Expert Review of Pharmacoeconomics & Outcomes Research
ISSN: 1473-7167 (Print) 1744-8379 (Online) Journal homepage: http://www.tandfonline.com/loi/ierp20
Are healthcare expenditures increasing faster for the elderly than the rest of the population? Hans Olav Melberg To cite this article: Hans Olav Melberg (2014) Are healthcare expenditures increasing faster for the elderly than the rest of the population?, Expert Review of Pharmacoeconomics & Outcomes Research, 14:5, 581-583 To link to this article: http://dx.doi.org/10.1586/14737167.2014.919857
Published online: 16 May 2014.
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Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ierp20 Download by: [University of Wisconsin Oshkosh]
Date: 06 November 2015, At: 02:06
Editorial
Are healthcare expenditures increasing faster for the elderly than the rest of the population? Downloaded by [University of Wisconsin Oshkosh] at 02:06 06 November 2015
Expert Rev. Pharmacoecon. Outcomes Res. 14(5), 581–583 (2014)
Hans Olav Melberg Department of Health Economics and Health Management, University of Oslo, Box 1089 Blindern, 0317 Oslo, Norway Tel.: +47 2285 0550 Fax: +47 2284 5091 [email protected]
The debate about whether health expenditures will increase more or less for the old is conceptually confused because the participants focus on different factors, use different assumptions and, finally, do not connect the predictions to more general theories of demand for health services. Some focus on increases in life expectancy and how this will change the distribution of end-of-life costs. Others focus on how changes in income and technology will affect the relationship between age and health spending. Higher income, and a larger share of the population, will make it more profitable to invest in treatments aimed at old people, which will lead to steepening in some age groups, but a flattening in other age groups.
The literature on future changes in the age distribution of health expenditure is conceptually and empirically diverse. Some, like Zweifel et al., have argued that a combination of increasing life expectancy and high end-of-life cost will lead to a decrease in the average health expenditure for some age groups since the groups will contain fewer expensive patients who are close to death [1]. Once this mechanism is accounted for, predictions of future health expenditures are reduced; in some cases by as much as a third. Others, like Buchner and Wasem, have argued that ‘health care expenditure for the elderly grows faster than for younger people’ [2]. This is labeled steepening of the expenditure profile, and it is predicted that the phenomenon will lead to a sharp increase of health expenditure: Not only will we have more old people in the future, but they will also cost more per capita than today. To understand some of the issues involved it is useful to start by considering the current average health expenditure in different age groups. For instance, as age increases average hospital expenditure per capita increases slowly at first, but after the age of 50 average expenditure increases faster. As a rough rule of thumb
average spending on 60 year olds is twice as high as the spending for 40 year olds, spending on 70 year olds is four-times as high and 80 year olds have on average sixtimes higher hospital expenditures than 40 year olds. Spending then tends to peak around 80 and even decline somewhat in the older age groups. The question is how this relationship between age and health expenditure will change in the future. Some argue that the onset of diseases will move to older age groups [3], which will lead to a flattening for the age groups in the middle and a relatively steeper curve in other age groups unless the peak is also moved. Others argue that the peak will move when life expectancy increases. This will lead to a rightward shift in the expenditure curve. Finally, some argue that other factors, like income and technology, will lead to shifts, which makes the curve shift upward for all, but increasing spending among the old by a higher percentage than spending among the other groups. Making sense of the disagreements
Although the arguments seem starkly different, it is possible to make sense of the differing conclusions by engaging in conceptual clarification and empirical testing.
KEYWORDS: elderly • expenditure profile • health expenditure • red herring • steepening
informahealthcare.com
10.1586/14737167.2014.919857
Ó 2014 Informa UK Ltd
ISSN 1473-7167
581
Downloaded by [University of Wisconsin Oshkosh] at 02:06 06 November 2015
Editorial
Melberg
Empirically, the conclusions in both papers have been moderated by other studies. Zweifel’s arguments have generated a large literature attacking and defending the importance of age as a predictor of health expenditure (the ‘red herring debate’) [4,5]. The emerging consensus is that both age and time-to-death are important for healthcare expenditures [6,7]. With respect to the steepening hypothesis, Felder and Werblow have argued that the steepening effect is real, but weaker than previously believed [8]. More recently, Gregersen reported some evidence of steepening in Norwegian hospital data [9], but it was not as strong as indicated by Buchner and Wasem. It should be noted that the strength of the empirical conclusions also depends on whether the definition of health expenditure includes long-term nursing care. When it is included as a health expense, age becomes more important as a predictor of health spending. Altogether this means that although the theories produce different empirical predictions, the difference is not as large as one may initially believe. Conceptually, the authors concentrate on different factors affecting the age-related health expenditure profile and for this reason one should not expect the same conclusions. Zweifel et al. focus on the endogenous change that occurs when life expectancy increases. As life expectancy increases, fewer deaths in an age group imply reduced average costs in that age group when all other factors are held constant. But for Buchner and Wasem, all other things are not assumed constant. For instance, one mechanism affecting the health expenditure profile is technological innovations [10]. When the share of old people in the population increases, the economic incentive to focus on technological innovations for this group also increases. The result is that the average health expenditure per capita for old people may increase even more than for other groups. However, this conclusion is based on including factors – technological change – that were intentionally outside the scope of Zweifel’s model. Technological change is only one of several such variables that could change the age-related expenditure curve. Others include changes in education, changes in family size and cultural changes. One particularly important factor that changes over time is income. Increasing income will shift the expenditure profile upward. In itself this is not steepening as long as the shift is equally large in all age groups, but as shown in the next section there is good reason to suspect that this is not the case.
demand for health services as a response to episodes of illness that become increasingly frequent as age increases. Distinguishing between the two theories of the demand for health is important because they result in different predictions about whether health expenditures will raise more among the elderly than the young. If the precautionary motive emphasized by Grossman is most important, future higher income should lead to an increase in average health spending for young people as well as the old. In this model, higher income increases the reward to work relative to leisure and it becomes even more profitable for the young to stay healthy to be able to work. If Zweifel’s theory is more accurate, an increase in income and a larger health budget will mainly be allocated to improve treatment for those in bad health. Additionally, it can lower the threshold for when to provide health services. These two outcomes will result in a disproportionately higher spending for older people because larger shares of those who are sick are old. These age groups also have a larger share of people on the borderline of needing treatment. This means that based on Zweifel’s theory of the demand for health services, higher income will lead health expenditures to increase faster for the elderly than the rest of the population. The conclusion is that different theories of demand for health have different implications for how income will affect the age distribution of health spending. Old is the new young
In order to test the theories of demand for health, it is useful to examine differences in the age distribution of health spending in similar countries with different life expectancies. For instance, data on health expenditure from Norway and Denmark indicate that a 1-year increase in life expectancy tends to shift the average cost curve by 1 year: future 70 year olds will be more like today’s 79 year olds [13]. This suggests that the whole spending curve shifts as life expectancy increases. In itself the shift should lead to a reduction in health expenses in many previously old age groups. At the same time higher life expectancy is often correlated with higher income. As long as the higher income is spent mainly on those who are sick, this will cause some steepening. In this sense, there is both flattening due to reduced mortality in some groups and steepening in other age groups with the largest share of people who are sick or close to being sick due to increased spending on these groups as income increases.
Different theories, different predictions
One important background for predictions of the age distribution of health expenditure is the theoretical connection to the theory of the demand for health services. In the standard Grossman model, health services are partly demanded as a preventive investment to reduce the risk of bad health [11]. In this model, higher income would lead to higher health expenditures for the young and the old. An alternative view is presented by Zweifel [12]. Instead of viewing health expenditures as mainly driven by forward looking investment motives, he models
582
Financial & competing interests disclosure
The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties. No writing assistance was utilized in the production of this manuscript.
Expert Rev. Pharmacoecon. Outcomes Res. 14(5), (2014)
Are healthcare expenditures increasing faster for the elderly than the rest of the population?
2.
3.
Downloaded by [University of Wisconsin Oshkosh] at 02:06 06 November 2015
4.
5.
