Department of Labor Logo United States Department of Labor
Dot gov

The .gov means it's official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.


The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Bureau of Labor Statistics > Price and Index Number Research > Price research data > Research Disease Based Price Indexes


  • The September 2021 Disease-Based Price Indexes (XLSM) are now available.
  • Indexes for select specific conditions (XLSX) are now available.
  • Standard deviations of the main indexes (XLSX) and of the indexes for select specific conditions (XLSX) are now available.

On This Page

PINR Research Disease-Based Price Indexes

What are Disease Based Price Indexes?

A Disease-Based Price Index (DBPI) measures changes in the average price level to treat an episode of specific disease. A DBPI is calculated by estimating the average expenditure for all medical services used to treat a specific medical condition. It is a good indicator of medical prices in health care because an average customer is more interested in the total costs of treating a disease than the price for a single medical service such as one visit to doctor's office. See the complete description of our methods to construct disease based price indexes.

How do these indexes differ from the medical component of the CPI or PPI?

Currently published official medical price indexes track the price changes of a fixed market basket of medical goods and services while DBPIs encompass all services related to a specific medical condition over a period of time. DBPIs reflect not only changes in the price of the medical services, but also changes in the average utilization of the services for treating a disease. Traditional service based indexes have difficulty capturing technological improvements that allow diseases to be treated using fewer medical services or treatments moving to less intensive settings, e.g. inpatient to outpatient.

How do BLS's DBPIs differ from BEA's MCE indexes in the health care satellite account?

Taking a recommendation from National Research Council (2010), the U.S. Bureau of Economic Analysis (BEA) introduced a Health Care Satellite Account(HCSA), in which spending is reported by disease rather than by medical goods and services. BEA has also generated the Medical Care Expenditure (MCE) indexes for broad 18 categories of diseases in the HCSA. The HCSA comes with two versions: MEPS account and Blended account.

MEPS account

Since both BEA and BLS (with a 3-year lag) obtain the service quantity information from the Medical Expenditure Panel Survey (MEPS) and use the same index calculation formulas, differences in the indexes should be attributable to the price component. While BEA directly takes into the calculation the average expenditure to treat a disease with all medical services from MEPS, BLS instead uses current monthly CPI/PPI indexes for each medical service to publish timely indexes. In general, the average service prices per encounter grow faster than the service prices per procedure, resulting in a faster growth in BEA’s MEPS aggregate MCE index than BLS’s aggregate DBPI.

Blended account

To address volatility issues due to relatively small sample sizes in MEPS data, BEA incorporates large claims data such as MarketScan Data, Medicare claims, and The Medicare Current Beneficiary Survey as supplements to create the so-called blended account. The MCE indexes for each disease category in the blended account are the same as those in the MEPS account; however, aggregate indexes across all diseases are different because of re-calculated expenditure weights with a variety of databases. Thanks to the increased sample sizes in the blended account, BEA recently released MCE indexes at a finer level - from 18 diseases categories to more than 260 specific medical conditions.

Disease Based Price Indexes: Results and Data

The file below contains charts and the monthly and annual history of the various disease based price indexes and standard deviations from January 1999 to the latest month in 2021. It contains not only the utilization adjusted disease based price indexes but also the indexes that are computed under traditional methods (the Lowe Indexes).

Main Indexes (updated monthly)

    • Price Indexes from 1999 to 2021 (XLSM) - Instructions - Query Tool for the Disease Based Price Indexes (PDF)
    • Standard deviations of the monthly changes in the price indexes from 1999 to 2021 (XLSX)

Indexes for select specific conditions (updated quarterly)

    • Indexes for select specific conditions (XLSX)
    • Standard deviations of the monthly changes in the select specific conditions (XLSX)

Methodology Notes

    • Disease based price index methodology (PDF)
    • Estimating standard deviations (PDF)
    • Explanation - ICD-9 to ICD-10 crosswalk (PDF)

All diagnoses are classified into 17 disease categories by the ICD-10 manual (please see the instructions and explanation document above for detail). We also select 115 medical conditions from the 17 disease categories to produce price indexes at a finer level (Please see Indexes for select specific conditions above). We produce and update our research DBPIs for each category on a monthly and/or an annual basis. The monthly indexes are available as both one month relative price change and cumulative versions from the base period- January 1999. The all-disease indexes are calculated by aggregating the individual disease series.

