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Published in: The European Journal of Health Economics 5/2019

Open Access 01-07-2019 | Original Paper

Estimating the marginal cost of a life year in Sweden’s public healthcare sector

Authors: Jonathan Siverskog, Martin Henriksson

Published in: The European Journal of Health Economics | Issue 5/2019

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Abstract

Although cost-effectiveness analysis has a long tradition of supporting healthcare decision-making in Sweden, there are no clear criteria for when an intervention is considered too expensive. In particular, the opportunity cost of healthcare resource use in terms of health forgone has not been investigated empirically. In this work, we therefore seek to estimate the marginal cost of a life year in Sweden’s public healthcare sector using time series and panel data at the national and regional levels, respectively. We find that estimation using time series is unfeasible due to reversed causality. However, through panel instrumental variable estimation we are able to derive a marginal cost per life year of about SEK 370,000 (EUR 39,000). Although this estimate is in line with emerging evidence from other healthcare systems, it is associated with uncertainty, primarily due to the inherent difficulties of causal inference using aggregate observational data. The implications of these difficulties and related methodological issues are discussed.
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Footnotes
1
In 2016, total revenue from patient fees amounted to SEK 6.3 billion [14], covering 2.3% of total regional healthcare expenditure.
 
2
The council of Gotland, which has special status as both a region and a local municipality, is excluded due to limited data availability. Because of data availability issues for other variables, the panel data analysis is restricted to the period 2003–2015 (N = 20, T = 13).
 
3
We do not wish argue that life expectancy (mortality) depends exclusively on morbidity, but we believe that most of the effect of other variables (including expenditure) is working through it. Any potential direct links with life expectancy are accounted for by our empirical specification, although not included in our conceptual model.
 
4
This variable could act as an instrument for mean age, but since this is not the causal effect of interest to the study, we use it directly as a control, so as not to confound the main results or introduce unnecessary endogenous regressors.
 
5
If the effect of expenditure is heterogeneous across ages, then discounting could of course turn out to be important in an analysis of age-specific mortality rates, by, e.g. tilting health gains towards the future.
 
6
Earlier conference presentations of this work used different measures of mortality and expenditure where cointegration was present; the Granger causality results, however, similarly indicated unidirectional causality from mortality to expenditure.
 
7
At the average exchange rate in 2016, EURSEK = 9.4689, from the European Central Bank.
 
8
New interventions would not have to displace existing personnel, but simply reduce the rate at which new staff is hired.
 
