Skip to main page content
U.S. flag

An official website of the United States government

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.

Https

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.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2023 Jun 6;21(1):201.
doi: 10.1186/s12916-023-02896-6.

Disease-specific health spending by age, sex, and type of care in Norway: a national health registry study

Jonas Minet Kinge  1   2 , Joseph L Dieleman  3 , Øystein Karlstad  4 , Ann Kristin Knudsen  4 , Søren Toksvig Klitkou  5 , Simon I Hay  3 , Theo Vos  3 , Christopher J L Murray  3 , Stein Emil Vollset  3
Affiliations

Disease-specific health spending by age, sex, and type of care in Norway: a national health registry study

Jonas Minet Kinge et al. BMC Med. .

Abstract

Background: Norway is a high-income nation with universal tax-financed health care and among the highest per person health spending in the world. This study estimates Norwegian health expenditures by health condition, age, and sex, and compares it with disability-adjusted life-years (DALYs).

Methods: Government budgets, reimbursement databases, patient registries, and prescription databases were combined to estimate spending for 144 health conditions, 38 age and sex groups, and eight types of care (GPs; physiotherapists & chiropractors; specialized outpatient; day patient; inpatient; prescription drugs; home-based care; and nursing homes) totaling 174,157,766 encounters. Diagnoses were in accordance with the Global Burden of Disease study (GBD). The spending estimates were adjusted, by redistributing excess spending associated with each comorbidity. Disease-specific DALYs were gathered from GBD 2019.

Results: The top five aggregate causes of Norwegian health spending in 2019 were mental and substance use disorders (20.7%), neurological disorders (15.4%), cardiovascular diseases (10.1%), diabetes, kidney, and urinary diseases (9.0%), and neoplasms (7.2%). Spending increased sharply with age. Among 144 health conditions, dementias had the highest health spending, with 10.2% of total spending, and 78% of this spending was incurred at nursing homes. The second largest was falls estimated at 4.6% of total spending. Spending in those aged 15-49 was dominated by mental and substance use disorders, with 46.0% of total spending. Accounting for longevity, spending per female was greater than spending per male, particularly for musculoskeletal disorders, dementias, and falls. Spending correlated well with DALYs (Correlation r = 0.77, 95% CI 0.67-0.87), and the correlation of spending with non-fatal disease burden (r = 0.83, 0.76-0.90) was more pronounced than with mortality (r = 0.58, 0.43-0.72).

Conclusions: Health spending was high for long-term disabilities in older age groups. Research and development into more effective interventions for the disabling high-cost diseases is urgently needed.

Keywords: Burden of disease; Cost of illness; Disability-adjusted life years (DALYs); Disease expenditures; Norway.

PubMed Disclaimer

Conflict of interest statement

Søren Toksvig Klitkou, formerly employed by the Norwegian Institute of Public Health, is currently an employee of MSD Norway, a subsidiary of Merck & Co., Inc., Kenilworth, NJ, USA, which manufactures drugs and vaccines.

Øystein Karlstad reports participation in research projects funded by Novo Nordisk, LEO Pharma, and Bristol Myers Squibb, all regulator-mandated phase IV studies, all with funds paid to his institution (no personal fees), outside of the submitted work.

The other authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Health care spending in Norway by type of care and health condition category, 2019 Notes: * Communicable, maternal, neonatal, and nutritional diseases. ** DUBE indicates diabetes, urogenital, blood, and endocrine diseases. Reported in 2019 Norwegian Kroner. Increases in spending along the x-axis show more spending. Additional File 1, Supplementary Table 1 lists the aggregated condition category in which each condition was classified
Fig. 2
Fig. 2
Health care spending in Norway by age, sex, and aggregated condition category, 2019 Notes: * Communicable, maternal, neonatal, and nutritional diseases. ** DUBE indicates diabetes, urogenital, blood, and endocrine diseases. Reported in 2019 Norwegian Kroner. Panel A illustrates health care spending by age, sex, and aggregated condition category. Panel B illustrates health care spending per person. Additional File 1, Supplementary Table 1 lists the aggregated condition category in which each condition was classified. Increases in spending along the x-axis show more spending. Population by age and sex is from Statistics Norway and is the 1 of January 2019. Some persons die during the year. Additional analysis accounting for deaths is in Additional File 1, Supplementary Fig. 2
Fig. 3
Fig. 3
Scatterplot of percent of DALYs and percent of spending in 2019 Notes: * Communicable, maternal, neonatal, and nutritional diseases. ** DUBE indicates diabetes, urogenital, blood, and endocrine diseases. Both percent DALYs and percent spending sum to 100%. The solid line represents the line of equality. Data on DALYs by health condition in 2019 are from the Global Burden of Disease Collaborative Network [16]. DEX-health conditions are based upon the GBD health conditions, with a few deviations as health conditions include categories for non-disease-related spending and risk factors. These were excluded. In addition, maternal and neonatal conditions were aggregated. Hence, the scatterplot includes a total of 115 health conditions
See this image and copyright information in PMC

Comment in

References

    1. OECD . Income inequality (indicator) 2022.
    1. OECD . Health at a Glance 2021. 2021.
    1. Kinge JM, Sælensminde K, Dieleman J, Vollset SE, Norheim OF. Economic losses and burden of disease by medical conditions in Norway. Health Policy. 2017;121(6):691–698. doi: 10.1016/j.healthpol.2017.03.020. - DOI - PubMed
    1. Micah AE, Cogswell IE, Cunningham B, Ezoe S, Harle AC, Maddison ER, et al. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990–2050. Lancet. 2021;398(10308):1317–1343. doi: 10.1016/S0140-6736(21)01258-7. - DOI - PMC - PubMed
    1. Bierl M, Marsh T, Webber L, Brown M, McPherson K, Rtveladze K. Apples and oranges: a comparison of costing methods for obesity. Obes Rev. 2013;14(9):693–706. doi: 10.1111/obr.12044. - DOI - PubMed

Publication types