There are 4 options available for each disease index: fixed quantities (Lowe) or adjusted quantities (disease based), dental combined or dental separated, with or without comorbidity adjustment, and smoothed or unsmoothed. In the fixed quantities indexes, quantities are fixed at the base year level throughout the series. In contrast, quantities are updated annually in the adjusted quantities series. The “dental separated” and “dental combined” option refers to whether the dental diseases are separated from diseases of the digestive system (Category 8). In the comorbidities unadjusted index, if a physician treats two diseases in the same visit, one visit will be allocated to the treatment bundle for each disease. In the comorbidities adjusted index, a fraction of the physician visit is assigned to each disease. The treatment bundle for each disease is updated annually. There are the unsmoothed indexes where all the yearly quantity updates are done in January of each year, which causes a “jump” in the January index, and the smoothed indexes where the annual quantity change is spread over the entire year (1/12 of the yearly quantity adjustment is applied to each month).

The indexes are calculated at the disease level and are then aggregated to form an all-disease index. Figure 1 below compares three different all disease price indexes. The first is the all disease index computed under the traditional fixed-basket method where the medical utilization for each disease is fixed at base period (1999) levels. We call this the Lowe Index and it only captures the changes in the prices of medical goods and services. The next two are disease-based price indexes where one makes an adjustment for comorbidities and the other does not. The comorbidity adjustment has a minimal impact on the Lowe index, so only the unadjusted version is presented. Similarly, separating the dental diseases only has a small effect on the aggregate index, so only the dental separated version is presented. From 1999 to 2021, the disease-based price indexes on average grew less rapidly than the traditional Lowe index. However, there were periods when the reverse was true, particularly from 1999 to 2007. This was a period when health insurance coverage shifted from health maintenance organizations to more generous preferred provider policies. In recent years, the disease-based price indexes have grown more slowly than the Lowe index as average utilization for many diseases has decreased.


Calculating Real Expenditure

Figure 2 shows the effect of using different price indexes to calculate real medical expenditures in 2018.[1] Real expenditure in 2018 is calculated by deflating nominal expenditures by the traditional Lowe Index without comorbidities, DBPI without comorbidities, and DBPI with comorbidities, respectively. Using a disease-based price index results in higher real medical care expenditures for 2018 than using the traditional Lowe price indexes. This also increases real GDP.

Decomposing Nominal Expenditure Growth

The file below contains the results from a decomposition of the growth in nominal expenditures by disease into the parts that come from inflation growth, population growth, and prevalence growth. The DBPIs and Lowe indexes used to deflate nominal expenditures here are dental separated, with and without comorbidities adjustments, and with smoothed quantities indexes.

    • Decomposition of Nominal Expenditure Growth with Comorbidities (XLSX)
    • Decomposition of Nominal Expenditure Growth without Comorbidities (XLSX)
    • Decomposition of Nominal Expenditure Growth by Disease with Comorbidities (XLSX)
    • Decomposition of Nominal Expenditure Growth by Disease without Comorbidities (XLSX)

Background and Development of Disease Based Price Indexes

In 2019, healthcare accounted for 17.7 percent of U.S. Gross Domestic Product (GDP).[2] Because healthcare is such a large sector, it is important that we measure its output and prices correctly. If published healthcare inflation rates are too high, then measured real output growth is too low and consumers are getting more for their healthcare dollar than the published estimates suggest. Similarly, if published healthcare inflation rates are too low, measured real output growth would be too high.