Literature
1.
go back to reference Brouwer, W., van Baal, P., van Exel, J., Versteegh, M.: When is it too expensive? Cost-effectiveness thresholds and health care decision-making. Eur. J. Health Econ. (2018) Brouwer, W., van Baal, P., van Exel, J., Versteegh, M.: When is it too expensive? Cost-effectiveness thresholds and health care decision-making. Eur. J. Health Econ. (2018)
2.
go back to reference Claxton, K., Walker, S., Palmer, S., Schulpher, M.: Appropriate perspectives for health care decisions. CHE Research Paper 54. Center for Health Economics, University of York (2010) Claxton, K., Walker, S., Palmer, S., Schulpher, M.: Appropriate perspectives for health care decisions. CHE Research Paper 54. Center for Health Economics, University of York (2010)
3.
go back to reference Claxton, K., Martin, S., Soares, M., Rice, N., Spackman, E., Hinde, S., Devlin, N., Smith, P.C., Sculpher, M.: Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold. Health Technol. Asses. 19(14), 1–503 (2015)CrossRef Claxton, K., Martin, S., Soares, M., Rice, N., Spackman, E., Hinde, S., Devlin, N., Smith, P.C., Sculpher, M.: Methods for the estimation of the National Institute for Health and Care Excellence cost-effectiveness threshold. Health Technol. Asses. 19(14), 1–503 (2015)CrossRef
4.
go back to reference Edney, L.C., Afzali, H.H.A., Cheng, T.C., Karnon, J.: Estimating the reference incremental cost-effectiveness ratio for the Australian Health System. Pharmacoeconomics 36(2), 239–252 (2018)CrossRefPubMed Edney, L.C., Afzali, H.H.A., Cheng, T.C., Karnon, J.: Estimating the reference incremental cost-effectiveness ratio for the Australian Health System. Pharmacoeconomics 36(2), 239–252 (2018)CrossRefPubMed
5.
go back to reference Vallejo-Torres, L., Garcia-Lorenzo, B., Serrano-Aguilar, P.: Estimating a cost-effectiveness threshold for the Spanish NHS. Health Econ. 27(4), 746–761 (2018)CrossRefPubMed Vallejo-Torres, L., Garcia-Lorenzo, B., Serrano-Aguilar, P.: Estimating a cost-effectiveness threshold for the Spanish NHS. Health Econ. 27(4), 746–761 (2018)CrossRefPubMed
6.
go back to reference Nolte, E., McKee, M.: Does health care save lives? Avoidable mortality revisited. The Nuffield Trust, London (2004) Nolte, E., McKee, M.: Does health care save lives? Avoidable mortality revisited. The Nuffield Trust, London (2004)
7.
go back to reference Gallet, C.A., Doucouliagos, H.: The impact of healthcare spending on health outcomes: a meta-regression analysis. Soc. Sci. Med. 179, 9–17 (2017)CrossRefPubMed Gallet, C.A., Doucouliagos, H.: The impact of healthcare spending on health outcomes: a meta-regression analysis. Soc. Sci. Med. 179, 9–17 (2017)CrossRefPubMed
8.
go back to reference Gravelle, H.S.E., Backhouse, M.E.: International cross-section analysis of the determination of mortality. Soc. Sci. Med. 25(5), 427–441 (1987)CrossRefPubMed Gravelle, H.S.E., Backhouse, M.E.: International cross-section analysis of the determination of mortality. Soc. Sci. Med. 25(5), 427–441 (1987)CrossRefPubMed
9.
go back to reference Lichtenberg, F.R.: Sources of US longevity increases, 1960–2001. Q. Rev. Econ. Finance 44(3), 369–389 (2004)CrossRef Lichtenberg, F.R.: Sources of US longevity increases, 1960–2001. Q. Rev. Econ. Finance 44(3), 369–389 (2004)CrossRef
10.
go back to reference Martin, S., Rice, N., Smith, P.C.: Does health care spending improve health outcomes? Evidence from English programme budgeting data. J. Health Econ. 27(4), 826–842 (2008)CrossRefPubMed Martin, S., Rice, N., Smith, P.C.: Does health care spending improve health outcomes? Evidence from English programme budgeting data. J. Health Econ. 27(4), 826–842 (2008)CrossRefPubMed
11.
go back to reference Martin, S., Rice, N., Smith, P.C.: Comparing costs and outcomes across programmes of health care. Health Econ. 21(3), 316–337 (2012)CrossRefPubMed Martin, S., Rice, N., Smith, P.C.: Comparing costs and outcomes across programmes of health care. Health Econ. 21(3), 316–337 (2012)CrossRefPubMed
12.
go back to reference Claxton, K., Lomas, J., Martin, S.: The impact of NHS expenditure on health outcomes in England: alternative approaches to identification in all-cause and disease specific models of mortality. Health Econ. 27(6), 1017–1023 (2018)CrossRefPubMed Claxton, K., Lomas, J., Martin, S.: The impact of NHS expenditure on health outcomes in England: alternative approaches to identification in all-cause and disease specific models of mortality. Health Econ. 27(6), 1017–1023 (2018)CrossRefPubMed
13.
go back to reference Andrews, M., Elamin, O., Hall, A.R., Kyriakoulis, K., Sutton, M.: Inference in the presence of redundant moment conditions and the impact of government health expenditure on health outcomes in England. Economet. Rev. 36(1–3), 23–41 (2017)CrossRef Andrews, M., Elamin, O., Hall, A.R., Kyriakoulis, K., Sutton, M.: Inference in the presence of redundant moment conditions and the impact of government health expenditure on health outcomes in England. Economet. Rev. 36(1–3), 23–41 (2017)CrossRef
15.
go back to reference OECD: A system of health accounts: version 1.0. OECD Publication Service, Paris (2000) OECD: A system of health accounts: version 1.0. OECD Publication Service, Paris (2000)
17.
go back to reference OECD, Eurostat, WHO: A system of health accounts 2011: revised edition. OECD Publishing, Paris (2017)CrossRef OECD, Eurostat, WHO: A system of health accounts 2011: revised edition. OECD Publishing, Paris (2017)CrossRef
19.
go back to reference Granger, C.W.J.: Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37(3), 424–438 (1969)CrossRef Granger, C.W.J.: Investigating causal relations by econometric models and cross-spectral methods. