25:["$","title",null,{"children":"Redox: Value Based Care Strategy | Nolan Johnson | Observable"}] 49:T400,md`Undoubtedly, healthcare costs have ballooned in an unprecedented way, outpacing education (the other oft-cited example of rampant cost increases). All while many other goods and services have decreased in cost.

___ There are a total of **${fastFacts.total_number_of_all_us_hospitals.toLocaleString()} hospitals** in the US and an astronomical **${fastFacts.total_expenses_for_all_us_hospitals.toLocaleString( undefined, numberFormats.usd_0 )} in US hospital expenses** (approx. 1 trillion), according to the [American Hospital Association](https://www.aha.org/statistics/fast-facts-us-hospitals). But this staggering figure represents less than a third of Total National Health Expenditure, which [CMS estimates](https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/highlights.pdf) around **$3.5 trillion** or $10,739 per person as of 2017. `4a:T531,{ const spend = vl .markArea({ point: true }) .data(expenditureData.slice(0, -1)) .encode( vl.x().fieldO('year'), vl .y() .fieldQ('total_national_health_expenditures') .title(null), vl.tooltip([vl.y().fieldQ('total_national_health_expenditures')]) ) .width(400) .title('Total National Health Expenditures (millions USD)'); const spendArrow = spend .markPoint({ color: 'black', shape: 'arrow', yOffset: -10, angle: 180 }) .transform(vl.filter(`datum.year === ${startYear}`)); const popLine = vl .markArea({ opacity: 0.7, fill: 'rgb(200, 100, 70)' }) .data(usPopulation.filter(d => d.year <= 2017)) .encode( vl.x().fieldO('year'), vl .y() .fieldQ('population') .title(null), vl.tooltip([vl.y().fieldQ('population')]) ) .width(400) .title('US Population'); const popArrow = popLine .markPoint({ color: 'black', shape: 'arrow', yOffset: -10, angle: 180 }) .transform(vl.filter(`datum.year === ${startYear}`)); return ( vl .hconcat(vl.layer(spend, spendArrow), vl.layer(popLine, popArrow)) // .resolve({ axis: { y: 'independent' }, scale: { y: 'independent' } }) .render() ); }4b:T49a,md`___ Health expenditure is not a single monolithic $3.5 trillion dollar price tag though. Instead it's a made up of many different sectors and modes of care. The [Health Care Cost Institute](https://healthcostinstitute.org) aggregates claims data from four national insurance companies: Aetna, Humana, Kaiser Permanente, and UnitedHealthcare to provide estimates of cost across different categories. HCCI provides this data at various levels of granularity. Shown below are the price, utilization, and spending (price * utilization) across the 4 major categories (as well as a combined \`Total\` category). The big takeaway, shown in the chart on the right below, is that **spend is increasing across all categories**. Spend is a factor of both utilization rates and prices. Looking at that decomposition on the left, **utilization rates (dashed lines) are staying constant** or even declining slightly, and what's driving higher spend is almost 100% an **increase in the price/cost of health care**. _They also provide an [interactive tool](https://healthcostinstitute.org/research/hccur/2017-health-care-cost-and-utilization-report) of this data that's worth exploring!_`4c:T76e,{ const select1 = vl .selectSingle() .on('mouseover') .encodings('color'); const select2 = vl .selectSingle() .on('mouseover') .encodings('color'); const base = vl .markLine({ point: true, strokeWidth: 3 }) .data( hcciCostUtilization.filter( d => (d.hcci_subcategory.includes('All ') && d.outpatient_service_type === "" && d.rx_brand_generic === "") || d.hcci_category === 'Total' ) ) .encode( vl.x().fieldO('yr'), vl .color() .if(select1 || select2, vl.fieldN('hcci_category')) .value('lightgrey') ); const baseText = field => base.markText({ dy: -10, dx: -5 }).encode( vl.y().fieldQ(`${field}`), vl.text({ format: '.2f' }).fieldQ(`${field}`), vl .color() .if(select1 || select2, vl.fieldN('hcci_category')) .value(null) ); const baseLabel2017 = field => baseText(field).transform(vl.filter('+datum.yr === 2017')); return vl .hconcat( vl .layer( base .select(select1) .markLine({ point: true, strokeDash: [10, 2], strokeWidth: 3 }) .encode(vl.y().fieldQ('adj_util_cmltv')), base.select(select2).encode(vl.y().fieldQ('adj_price_cmltv')), // baseText('adj_util_cmltv'), // baseText('adj_price_cmltv'), baseLabel2017('adj_util_cmltv'), baseLabel2017('adj_price_cmltv') ) .width(300) .height(500), vl .layer( base.select(select1).encode(vl.y().fieldQ('spend_cmltv')), baseLabel2017('spend_cmltv') ) .width(300) .height(500) ) .title( "Cumulative Change in Price (left, solid), Utilization (left, dashed), and Spending (right) of Care by Category, 2013-2017" ) .render(); }4d:Ta71,{ //https://data.medicare.gov/Hospital-Compare/Hospital-Value-Based-Purchasing-HVBP-Total-Perform/ypbt-wvdk const brush = vl .selectInterval() .encodings('x') .resolve('intersect'); const base = vl .markBar() .data(hvbpTotalPerformance) .encode( vl .y() .count() .title('Count of Hospitals') ) .width(width / 4 - 70) .height(200); const x = field => vl .x() .fieldQ(field) .bin({ maxbins: 20 }); return vl .vconcat( // TOP ROW - OVERALL vl .layer( base .select(brush) .encode( x('total_performance_score').title('Overall'), vl.color().value('none') ) .width(width - 100), base.transform(vl.filter(brush)).encode(x('total_performance_score')) ) .resolve({ scale: { y: 'independent' } }) .title('Total Performance Score\n'), // SECOND ROW vl.hconcat( // Clinical Care vl.layer( base .select(brush) .encode( x('weighted_normalized_clinical_care_domain_score').title( 'Clinical Care' ), vl.color().value('lightgrey') ), base .transform(vl.filter(brush)) .encode(x('weighted_normalized_clinical_care_domain_score')) ), // Engagement vl.layer( base .select(brush) .encode( x('weighted_person_and_community_engagement_domain_score').title( 'Engagement' ), vl.color().value('lightgrey') ), base .transform(vl.filter(brush)) .encode(x('weighted_person_and_community_engagement_domain_score')) ), // Safety vl.layer( base .select(brush) .encode( x('weighted_safety_domain_score').title('Safety'), vl.color().value('lightgrey') ), base .transform(vl.filter(brush)) .encode(x('weighted_safety_domain_score')) ), // Efficiency vl.layer( base .select(brush) .encode( x('weighted_efficiency_and_cost_reduction_domain_score').title( 'Efficiency' ), vl.color().value('lightgrey') ), base .transform(vl.filter(brush)) .encode(x('weighted_efficiency_and_cost_reduction_domain_score')) ) ) ) .render(); }4e:T428,// https://www.aha.org/statistics/fast-facts-us-hospitals fastFacts = d3 .tsvParse( `key\tfact Total Number of All U.S. Hospitals 6210 Number of U.S. Community Hospitals 5262 Number of Nongovernment Not-for-Profit Community Hospitals 2968 Number of Investor-Owned (For-Profit) Community Hospitals 1322 Number of State and Local Government Community Hospitals 972 Number of Federal Government Hospitals 208 Number of Nonfederal Psychiatric Hospitals 620 Other Hospitals 120 Total Staffed Beds in All U.S. Hospitals 931203 Staffed Beds in Community Hospitals 798921 Total Admissions in All U.S. Hospitals 36510207 Admissions in Community Hospitals 34305620 Total Expenses for All U.S. Hospitals 1060933249000 Expenses for Community Hospitals 966204239000 Number of Rural Community Hospitals 1875 Number of Urban Community Hospitals 3387 Number of Community Hospitals in a System 3494 Number of Community Hospitals in a Network 1749`, d => ({ key: fixFieldName(d.key), fact: +d.fact }) ) .reduce((prev, curr) => ({ ...prev, [curr.key]: curr.fact }), {})4f:T41c,// source: https://fred.stlouisfed.org/series/POPTOTUSA647NWDB usPopulation = d3.tsvParse( `year population 1960 180671000 1961 183691000 1962 186538000 1963 189242000 1964 191889000 1965 194303000 1966 196560000 1967 198712000 1968 200706000 1969 202677000 1970 205052000 1971 207661000 1972 209896000 1973 211909000 1974 213854000 1975 215973000 1976 218035000 1977 220239000 1978 222585000 1979 225055000 1980 227225000 1981 229466000 1982 231664000 1983 233792000 1984 235825000 1985 237924000 1986 240133000 1987 242289000 1988 244499000 1989 246819000 1990 249623000 1991 252981000 1992 256514000 1993 259919000 1994 263126000 1995 266278000 1996 