The Bureau of Labor Statistics (BLS) is committed to producing and publishing the most accurate medical price indexes possible. BLS has constructed research disease-based price indexes to find a better way to estimate inflation, real medical output, and real consumption.

Federal statistical agencies currently report medical data for goods and services. The National Health Expenditure Accounts (NHEA), the National Income and Product Accounts (NIPA), the Producer Price Index (PPI), and the Consumer Price Index (CPI) all report their medical statistics for physician services, hospital services, pharmaceuticals and other types of medical goods and services. However, many economists and others who analyze healthcare data believe this is not the best way to report medical statistics. In 1967, the U.S. Department of Health, Education, and Welfare noted:

"...the average consumer of medical care is not as interested in the price of a visit or hospital day as he is in the total cost of an episode of illness.[3]"

Starting with the pioneering work of Anne Scitovsky (1967), many analysts found that reporting medical statistics on a disease basis rather than a goods and services basis could provide better information on well-being. There can be large differences between the two methods because reporting on a disease basis can account for new technology that changes the use of medical resources. For example, in the 1990s a new generation of antidepressants could treat depression with fewer therapy visits. A disease-based price index for depression could account for this change in treatment, but indexes produced under the traditional approach of using medical goods and services could not.

Studies completed in the 1990's and early 2000's compute price indexes for cataracts, heart disease and depression.[4] These studies find that their disease-based price indexes grow less rapidly than indexes based on goods and services. The reason is that innovations changed how medical goods and services are used to treat these diseases. As a result, the Committee on National Statistics (CNSTAT) in 2002 published a recommendation that BLS create research disease-based price indexes.[5] This recommendation calls on BLS to use medical claims data to determine the quantity of physician visits, hospital visits and other inputs and use these quantities as weights in the construction of disease-based price indexes. The prices for these indexes would continue to come from the current price-collection system. While BLS would continue to generate monthly research disease-based price indexes from its monthly price collection system, the quantities would only be updated every year or two. The information on this page results from the CNSTAT recommendation.

When BLS set out to implement the CNSTAT recommendation, we established several criteria. First, the indexes had to be timely. Second, they needed to have a cost-of-living basis. Third, they could be used as an input for the All-Items Consumer Price Index. Fourth, there could be no additional costs or any disruption to existing statistical programs when constructing these indexes. Finally, the methods must be transparent.

Because of the criterion for no additional costs, BLS could not use medical claims for inputs because medical claims data are expensive. Instead, we use the publicly available Medical Expenditure Panel Survey (MEPS). We then get a blended data result, with prices from the BLS price index programs and quantities from MEPS.

One challenge in constructing disease-based price indexes is the choice of a method that accounts for comorbidities. Comorbidities occur when a physician office visit or a hospital visit treats a patient for more than one disease. We construct two types of disease-based price indexes that account for comorbidities differently.

Similar to BLS's currently published Lowe medical indexes, the research disease-based price indexes need a representative sample of medical transaction prices. The sampling of medical prices is a challenging task. Respondent participation in our price-collection programs is voluntary, and the reimbursement rates negotiated between insurers and medical providers often are proprietary. These rates are not posted for all customers to observe in the same way as, say, coffee prices in a grocery store. This puts more burden on respondents for the medical providers and on the BLS field economists who collect these prices. BLS has reduced respondent burden, and we are trying to reduce it even more. We appreciate the cooperation of the medical providers who participate in our price-collection program.

It is a great accomplishment to release these indexes in timely manner without increasing costs or disrupting our current statistical programs. BLS has found a way to use our existing products better.

Yet, there is still much to do. Patients consume medical goods and services to heal or be protected from disease. However, there currently is no reliable data source on the healing and prevention outcomes from medical spending. Many data users have suggested that BLS adjust our healthcare price indexes to reflect changes in the quality of the treatment outcomes that result from new technology. There are many challenges to quality adjustment, and we outline them in our methods.