Zweifel P, Felder S, Meiers M. Ageing of population and health care expenditure: a red herring? Health Econ 1999;8(6): 485-96 Buchner F, Wasem J. “Steeping” of health expenditure profiles. Geneva Papers on Risk and Insurance-Issues and Practice 2006; 31(4):581-99 Fries JF. Aging, natural death, and the compression of morbidity. Bull World Health Organ 2002;80(3):245-50 Karlsson M, Klohn F. Testing the red herring hypothesis on an aggregated level: ageing, time-to-death and care costs for older people in Sweden. Eur J Health Econ 2013. [Epub ahead of print] Wong A, van Baal PH, Boshuizen HC, Polder JJ. Exploring the influence of
informahealthcare.com
steepening. Eur J Health Econ 2013. [Epub ahead of print]
proximity to death on disease-specific hospital expenditures: a carpaccio of red herrings. Health Econ 2011;20(4):379-400
10.
6.
Stearns SC, Norton EC. Time to include time to death? The future of health care expenditure predictions. Health Econ 2004; 13(4):315-27
Ried W. Medical progress and age-specific expenditure on health care. Jahrbucher Fur Nationalokonomie Und Statistik. 2007; 227(5-6):636-59
11.
7.
Ha¨kkinen U, Martikainen P, Noro A, et al. Aging, health expenditure, proximity to death, and income in Finland. Health Econ Policy Law 2008;3(Pt 2):165-95
Grossman M. The demand for health, 30 years later: a very personal retrospective and prospective reflection. J Health Econ 2004;23(4):629-36
12.
8.
Felder S, Werblow A. Does the age profile of health care expenditure really steepen over time? New evidence from Swiss Cantons. Geneva Risk Ins Rev 2008;33(4): 710-27
Zweifel P. The Grossman model after 40 years. Eur J Health Econ 2012;13(6): 677-82
13.
Melberg HO, Sørensen J. How does end of life costs and increases in life expectancy affect projections of future hospital spending? in HERO On line Working Paper Oslo University, Oslo, Norway; 2013
References 1.
Editorial
9.
Gregersen FA. The impact of ageing on health care expenditures: a study of
583
ISSN: 1473-7167 (Print) 1744-8379 (Online) Journal homepage: http://www.tandfonline.com/loi/ierp20
Are healthcare expenditures increasing faster for the elderly than the rest of the population? Hans Olav Melberg To cite this article: Hans Olav Melberg (2014) Are healthcare expenditures increasing faster for the elderly than the rest of the population?, Expert Review of Pharmacoeconomics & Outcomes Research, 14:5, 581-583 To link to this article: http://dx.doi.org/10.1586/14737167.2014.919857
Published online: 16 May 2014.
Submit your article to this journal
Article views: 154
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=ierp20 Download by: [University of Wisconsin Oshkosh]
Date: 06 November 2015, At: 02:06
Editorial
Are healthcare expenditures increasing faster for the elderly than the rest of the population? Downloaded by [University of Wisconsin Oshkosh] at 02:06 06 November 2015
Expert Rev. Pharmacoecon. Outcomes Res. 14(5), 581–583 (2014)
Hans Olav Melberg Department of Health Economics and Health Management, University of Oslo, Box 1089 Blindern, 0317 Oslo, Norway Tel.: +47 2285 0550 Fax: +47 2284 5091 [email protected]
The debate about whether health expenditures will increase more or less for the old is conceptually confused because the participants focus on different factors, use different assumptions and, finally, do not connect the predictions to more general theories of demand for health services. Some focus on increases in life expectancy and how this will change the distribution of end-of-life costs. Others focus on how changes in income and technology will affect the relationship between age and health spending. Higher income, and a larger share of the population, will make it more profitable to invest in treatments aimed at old people, which will lead to steepening in some age groups, but a flattening in other age groups.