269394000 1997 272657000 1998 275854000 1999 279040000 2000 282162411 2001 284968955 2002 287625193 2003 290107933 2004 292805298 2005 295516599 2006 298379912 2007 301231207 2008 304093966 2009 306771529 2010 309326085 2011 311580009 2012 313874218 2013 316057727 2014 318386421 2015 320742673 2016 323071342 2017 325147121 2018 327167434`, d => ({ year: +d.year, population: +d.population }) )50:[] 29:{"id":"2e978b86141eb1ae","slug":null,"title":"Redox: Value Based Care Strategy","thumbnail":"bb47fe4f1a6d26e10066050848c8ebe17031567a8f658f3ab49c8d97aefe7021","access_level":"public","create_time":"$D2019-09-09T15:30:56.167Z","update_time":"$D2019-09-12T17:49:53.887Z","view_time":null,"first_public_time":"$D2025-09-10T23:46:06.538Z","has_unpublished_edits":null,"fork":false,"stars":0,"starred":false,"owner":{"type":"team","id":"b4d4c6f199c86820","login":"nolanbjohnson","name":"Nolan Johnson","avatar_url":"https://avatars-next.observableusercontent.com/57cd1ae90cfb935890f756de647048aeadeec3cf8dfd56576b3dbd94fafb7906","tier":"starter_2024","bio":"","followed_by_you":false,"follows_you":false},"version":1545,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"b8ce3f003f06f805","login":"nolanbjohnson","name":"Nolan 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Strategy`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1020,"value":"md`___\n### Introduction`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":563,"value":"$49","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1030,"value":"md`**Growth in Spend vs. US Population**`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":335,"value":"$4a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":932,"value":"{\n const spendForYear = year =>\n expenditureData.filter(d => d.year === year)[0]\n .total_national_health_expenditures;\n\n const popForYear = year =>\n usPopulation.filter(d => d.year === year)[0].population;\n\n const growth = func => func(2017) / func(startYear) - 1;\n const cagr = func =>\n Math.pow(func(2017) / func(startYear), 1 / (2017 - startYear)) - 1;\n\n return md`Between ${startYear} and 2017, health expenditure growth outpaced US population growth by a **factor of ${(\n cagr(spendForYear) / cagr(popForYear)\n ).toLocaleString(\n undefined,\n numberFormats.number_1\n )}** on an annualized basis (spend increased by ${cagr(\n spendForYear\n ).toLocaleString(undefined, numberFormats.percent_1)} on average vs. ${cagr(\n popForYear\n ).toLocaleString(\n undefined,\n numberFormats.percent_2\n )} for the US population over those ${2017 - startYear} years).`;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":941,"value":"viewof startYear = slider({\n min: 1960,\n max: 2015,\n step: 1,\n value: 1960,\n description: md`Adjust the start year to see how that's changed over time`\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":866,"value":"$4b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":439,"value":"$4c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1078,"value":"md`___\n### So where does the cost increase come from? \nThe likely answer: **wasted spending**`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1063,"value":"md`The [Institute of Medicine claimed](http://www.nationalacademies.org/hmd/Reports/2012/Best-Care-at-Lower-Cost-The-Path-to-Continuously-Learning-Health-Care-in-America/Press-Release.aspx) that, in 2009, 30% of health spending...was waste (!)...unnecessary services, excessive administrative costs, fraud, and other problems.`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1504,"value":"md`That 30% of overall wasted spending is spread across both public and private providers/payers.\n\nPer [National Health Expenditure (NHE) data](https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsHistorical.html):\n> \"_...private insurers absorb administrative overhead (and profits) equivalent to $600–$700 annually per member, as compared with approximately $200 for Medicare’s traditional fee-for-service model..._\"`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1100,"value":"\nmd`In the public sector, the calculated waste was split fairly evenly between clinical and administrative setting -- the highest single waste category was overtreatment (one example being diagnostic imaging for uncomplicated headaches or back problems).