Disease-based price indexes are in their infancy. We regard them as research indexes because we still need to learn more from the research that we and others will conduct. As we learn and improve these indexes, BLS hopes that they will greatly enhance our understanding of the healthcare sector.

We list below additional research about healthcare price indexes. Not all the authors of the research papers and conference presentations are affiliated with BLS. We provide this information for your convenience, and this research does not necessarily reflect the views or policies of BLS.


[1] We use the MEPS to get the medical spending totals and the most current year is 2018.

[2] This is an estimate from the National Health Expenditure Accounts (NHEA) by the Centers for Medicare & Medicaid Services, CMS.

[3] US Department of Health, Education and Welfare (1967), A Report to the President on Medical Care Prices, U.S. Government Printing Office, page 13.

[4] For heart disease, see Cutler et. al. (1998). For depression, see Berndt et. al. 2002. For cataracts, see Shapiro and Wilcox (1996).

[5] This is recommendation 6.1 in Mackie and Schultze (2002).


    • Aizcorbe A. and Nestoriak N. (2010), "Changing Mix of Medical Care Services: Stylized Facts and Implications for Price Indexes," Journal of Health Economics 30, no. 3 (May): 568—574.
    • Aizcorbe A., Bradley R., Greenaway—McGrevy R., Herauf B., Kane R., Liebman E., Pack S., Rozental L., (2011), "Alternative Price Indexes for Medical Care: Evidence from the MEPS Survey" Bureau of Economic Analysis: Working Paper WP2011—01.
    • Aizcorbe, Ana M. (2013), "Recent Research on Disease—Based Price Indexes: Where Do We Stand?" SURVEY OF CURRENT BUSINESS 93 (July): 9–13.
    • Aizcorbe, Ana M., and Nicole Nestoriak. (2011), "Changing Mix of Medical Care Services: Stylized Facts and Implications for Price Indexes." Journal of Health Economics 30, no. 3 (May): 568–574.
    • Aizcorbe, Ana M., and Tina Highfill. (2014), "Medical Care Expenditure Indexes for the United States, 1980–2006." Paper presented at the Society of Economic Measurement Conference, Chicago, IL, August 18–20.
    • Aizcorbe, Ana M., Bonnie A. Retus, and Shelly Smith (2008), "Toward a Health Care Satellite Account." SURVEY OF CURRENT BUSINESS 88 (May) 24–30.
    • Aizcorbe, Ana M., Eli B. Liebman, David M. Cutler, and Allison B. Rosen, (2012), "Household Consumption Expenditures for Medical Care: An Alternate Presentation." SURVEY OF CURRENT BUSINESS 92 (June): 34–47.
    • Aizcorbe, Ana M., Ralph Bradley, Ryan Greenaway—McGrevy, Brad Herauf, Richard Kane, Eli Liebman, Sarah Pack, and Lyubov Rozental. (2011), "Alternative Price Indexes for Medical Care: Evidence from the MEPS Survey." Bureau of Economic Analysis (BEA) Working Paper WP2011–01. Washington, DC: BEA.
    • Baker C. and Bradley R., (2014), "The Simultaneous Effects of Obesity, Insurance Choice, and Medical Visit Choice on Healthcare Costs," forthcoming, Measuring and Modeling Health Care Costs, Ana Aizcorbe, Colin Baker, Ernst Berndt, and David Cutler, editors University of Chicago Press.
    • Berndt E.R., Bir A., Busch S., Frank R., and Normand, S. (2002), "The Treatment of Medical Depression, 1991—1996: Productive Inefficiency, Expected Outcome Variations, and Price Indexes," Journal of Health Economics, 21: 373—396.
