US Health Care Spending by Payer and Health Condition, 1996-2016 | Health Care Economics, Insurance, Payment | JN Learning | AMA Ed Hub [Skip to Content]
[Skip to Content Landing]

US Health Care Spending by Payer and Health Condition, 1996-2016

Educational Objective
To understand recent changes in US health care spending.
1 Credit CME
Key Points

Question  How does spending on different health conditions vary by payer (public insurance, private insurance, or out-of-pocket payments) and how has this spending changed over time?

Findings  From 1996 to 2016, total health care spending increased from an estimated $1.4 trillion to an estimated $3.1 trillion. In 2016, private insurance accounted for 48.0% (95% CI, 48.0%-48.0%) of health care spending, public insurance for 42.6% (95% CI, 42.5%-42.6%) of health care spending, and out-of-pocket payments for 9.4% (95% CI, 9.4%-9.4%) of health care spending. After adjusting for population size and aging, the annualized spending growth rate was 2.6% (95% CI, 2.6%-2.6%) for private insurance, 2.9% (95% CI, 2.9%-2.9%) for public insurance, and 1.1% (95% CI, 1.0%-1.1%) for out-of-pocket payments.

Meaning  Understanding how much each payer spent on each health condition and how these amounts have changed over time can inform health care policy.

Abstract

Importance  US health care spending has continued to increase and now accounts for 18% of the US economy, although little is known about how spending on each health condition varies by payer, and how these amounts have changed over time.

Objective  To estimate US spending on health care according to 3 types of payers (public insurance [including Medicare, Medicaid, and other government programs], private insurance, or out-of-pocket payments) and by health condition, age group, sex, and type of care for 1996 through 2016.

Design and Setting  Government budgets, insurance claims, facility records, household surveys, and official US records from 1996 through 2016 were collected to estimate spending for 154 health conditions. Spending growth rates (standardized by population size and age group) were calculated for each type of payer and health condition.

Exposures  Ambulatory care, inpatient care, nursing care facility stay, emergency department care, dental care, and purchase of prescribed pharmaceuticals in a retail setting.

Main Outcomes and Measures  National spending estimates stratified by health condition, age group, sex, type of care, and type of payer and modeled for each year from 1996 through 2016.

Results  Total health care spending increased from an estimated $1.4 trillion in 1996 (13.3% of gross domestic product [GDP]; $5259 per person) to an estimated $3.1 trillion in 2016 (17.9% of GDP; $9655 per person); 85.2% of that spending was included in this study. In 2016, an estimated 48.0% (95% CI, 48.0%-48.0%) of health care spending was paid by private insurance, 42.6% (95% CI, 42.5%-42.6%) by public insurance, and 9.4% (95% CI, 9.4%-9.4%) by out-of-pocket payments. In 2016, among the 154 conditions, low back and neck pain had the highest amount of health care spending with an estimated $134.5 billion (95% CI, $122.4-$146.9 billion) in spending, of which 57.2% (95% CI, 52.2%-61.2%) was paid by private insurance, 33.7% (95% CI, 30.0%-38.4%) by public insurance, and 9.2% (95% CI, 8.3%-10.4%) by out-of-pocket payments. Other musculoskeletal disorders accounted for the second highest amount of health care spending (estimated at $129.8 billion [95% CI, $116.3-$149.7 billion]) and most had private insurance (56.4% [95% CI, 52.6%-59.3%]). Diabetes accounted for the third highest amount of the health care spending (estimated at $111.2 billion [95% CI, $105.7-$115.9 billion]) and most had public insurance (49.8% [95% CI, 44.4%-56.0%]). Other conditions estimated to have substantial health care spending in 2016 were ischemic heart disease ($89.3 billion [95% CI, $81.1-$95.5 billion]), falls ($87.4 billion [95% CI, $75.0-$100.1 billion]), urinary diseases ($86.0 billion [95% CI, $76.3-$95.9 billion]), skin and subcutaneous diseases ($85.0 billion [95% CI, $80.5-$90.2 billion]), osteoarthritis ($80.0 billion [95% CI, $72.2-$86.1 billion]), dementias ($79.2 billion [95% CI, $67.6-$90.8 billion]), and hypertension ($79.0 billion [95% CI, $72.6-$86.8 billion]). The conditions with the highest spending varied by type of payer, age, sex, type of care, and year. After adjusting for changes in inflation, population size, and age groups, public insurance spending was estimated to have increased at an annualized rate of 2.9% (95% CI, 2.9%-2.9%); private insurance, 2.6% (95% CI, 2.6%-2.6%); and out-of-pocket payments, 1.1% (95% CI, 1.0%-1.1%).