\n\nIn the private sector, around **two-thirds of waste is administrative and operational** and the highest single category by a wide margin is administrative complexity. At least partially to blame is the _[mosaic of smaller markets for particular services or products](https://www.healthaffairs.org/do/10.1377/hblog20180530.245587/full/)_, each with different software, pay structure, etc.\n\n

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1146,"value":"md`___\n## As costs go up and up, health outcomes are not improving at a comparable rate. \n
\n## In fact, not even keeping pace with other developed countries...\n___`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1201,"value":"md`**[Gapminder.org](https://www.gapminder.org/)**`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1174,"value":"html``","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":756,"value":"md`___\n### The U.S. is looking for value in health care\n\nValue-based care is the umbrella term for numerous initiatives that look to reward health providers for better patient outcomes rather than services provided. One common approach ties quality measures with incentives (🥕carrot) or penalties (stick 🏏).\n\nOne such program is Medicare's [Hospital Value Based Purchasing](https://data.medicare.gov/Hospital-Compare/Hospital-Value-Based-Purchasing-HVBP-Total-Perform/ypbt-wvdk) (HVBP) program. According to data for the HVBP program, Clinical Care and Safety measures are much more evenly distributed than Engagement and Efficiency measures. Notice the sharp right skew on the latter, indicating that relatively few perform well on this measure.\n\nAlso, being exceptional in any one category isn't highly correlated with success in any other category.\n\n_Try scrubbing each chart (click and drag) to identify how they correlate to each other_\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1271,"value":"md`**HVPB Performance Measures**`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":142,"value":"$4d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1262,"value":"md`
\n_What can we learn from this?_\n\nFirst, that efficiency and patient engagement are **not what health care orgs traditionally do** and it's not how they've measured success historically.\n\nSecond, perhaps it reenforces the claim that clinical care represents only 10-20 percent of health outcomes, and that health care orgs are often ill-equipped to deal with the other 80%, [Social Determinants of Health](https://nam.edu/social-determinants-of-health-101-for-health-care-five-plus-five/) (SDoH).\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1307,"value":"md`With the largest payout over $10 million in 2017 and total payments somewhere far north of **${(\n Math.round(\n d3.sum(\n hvbpPayouts,\n d => d.count * +d.payout.split(' to ')[0].replace(/[>\\$,]/g, '')\n ) / 1000000\n ) * 1000000\n).toLocaleString(\n undefined,\n numberFormats.usd_0\n)}***, there's real money on the line!`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1367,"value":"md`_*Using the low end of each incentive range, knowing that over 500 incentives between $1 and $10 million were awarded_`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1310,"value":"vl\n .markBar({ fill: 'rgb(50,150,50)' })\n .data(\n hvbpPayouts.map(d => ({\n ...d,\n order: +d.payout.split(' to ')[0].replace(/[>\\$,]/g, '')\n }))\n )\n .encode(\n vl\n .x()\n .fieldO('payout')\n .sort({ field: 'order', order: \"ascending\" }),\n vl.y().fieldQ('count'),\n vl.tooltip('count')\n )\n .height(200)\n .title('Hosptial Value Based Purchasing Incentives (2017)')\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1277,"value":"md`___\n### What do physicians need to provide more effecient care?\n\nAccording to findings from Deloitte’s 2018 Survey of Physicians, in short:\n> _Physicians want, but lack, data on health care costs_\n\n