    • Berndt E.R., Busch S.H., Frank R.G. (2001), "Treatment Price Indexes for Acute Phase Major Depression," in: D. M. Cutler and E. R. Berndt (Eds.), Medical Care Output and Productivity, Studies in Income and Wealth. University of Chicago Press Chicago. pp. 463—505.
    • Berndt E.R., Cockburn I., and Griliches Z. (1996), "Pharmaceutical Innovations and Market Dynamics: Tracking Effects on Price Indexes on Anti—Depressant Drugs," Brookings Papers on Economic Activity: Micro—Economic 133—188.
    • Berndt, Ernst R., David M. Cutler, Richard G. Frank, Zvi Griliches, Joseph P. Newhouse, and Jack E. Triplett. (2000), "Medical Care Prices and Output." In Handbook of Health Economics, edited by Anthony J. Culyer and Joseph P Newhouse, 119–180. Amsterdam, The Netherlands: North Holland.
    • Bradley, R., Cardenas, E., Ginsburg, D.H., Rozental, L., Velez, F., (2010), "Producing disease—based price indexes" Monthly Labor Review 133, 20—28.
    • Bradley, Ralph. (2013), "Feasible Methods to Estimate Disease—Based Price Indexes." Journal of Health Economics 32, no. 3 (May): 504–514.
    • Bundorf, K.M., Royalty, A. and Baker, L.C., (2009), "Health Care Cost Growth Among the Privately Insured," Health Affairs, 28(5), 1294—1304.
    • Cawley, J., (2004), "The Impact of Obesity on Wages," Journal of Human Resources, 39(2), 451—474.
    • Cawley, J., and Meyerhoefer, C., (2012), "The Medical Care Costs of Obesity: An Instrumental Variable Approach," Journal of Health Economics, 31(1), 219—230.
    • Chen, A.J., (2012), "When does weight matter?," Journal of Health Economics, 31(1), 285—295.
    • Chernew M.E., Afendulis, C.C., Yulie, H., Zaslavsky, A.M., (2011),"The Impact of Medicare Part D on Hospitalization Rates," Health Services Research, 46:4, 1022—1038.
    • Christian, Michael S. 2007. "Measuring the Output of Health Care in the United States." SURVEY OF CURRENT BUSINESS 87 (June): 78–83.
    • Cutler, D.M, McClellan M., Newhouse J.P, Remler, D., (1998), "Are Medical Prices Declining? Evidence from Heart Attack Treatments," Quarterly Journal of Economics, 13(4) 991—1024.
    • Cutler, David M., Mark McClellan, and Joseph P. Newhouse, (2000) "How Does Managed Care Do It?" The RAND Journal of Economics 31, no. 3: 526–548.
    • Cutler, David M., Mark McClellan, Joseph P. Newhouse, and Dahlia Remler, (1998), "Are Medical Prices Declining? Evidence from Heart Attack Treatments." The Quarterly Journal of Economics 113, no. 4 (November): 991–1024.
    • Diewert, W.E., (1976), "Exact and Superlative Index Numbers," Journal of Econometrics, 46(4), 883—900.
    • Diewert, W.E., (1987), "Index Numbers," The New Palgrave: A Dictionary of Economics, Eatwell J. and Newman P. (eds.) The Macmillan Press, 767—780.
    • Dunn, A., Liebman E.B., and Shapiro A., (2012), "Implications of Utilization Shifts on Medical—Care Price Measurement." Bureau of Economic Analysis (BEA) Working Paper WP2012——09. Washington, DC: BEA.
    • Dunn, Abe, Eli B. Liebman, and Adam Shapiro. (2014), "Developing a Framework for Decomposing Medical Care Expenditure Growth: Exploring Issues of Representativeness." In Measuring Economic Sustainability and Progress, edited by Dale W. Jorgenson, J. Steven Landefeld, and Paul Schreyer, 545–574. Chicago: University of Chicago Press, for the National Bureau of Economic Research;
    • Dunn, Abe, Eli B. Liebman, Lindsey Rittmueller, and Adam Shapiro, (2014), "Defining Disease Episodes and the Effects on the Components of Expenditure Growth." Bureau of Economic Analysis (BEA) Working Paper WP2014–4. Washington, DC: BEA.
