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How much does the treatment of each major disease cost? A decomposition of Swiss National Health Accounts

Overview of attention for article published in HEPAC Health Economics in Prevention and Care, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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1 news outlet
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12 X users
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1 Facebook page

Citations

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43 Dimensions

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87 Mendeley
Title
How much does the treatment of each major disease cost? A decomposition of Swiss National Health Accounts
Published in
HEPAC Health Economics in Prevention and Care, February 2018
DOI 10.1007/s10198-018-0963-5
Pubmed ID
Authors

Simon Wieser, Marco Riguzzi, Mark Pletscher, Carola A. Huber, Harry Telser, Matthias Schwenkglenks

Abstract

In most countries, surprisingly little is known on how national healthcare spending is distributed across diseases. Single-disease cost-of-illness studies cover only a few of the diseases affecting a population and in some cases lead to untenably large estimates. The objective of this study was to decompose healthcare spending in 2011, according to Swiss National Health Accounts, into 21 collectively exhaustive and mutually exclusive major disease categories. Diseases were classified following the Global Burden of Disease Study. We first assigned the expenditures directly mapping from National Health Accounts to the 21 diseases. The remaining expenditures were assigned based on diagnostic codes and clues contained in a variety of microdata sources. Expenditures were dominated by non-communicable diseases with a share of 79.4%. Cardiovascular diseases stood out with 15.6% of total spending, followed by musculoskeletal disorders (13.4%), and mental and substance use disorders (10.6%). Neoplasms (6.0% of the total) ranked only sixth, although they are the leading cause of premature death in Switzerland. These results may be useful for the design of health policies, as they illustrate how healthcare spending is influenced by the epidemiological transition and increasing life expectancy. They also provide a plausibility check for single cost-of-illness studies. Our study may serve as a starting point for further research on the drivers of the constant growth of healthcare spending.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 87 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 87 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 17%
Student > Ph. D. Student 12 14%
Other 9 10%
Student > Master 6 7%
Student > Bachelor 5 6%
Other 15 17%
Unknown 25 29%
Readers by discipline Count As %
Medicine and Dentistry 17 20%
Economics, Econometrics and Finance 11 13%
Nursing and Health Professions 8 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 5%
Business, Management and Accounting 4 5%
Other 13 15%
Unknown 30 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 September 2019.
All research outputs
#2,028,357
of 25,382,440 outputs
Outputs from HEPAC Health Economics in Prevention and Care
#79
of 1,303 outputs
Outputs of similar age
#42,926
of 344,220 outputs
Outputs of similar age from HEPAC Health Economics in Prevention and Care
#2
of 19 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,303 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done particularly well, scoring higher than 93% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 344,220 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.