Conclusions and Relevance  Estimates of US spending on health care showed substantial increases from 1996 through 2016, with the highest increases in population-adjusted spending by public insurance. Although spending on low back and neck pain, other musculoskeletal disorders, and diabetes accounted for the highest amounts of spending, the payers and the rates of change in annual spending growth rates varied considerably.

Sign in to take quiz and track your certificates

Buy This Activity

JN Learning™ is the home for CME and MOC from the JAMA Network. Search by specialty or US state and earn AMA PRA Category 1 CME Credit™ from articles, audio, Clinical Challenges and more. Learn more about CME/MOC

CME Disclosure Statement: Unless noted, all individuals in control of content reported no relevant financial relationships. If applicable, all relevant financial relationships have been mitigated.

Article Information

Corresponding Author: Joseph L. Dieleman, PhD, Institute for Health Metrics and Evaluation, 2301 Fifth Ave, Ste 600, Seattle, WA 98121 (dieleman@uw.edu).

Accepted for Publication: January 21, 2020.

Author Contributions: Dr Dieleman had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Dieleman, Chen, Liu, Matyasz, Campbell, Naghavi, Sadat, Murray.

Acquisition, analysis, or interpretation of data: Dieleman, Cao, Chapin, Chen, Li, Liu, Horst, Kaldjian, Matyasz, Scott, Bui, Campbell, Duber, Dunn, Flaxman, Fitzmaurice, Naghavi, Sadat, Shieh, Squires, Yeung.

Drafting of the manuscript: Dieleman, Cao, Chen, Li, Horst, Kaldjian, Bui.

Critical revision of the manuscript for important intellectual content: Dieleman, Chapin, Liu, Horst, Matyasz, Scott, Bui, Campbell, Duber, Dunn, Flaxman, Fitzmaurice, Naghavi, Sadat, Shieh, Squires, Yeung, Murray.

Statistical analysis: Dieleman, Cao, Chen, Li, Liu, Horst, Kaldjian, Matyasz, Campbell, Flaxman, Sadat, Shieh, Squires.

Obtained funding: Dieleman, Chapin.

Administrative, technical, or material support: Dieleman, Chapin, Horst, Kaldjian, Matyasz, Duber, Dunn.

Supervision: Dieleman, Chapin, Naghavi, Murray.

Conflict of Interest Disclosures: Dr Dieleman reported receiving grants from the Bill and Melinda Gates Foundation, the National Institutes of Health, and the National Pharmaceutical Council; and receiving other funding from Gates Ventures. Dr Flaxman reported receiving personal fees from Kaiser Permanente, Sanofi, Merck for Mothers, Agathos Ltd, and NORC (formerly called the National Opinion Research Center); and receiving grants from the Bill and Melinda Gates Foundation, the Alfred P. Sloan Foundation, and the National Science Foundation. No other disclosures were reported.

Funding/Support: This research was supported by the Peterson Center on Healthcare and by grant P30AG047845 from the National Institute on Aging.

Role of the Funder/Sponsor: The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The views expressed in this article are those of the authors and do not necessarily represent the views of the US Bureau of Economic Analysis or the US Department of Commerce.

Additional Contributions: We acknowledge with gratitude the contributions of Maxwell Birger, MD, Hannah Hamavid, BA, Elizabeth Johnson, MPA, Jonathan Joseph, BS, Liya Lomsadze, BS, and Alex Reynolds, BA (all formerly with the Institute for Health Metrics and Evaluation). Their work was critical in developing the foundations of this research. From the Vitality Group, we thank Francois Millard, FIA, FSA, and Howard Bolnick, MBA, FSA, for contributions to the manuscript. We acknowledge Jay Want, MD, Jeffrey Selberg, MSc, Emily Zyborowicz, MPH, Emily Weisberger, MPH, and Frederica Stahl, MPhil, from the Peterson Center on Healthcare for their work advising the trajectory of this research. Finally, we thank Larry Levitt, MPP, from the Henry J. Kaiser Family Foundation for his contributions to this article and the research as a whole. No person was compensated for their contributions.