The literature on future changes in the age distribution of health expenditure is conceptually and empirically diverse. Some, like Zweifel et al., have argued that a combination of increasing life expectancy and high end-of-life cost will lead to a decrease in the average health expenditure for some age groups since the groups will contain fewer expensive patients who are close to death [1]. Once this mechanism is accounted for, predictions of future health expenditures are reduced; in some cases by as much as a third. Others, like Buchner and Wasem, have argued that ‘health care expenditure for the elderly grows faster than for younger people’ [2]. This is labeled steepening of the expenditure profile, and it is predicted that the phenomenon will lead to a sharp increase of health expenditure: Not only will we have more old people in the future, but they will also cost more per capita than today. To understand some of the issues involved it is useful to start by considering the current average health expenditure in different age groups. For instance, as age increases average hospital expenditure per capita increases slowly at first, but after the age of 50 average expenditure increases faster. As a rough rule of thumb
average spending on 60 year olds is twice as high as the spending for 40 year olds, spending on 70 year olds is four-times as high and 80 year olds have on average sixtimes higher hospital expenditures than 40 year olds. Spending then tends to peak around 80 and even decline somewhat in the older age groups. The question is how this relationship between age and health expenditure will change in the future. Some argue that the onset of diseases will move to older age groups [3], which will lead to a flattening for the age groups in the middle and a relatively steeper curve in other age groups unless the peak is also moved. Others argue that the peak will move when life expectancy increases. This will lead to a rightward shift in the expenditure curve. Finally, some argue that other factors, like income and technology, will lead to shifts, which makes the curve shift upward for all, but increasing spending among the old by a higher percentage than spending among the other groups. Making sense of the disagreements
Although the arguments seem starkly different, it is possible to make sense of the differing conclusions by engaging in conceptual clarification and empirical testing.
KEYWORDS: elderly • expenditure profile • health expenditure • red herring • steepening
informahealthcare.com
10.1586/14737167.2014.919857
Ó 2014 Informa UK Ltd
ISSN 1473-7167
581
Downloaded by [University of Wisconsin Oshkosh] at 02:06 06 November 2015
Editorial
Melberg
Empirically, the conclusions in both papers have been moderated by other studies. Zweifel’s arguments have generated a large literature attacking and defending the importance of age as a predictor of health expenditure (the ‘red herring debate’) [4,5]. The emerging consensus is that both age and time-to-death are important for healthcare expenditures [6,7]. With respect to the steepening hypothesis, Felder and Werblow have argued that the steepening effect is real, but weaker than previously believed [8]. More recently, Gregersen reported some evidence of steepening in Norwegian hospital data [9], but it was not as strong as indicated by Buchner and Wasem. It should be noted that the strength of the empirical conclusions also depends on whether the definition of health expenditure includes long-term nursing care. When it is included as a health expense, age becomes more important as a predictor of health spending. Altogether this means that although the theories produce different empirical predictions, the difference is not as large as one may initially believe. Conceptually, the authors concentrate on different factors affecting the age-related health expenditure profile and for this reason one should not expect the same conclusions. Zweifel et al. focus on the endogenous change that occurs when life expectancy increases. As life expectancy increases, fewer deaths in an age group imply reduced average costs in that age group when all other factors are held constant. But for Buchner and Wasem, all other things are not assumed constant. For instance, one mechanism affecting the health expenditure profile is technological innovations [10]. When the share of old people in the population increases, the economic incentive to focus on technological innovations for this group also increases. The result is that the average health expenditure per capita for old people may increase even more than for other groups. However, this conclusion is based on including factors – technological change – that were intentionally outside the scope of Zweifel’s model. Technological change is only one of several such variables that could change the age-related expenditure curve. Others include changes in education, changes in family size and cultural changes. One particularly important factor that changes over time is income. Increasing income will shift the expenditure profile upward. In itself this is not steepening as long as the shift is equally large in all age groups, but as shown in the next section there is good reason to suspect that this is not the case.