    • Dunn, Abe, Eli B. Liebman, Sarah Pack, and Adam Shapiro, (2013), "Medical Care Price Indexes for Patients with Employer—Provided Insurance: Nationally Representative Estimates from MarketScan Data." Health Services Research 48, no. 3 (June): 1173–1190.
    • Feenstra, R.C., (1995), "Exact Hedonic Price Indexes," The Review of Economics and Statistics, 77(4), 634—53.
    • Frank, Richard G., Ernst R. Berndt, and Susan M. Busch. 1999. "Price Indexes for the Treatment of Depression." In Measuring the Prices of Medical Treatments, edited by Jack E. Triplett, 72–102. Washington, DC: The Brookings Institution.
    • Glied, Sherry, (2000), "Managed Care." Handbook of Health Economics, edited by Anthony J. Culyer and Joseph P. Newhouse, 707–753. Amsterdam, The Netherlands: North Holland. Government Accountability Office (GAO). 2008.
    • Hall, Anne E., and Tina Highfill, (2013), "A Regression Based Medical Care Expenditure Index for Medicare Beneficiaries." Bureau of Economic Analysis (BEA) Working Paper WP2013–4. Washington, DC: BEA. 21 January 2015 SURVEY OF CURRENT BUSINESS.
    • Hall, Anne E., and Tina Highfill, (2014), "Calculating Disease—Based Medical Care Expenditure Indexes for Medicare Beneficiaries: A Comparison of Method and Data Choices." Bureau of Economic Analysis Working Paper. Washington, DC: BEA, June.
    • Highfill, Tina, and Elizabeth Bernstein, (2014), "Using Disability Adjusted Life Years to Value the Treatment of Thirty Chronic Conditions in the United States From 1987–2010." In General Conference of the International Association for Research in Income and Wealth. Rotterdam, The Netherlands: South Holland.
    • Konüs, A.A., (1939), "The Problem of the True Index of the Cost of Living," Econometrica, 7, 10—29.
    • M. Kate Bundorf, Anne Royalty, and Laurence C. Baker, (2009) "Health Care Cost Growth Among The Privately Insured" Health Affairs, September/October 28:51294—1304; doi:10.1377/hlthaff.28.5.1294.
    • Mackie C. and Schultze C.L., (2002) At What Price? Conceptualizing and Measuring Cost—of—Living Indexes, National Academy Press.
    • Moulton, Brent R., Brian C. Moyer, and Ana Aizcorbe, (2009), "Adapting BEA’s National and Industry Accounts for a Health Care Satellite Account." Strategies for a BEA Satellite Health Care Account: Summary of a Workshop. Washington, DC: The National Academies Press.
    • Murphy B.H., Holdway M., Lucier J.L., Carnival J., Garabis E., and Cardenas E., (2008) "Proposal for Adjusting the General Hospital Producer Price Index for Quality Change," BLS Manuscript.
    • Murphy, Kevin M., and Robert H. Topel. 2006. "The Value of Health and Longevity." Journal of Political Economy 114, no. 5 (October): 871–903. National Research Council. 2010. Accounting for Health and Health Care: Approaches to Measuring the Sources and Costs of Their Improvement. Washington, DC: The National Academies Press.
    • Pinkovskiy, Maxim, (2014), "The Impact of the Political Response to the Managed Care Backlash on Health Care Spending: Evidence From State Regulations of Managed Care" Working Paper. New York, NY: Federal Reserve Bank of New York.
    • Roehrig, C.S. and Rousseau, D.M., (2010), "The Growth in Cost Per Care Explains Far More of US Health Spending Increases than Rising Disease Prevalence," Health Affairs, 30:9 1657—1663.
    • Roehrig, Charles, George Miller, Graig Lake, and Jenny Bryan. (2009), "National Health Spending by Medical Condition, 1996–2005." Health Affairs 28, no. (March/April): 358–367.