References
1.
Chang  AY, Cowling  K, Micah  AE,  et al; Global Burden of Disease Health Financing Collaborator Network.  Past, present, and future of global health financing: a review of development assistance, government, out-of-pocket, and other private spending on health for 195 countries, 1995-2050.  Lancet. 2019;393(10187):2233-2260. doi:10.1016/S0140-6736(19)30841-4PubMedGoogle ScholarCrossref
2.
Morrisey  M. Health insurance. In:  Health Insurance. 2nd ed. Chicago, IL: Health Administration Press; 1-24.
3.
Centers for Medicare & Medicaid Services. NHEA related studies. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NHEA-Related-Studies.html. Published November 20, 2015. Accessed December 15, 2017.
4.
Centers for Medicare & Medicaid Services. Historical. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsHistorical.html. Published January 8, 2018. Accessed October 17, 2018.
5.
Dieleman  JL, Baral  R, Birger  M,  et al.  US spending on personal health care and public health, 1996-2013.  JAMA. 2016;316(24):2627-2646. doi:10.1001/jama.2016.16885PubMedGoogle ScholarCrossref
6.
Institute for Health Metrics and Evaluation. DEX home. http://www.healthdata.org/dex. Accessed December 15, 2017.
7.
Dieleman  JL, Squires  E, Bui  AL,  et al.  Factors associated with increases in US health care spending, 1996-2013.  JAMA. 2017;318(17):1668-1678. doi:10.1001/jama.2017.15927PubMedGoogle ScholarCrossref
8.
Bui  AL, Dieleman  JL, Hamavid  H,  et al.  Spending on children’s personal health care in the United States, 1996-2013.  JAMA Pediatr. 2017;171(2):181-189. doi:10.1001/jamapediatrics.2016.4086PubMedGoogle ScholarCrossref
9.
Agency for Healthcare Research and Quality. Medical Expenditure Panel Survey for 2013. https://www.meps.ahrq.gov/mepsweb/. Accessed January 23, 2020.
10.
Agency for Healthcare Research and Quality; Healthcare Cost and Utilization Project. Nationwide Inpatient Sample for 2012. https://www.hcup-us.ahrq.gov/db/nation/nis/nisdbdocumentation.jsp. Accessed January 23, 2020.
11.
Truven Health Analytics. United States MarketScan Medicare supplemental and coordination of benefits database for 2010. http://ghdx.healthdata.org/record/united-states-marketscan-medicare-supplemental-and-coordination-benefits-database-2010. Accessed January 23, 2020.
12.
US Centers for Disease Control and Prevention; National Center for Health Statistics. NAMCS and NHAMCS web tables. https://www.cdc.gov/nchs/ahcd/web_tables.htm. Published October 26, 2017. Accessed March 2, 2018.
13.
US Centers for Disease Control and Prevention; National Center for Health Statistics. National nursing home survey. https://www.cdc.gov/nchs/nnhs/index.htm. Published January 10, 2018. Accessed March 30, 2018.
14.
Foreman  KJ, Naghavi  M, Ezzati  M.  Improving the usefulness of US mortality data: new methods for reclassification of underlying cause of death.  Popul Health Metr. 2016;14:14. doi:10.1186/s12963-016-0082-4PubMedGoogle ScholarCrossref
15.
Dieleman  JL, Baral  R, Johnson  E,  et al.  Adjusting health spending for the presence of comorbidities: an application to United States national inpatient data.  Health Econ Rev. doi:10.1186/s13561-017-0166-2Google Scholar
16.
Hamavid  H, Birger  M, Bulchis  AG,  et al.  Assessing the complex and evolving relationship between charges and payments in US hospitals: 1996-2012.  PLoS One. 2016;11(7):e0157912. doi:10.1371/journal.pone.0157912PubMedGoogle Scholar
17.
Substance Abuse and Mental Health Services Administration. Results from the 2016 national survey on drug use and health: detailed tables. http://www.samhsa.gov/data/report/results-2016-national-survey-drug-use-and-health-detailed-tables. Published September 7, 2017. Accessed January 23, 2020.
18.
Smithson  M, Verkuilen  J.  A better lemon squeezer? maximum-likelihood regression with beta-distributed dependent variables.  Psychol Methods. 2006;11(1):54-71. doi:10.1037/1082-989X.11.1.54PubMedGoogle ScholarCrossref
19.
Aitchison  J.  The Statistical Analysis of Compositional Data. Caldwell, NJ: The Blackburn Press; 2003.
