Am J Kidney Dis, 71(5), 732-736. https://doi.org/10.1053/j.ajkd.2017.11.022 \r\n \r\n\r\n
- \t\t\t\t\t\t\r\n Weinhandl, E. D., Liu, J., Gilbertson, D. T., Wetmore, J. B., & Johansen, K. L. (2022, Oct). Associations of COVID-19 Outcomes with Dialysis Modalities and Settings. Clin J Am Soc Nephrol, 17(10), 1526-1534. https://doi.org/10.2215/cjn.03400322\r\n \r\n\r\n
- \t\t\t\t\t\t\r\n Xie, Y., Xu, E., Bowe, B., & Al-Aly, Z. (2022, Mar). Long-term cardiovascular outcomes of COVID-19. Nat Med, 28(3), 583-590. https://doi.org/10.1038/s41591-022-01689-3\r\n \r\n\t\t\t\t\t\t\r\n
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