    • Rosen S., (1974), "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, 34—55.
    • Rosen, Allison B., and David M. Cutler, (2007), "Measuring Medical Care Productivity: A Proposal for U.S. National Health Accounts. SURVEY OF CURRENT BUSINESS 87 (June): 54–58.
    • Rosen, Allison B., Eli Liebman, Ana M. Aizcorbe, and David M. Cutler. 2012. "Comparing Commercial Systems for Characterizing Episodes of Care." Bureau of Economic Analysis (BEA) Working Paper WP2012–7. Washington, DC: BEA.
    • Sato K., (1967), "The Two—Level Constant Elasticity of Substitution Production Function," "Review of Economic Studies, vol. 34, 201—218.
    • Sato, K., (1976), "The Ideal Log—Change Index Number," Review of Economics and Statistics, 58(2), 223—228.
    • Scitovsky, A. A., (1967), "Changes in the Costs of Treatment of Selected Illness, 1951—65," American Economic Review LVII, 1182—1195.
    • Selden, Thomas, and Merrile Sing. 2008. "The Distribution of Public Spending for Health Care in the United States, 2002." Health Affairs 27, no. 5 (September/ October): 349–359.
    • Shapiro, Irving, Matthew D. Shapiro, and David W. Wilcox. 2001. "Measuring the Value of Cataract Surgery." In Medical Care Output and Productivity, edited by David M. Cutler and Ernst R. Berndt, 411–437.
    • Shapiro, M. D., and Wilcox, D.M. (1996). "Mismeasurement in the Consumer Price Index: An Evaluation," in Bernanke, Ben S., Julio Rotemberg J. eds., NBER Macroeconomics Annual 1996. Cambridge and London: MIT Press, 93—142.
    • Smith, Shelly. 2009. "A New Approach to Price Measures for Health Care." SURVEY OF CURRENT BUSINESS 89 (February): 17–20.
    • Song X., Marder W., Houchens R., Conklin J.E., Bradley R., (2009), "Can A Disease Based Price Index Improve the Estimation of the Medical CPI ?" , Price Index Concepts and Measurement, Diewert, W.E, Greenlees, J.S., and Hulten C.R. (eds.) National Bureau of Economic Research ER, 329—372.
    • Starr, Martha, Laura Dominiak, and Ana Aizcorbe. (2014) "Decomposing Growth In Spending Finds Annual Cost of Treatment Contributed Most to Spending Growth, 1980——2006." Health Affairs 33 (May) 823——831.
    • Stewart, Susan, David M Cutler, and Allison B. Rosen. 2013. "U.S. Trends in Quality—Adjusted Life Expectancy From 1987 to 2008: Combining National Surveys to More Broadly Track the Health of the Nation." American Journal of Public Health 103 (November) 78–87.
    • Studies in Income and Wealth, vol. 62. Chicago: University of Chicago Press.
    • Thorpe K.E., Florence, C.S., and Joski P., (2004), "Which Medical Conditions Account for the Rise in Health Care Spending?" Health Affairs, W4.437, 437—445.
    • Thorpe, Kenneth E., Curtis S. Florence, Peter Joski. 2004. "Which Medical Conditions Account for the Rise in Health Care Spending?" Health Affairs (August); DOI: 10.1377/hlthaff.w4.437.
    • Triplett J.E., (2001) "What's Different about Health? Human Repair and Car Repair in National Accounts and in National Health Accounts," in Medical Care Output and Productivity, eds. Cutler D.M. and Berndt E.R., University of Chicago Press, 15—96.
    • Trogdon, Justin, Eric A. Finkelstein, and Thomas J. Hoerger. 2008. "Use of Econometric Models To Estimate Expenditure Shares." Health Services Research 43, no. 4 (August): 1442–1452.
    • Zuvekas, Samuel H., and Gary L. Olin. 2009. "Accuracy of Medicare Expenditures in the Medical Expenditure Panel Survey. Inquiry 46, no. 1 (Spring): 92–108.


Last Modified Date: August 27, 2021