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1237,"value":"md`___\n## How should Redox be positioned to have the largest impact as the US healthcare system shifts to Value Based Care?\n___`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1232,"value":"md`${slides({\n id: '1v9_6s7QGymGT_I40UtV12mAweJHosoRL-bUD1rcChpE',\n w: width\n})}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1449,"value":"viewof groovy = slider({\n value: 4,\n min: 0,\n max: 400,\n step: 1,\n description: \"make it groovy?\"\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1489,"value":"html`${end}`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1163,"value":"md`## Appendix`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1436,"value":"end = {\n // const hr = `

`;\n const discoBall = //\"https://media.giphy.com/media/7rzbxdu0ZEXLy/giphy.gif\";\n \"https://media.giphy.com/media/3o7aTAO0ySZp86eDfi/giphy.gif\";\n const div = md`

40 ? 'block' : 'none'\n }; opacity: ${(groovy - 40) / 100}\">\n

`;\n const color = groovy <= 4 ? 'lightgrey' : d3.interpolateRainbow(now / 1000);\n div.style.border = `solid ${groovy}px ${color}`;\n div.style.backgroundColor = color;\n return div;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":240,"value":"vl\n .markBar()\n .data(hrrp)\n .encode(\n vl\n .x()\n .fieldQ('excess_readmission_ratio')\n .bin({ maxbins: 60 })\n .scale({ nice: true }),\n vl.y().count(),\n vl.tooltip([vl.y().count(), vl.y().median('excess_readmission_ratio')])\n )\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":117,"value":"viewof selectedField = {\n const outOfFields = Object.keys(data[0]).filter(k =>\n data[0][k].includes('out of')\n );\n return select(outOfFields);\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":47,"value":"vl\n .markBar()\n .data(\n data.map(d => ({\n ...d,\n rate:\n Math.round(\n (100 * +d[selectedField].split(' out of ')[0]) /\n +d[selectedField].split(' out of ')[1]\n ) / 100\n }))\n )\n .encode(vl.x().fieldN(\"rate\"), vl.y().count())\n .render()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"function fetchData(url, format) {\n return fetch(`${url}.${format}?$limit=5000`, {\n headers: new Headers({\n \"X-App-Token\": `${Secret(\"MEDICARE_GOV_API_TOKEN\")}`\n })\n }).then(response => {\n if (!response.ok) throw new Error(response.status);\n return response.json();\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"medicareGovUrl = \"https://data.medicare.gov/resource/\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":34,"value":"data = {\n const data = d3.csv(\n \"https://data.medicare.gov/api/views/pudb-wetr/rows.csv\",\n // fix all field names to be lower case and underscore\n d => {\n return Object.keys(d).reduce((prev, curr) => {\n return { ...prev, [fixFieldName(curr)]: d[curr] };\n }, {});\n }\n );\n\n function fixFieldName(str) {\n return str\n .toLowerCase()\n .replace(/^\\s+/, \"\")\n .replace(/\\s+/g, \"_\")\n .replace(/-+/g, \"_\");\n }\n\n return data;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":136,"value":"hvbpClinicalCare = medicareGovData(\n \"https://data.medicare.gov/api/views/pudb-wetr/rows.csv\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":138,"value":"hvbpTotalPerformance = medicareGovData(\n \"https://data.medicare.gov/api/views/ypbt-wvdk/rows.csv\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1299,"value":"// 2017 incentives https://www.medicare.gov/hospitalcompare/data/value-based-incentive.html\nhvbpPayouts = d3.tsvParse(\n `payout\\tcount\n>$1,000,000\t524\n$950,001 to $1,000,000\t36\n$900,001 to $950,000\t44\n$850,001 to $900,000\t52\n$800,001 to $850,000\t50\n$750,001 to $800,000\t59\n$700,001 to $750,000\t73\n$650,001 to $700,000\t78\n$600,001 to $650,000\t85\n$550,001 to $600,000\t88\n$500,001 to $550,000\t86\n$450,001 to $500,000\t115\n$400,001 to $450,000\t136\n$350,001 to $400,000\t153\n$300,001 to $350,000\t152\n$250,001 to $300,000\t151\n$200,001 to $250,000\t190\n$150,001 to $200,000\t198\n$100,001 to $150,000\t231\n$50,001 to $100,000\t259\n$1 to $50,000\t184\n$0 to $0\t0`,\n d => ({ ...d, count: +d.count })\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":237,"value":"hrrp = medicareGovData(\"https://data.medicare.gov/api/views/9n3s-kdb3/rows.csv\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":132,"value":"function medicareGovData(url) {\n return d3.csv(\n // example: \"https://data.medicare.gov/api/views/pudb-wetr/rows.csv\",\n url,\n // fix all field names to be lower case and underscore\n d => {\n return Object.keys(d).reduce((prev, curr) => {\n return { ...prev, [fixFieldName(curr)]: d[curr] };\n }, {});\n }\n );\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":284,"value":"expenditureData = {\n const parsedData = await d3\n .tsv(\n \"https://docs.google.com/spreadsheets/d/e/2PACX-1vRGS0kCTS1n-LVDbI7fwVqXW6afz1ghqzs_KZSdmiiZCW1zS0aNpk4XUEPUDnCeIkLTpWvAn8uy0k7m/pub?gid=1081125121&single=true&output=tsv\"\n )\n .then(data =>\n data\n .map(d => {\n // long format with {year: , measure_name: } objects\n return Object.keys(d).reduce((prev, curr) => {\n return prev.concat({\n year: +curr,\n [fixFieldName(d.measure)]: +d[curr]\n });\n }, []);\n })\n .flat()\n );\n\n // roll up to one object per year\n return d3\n .nest()\n .key(d => d.year)\n .entries(parsedData)\n .map(d => {\n // reduce all measures to a single year \"observation\"\n return {\n ...d.values.reduce((prev, curr) => {\n return { ...prev, ...curr };\n }, [])\n };\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":428,"value":"hcciCostUtilization = d3.tsv(\n \"https://docs.google.com/spreadsheets/d/e/2PACX-1vRGS0kCTS1n-LVDbI7fwVqXW6afz1ghqzs_KZSdmiiZCW1zS0aNpk4XUEPUDnCeIkLTpWvAn8uy0k7m/pub?gid=0&single=true&output=tsv\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":628,"value":"numberFormats = {\n const num_digits = (min, max) => ({\n minimumFractionDigits: min,\n maximumFractionDigits: max\n });\n const num_0 = num_digits(0, 0);\n const num_1 = num_digits(1, 1);\n const num_2 = num_digits(2, 2);\n\n return {\n usd_0: { style: \"currency\", currency: \"USD\", ...num_0 },\n percent_0: { style: \"percent\", ...num_0 },\n percent_1: { style: \"percent\", ...num_1 },\n percent_2: { style: \"percent\", ...num_2 },\n number_0: { ...num_0 },\n number_1: { ...num_1 },\n number_2: { ...num_2 }\n };\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":594,"value":"$4e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":834,"value":"$4f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1153,"value":"// OECD (2019), Health spending (indicator). doi: 10.1787/8643de7e-en (Accessed on 11 September 2019)\noecd = d3.tsv(\n \"https://docs.google.com/spreadsheets/d/e/2PACX-1vRGS0kCTS1n-LVDbI7fwVqXW6afz1ghqzs_KZSdmiiZCW1zS0aNpk4XUEPUDnCeIkLTpWvAn8uy0k7m/pub?gid=76004026&single=true&output=tsv\"\n)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":331,"value":"function fixFieldName(str) {\n return str\n .toLowerCase()\n .replace(/^\\s+/, \"\") // start of line\n .replace(/\\s+$/, \"\") // end of line\n .replace(/[^a-z0-9 -]/g, \"\") // no special characters\n .replace(/\\s+/g, \"_\") // spaces to _\n .replace(/-+/g, \"_\"); // - to _\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":649,"value":"viewof captureProportion = new View(0.5)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":110,"value":"import { select, slider } from \"@jashkenas/inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":641,"value":"import { bind } from \"@mbostock/inline-inputs\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":646,"value":"import { View } from \"@mbostock/synchronized-views\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1227,"value":"import { slides } from '@asg017/google-drive'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1124,"value":"slide_style","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":1120,"value":"import { slide, slide_style } from \"@mbostock/slide\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":44,"value":"import { vl } from '@vega/vega-lite-api'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"d3 = require(\"d3@5\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W50","stdlib":"1"}} 24:null