demand for health services as a response to episodes of illness that become increasingly frequent as age increases. Distinguishing between the two theories of the demand for health is important because they result in different predictions about whether health expenditures will raise more among the elderly than the young. If the precautionary motive emphasized by Grossman is most important, future higher income should lead to an increase in average health spending for young people as well as the old. In this model, higher income increases the reward to work relative to leisure and it becomes even more profitable for the young to stay healthy to be able to work. If Zweifel’s theory is more accurate, an increase in income and a larger health budget will mainly be allocated to improve treatment for those in bad health. Additionally, it can lower the threshold for when to provide health services. These two outcomes will result in a disproportionately higher spending for older people because larger shares of those who are sick are old. These age groups also have a larger share of people on the borderline of needing treatment. This means that based on Zweifel’s theory of the demand for health services, higher income will lead health expenditures to increase faster for the elderly than the rest of the population. The conclusion is that different theories of demand for health have different implications for how income will affect the age distribution of health spending. Old is the new young
In order to test the theories of demand for health, it is useful to examine differences in the age distribution of health spending in similar countries with different life expectancies. For instance, data on health expenditure from Norway and Denmark indicate that a 1-year increase in life expectancy tends to shift the average cost curve by 1 year: future 70 year olds will be more like today’s 79 year olds [13]. This suggests that the whole spending curve shifts as life expectancy increases. In itself the shift should lead to a reduction in health expenses in many previously old age groups. At the same time higher life expectancy is often correlated with higher income. As long as the higher income is spent mainly on those who are sick, this will cause some steepening. In this sense, there is both flattening due to reduced mortality in some groups and steepening in other age groups with the largest share of people who are sick or close to being sick due to increased spending on these groups as income increases.
Different theories, different predictions
One important background for predictions of the age distribution of health expenditure is the theoretical connection to the theory of the demand for health services. In the standard Grossman model, health services are partly demanded as a preventive investment to reduce the risk of bad health [11]. In this model, higher income would lead to higher health expenditures for the young and the old. An alternative view is presented by Zweifel [12]. Instead of viewing health expenditures as mainly driven by forward looking investment motives, he models
582
Financial & competing interests disclosure
The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending or royalties. No writing assistance was utilized in the production of this manuscript.
Expert Rev. Pharmacoecon. Outcomes Res. 14(5), (2014)
Are healthcare expenditures increasing faster for the elderly than the rest of the population?
2.
3.
Downloaded by [University of Wisconsin Oshkosh] at 02:06 06 November 2015
4.
5.
Zweifel P, Felder S, Meiers M. Ageing of population and health care expenditure: a red herring? Health Econ 1999;8(6): 485-96 Buchner F, Wasem J. “Steeping” of health expenditure profiles. Geneva Papers on Risk and Insurance-Issues and Practice 2006; 31(4):581-99 Fries JF. Aging, natural death, and the compression of morbidity. Bull World Health Organ 2002;80(3):245-50 Karlsson M, Klohn F. Testing the red herring hypothesis on an aggregated level: ageing, time-to-death and care costs for older people in Sweden. Eur J Health Econ 2013. [Epub ahead of print] Wong A, van Baal PH, Boshuizen HC, Polder JJ. Exploring the influence of
informahealthcare.com
steepening. Eur J Health Econ 2013. [Epub ahead of print]
proximity to death on disease-specific hospital expenditures: a carpaccio of red herrings. Health Econ 2011;20(4):379-400
10.
6.
Stearns SC, Norton EC. Time to include time to death? The future of health care expenditure predictions. Health Econ 2004; 13(4):315-27
Ried W. Medical progress and age-specific expenditure on health care. Jahrbucher Fur Nationalokonomie Und Statistik. 2007; 227(5-6):636-59
11.
7.
Ha¨kkinen U, Martikainen P, Noro A, et al. Aging, health expenditure, proximity to death, and income in Finland. Health Econ Policy Law 2008;3(Pt 2):165-95
Grossman M. The demand for health, 30 years later: a very personal retrospective and prospective reflection. J Health Econ 2004;23(4):629-36
12.
8.
Felder S, Werblow A. Does the age profile of health care expenditure really steepen over time? New evidence from Swiss Cantons. Geneva Risk Ins Rev 2008;33(4): 710-27
Zweifel P. The Grossman model after 40 years. Eur J Health Econ 2012;13(6): 677-82
13.
Melberg HO, Sørensen J. How does end of life costs and increases in life expectancy affect projections of future hospital spending? in HERO On line Working Paper Oslo University, Oslo, Norway; 2013
References 1.
Editorial
9.
Gregersen FA. The impact of ageing on health care expenditures: a study of
583