20.
US Department of Commerce. Bureau of Economic Analysis. https://www.bea.gov/data/prices-inflation/gdp-price-index. Published March 2, 2018. Accessed March 1, 2018.
21.
Squires  E, Duber  H, Campbell  M,  et al.  Health care spending on diabetes in the US, 1996-2013.  Diabetes Care. 2018;41(7):1423-1431. doi:10.2337/dc17-1376PubMedGoogle ScholarCrossref
22.
Patrick  SW, Schumacher  RE, Benneyworth  BD, Krans  EE, McAllister  JM, Davis  MM.  Neonatal abstinence syndrome and associated health care expenditures: United States, 2000-2009.  JAMA. 2012;307(18):1934-1940. doi:10.1001/jama.2012.3951PubMedGoogle ScholarCrossref
23.
Tangka  FK, Trogdon  JG, Richardson  LC, Howard  D, Sabatino  SA, Finkelstein  EA.  Cancer treatment cost in the United States: has the burden shifted over time?  Cancer. 2010;116(14):3477-3484. doi:10.1002/cncr.25150PubMedGoogle ScholarCrossref
24.
Hwang  W, Weller  W, Ireys  H, Anderson  G.  Out-of-pocket medical spending for care of chronic conditions.  Health Aff (Millwood). 2001;20(6):267-278. doi:10.1377/hlthaff.20.6.267PubMedGoogle ScholarCrossref
25.
GBD 2015 Disease and Injury Incidence and Prevalence Collaborators.  Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015.  Lancet. 2016;388(10053):1545-1602. doi:10.1016/S0140-6736(16)31678-6PubMedGoogle ScholarCrossref
26.
Choosing Wisely website. Lumbar spine imaging recommendations from the American College of Emergency Physicians. http://www.choosingwisely.org/clinician-lists/acep-lumbar-spine-imaging-in-the-ed/. Accessed October 19, 2018.
27.
Chou  R, Deyo  R, Friedly  J,  et al.  Systemic pharmacologic therapies for low back pain: a systematic review for an american college of physicians clinical practice guideline.  Ann Intern Med. 2017;166(7):480-492. doi:10.7326/M16-2458PubMedGoogle ScholarCrossref
28.
Chou  R, Deyo  R, Friedly  J,  et al.  Nonpharmacologic therapies for low back pain: a systematic review for an American College of Physicians Clinical Practice Guideline.  Ann Intern Med. 2017;166(7):493-505. doi:10.7326/M16-2459PubMedGoogle ScholarCrossref
29.
IQVIA website. Understanding the drivers of drug expenditure in the US: November 2017. https://www.iqvia.com/insights/the-iqvia-institute/reports/understanding-the-drivers-of-drug-expenditure-in-the-us. Accessed October 17, 2018.
30.
Coughlin  TA, Holahan  J, Caswell  K. Uncompensated care for the uninsured in 2013: a detailed examination—sources of funding for uncompensated care. https://www.kff.org/report-section/uncompensated-care-for-the-uninsured-in-2013-a-detailed-examination-sources-of-funding-for-uncompensated-care/. Accessed March 1, 2018.
31.
US Office of Personnel Management. Healthcare: plan information. https://www.opm.gov/healthcare-insurance/healthcare/plan-information/plans/. Accessed March 2, 2018.
32.
Rae  M, Claxton  G, Panchal  N. Tax subsidies for private health insurance. https://www.kff.org/private-insurance/issue-brief/tax-subsidies-for-private-health-insurance/. Accessed March 2, 2018.
33.
Currie  J, Ho  K, Kelly  BR, Kuziemko  I. Who will be our moral conscience now? a tribute to Uwe Reinhardt. https://www.healthaffairs.org/do/10.1377/hblog20190805.922868/full/. Accessed February 4, 2020.
Want full access to the AMA Ed Hub?
After you sign up for AMA Membership, make sure you sign in or create a Physician account with the AMA in order to access all learning activities on the AMA Ed Hub
Buy this activity
Close
Want full access to the AMA Ed Hub?
After you sign up for AMA Membership, make sure you sign in or create a Physician account with the AMA in order to access all learning activities on the AMA Ed Hub
Buy this activity
Close
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right
Close

Name Your Search

Save Search
Close
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Close

Lookup An Activity

or

Close

My Saved Searches

You currently have no searches saved.

Close

My Saved Courses

You currently have no courses saved.

Close
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right
Close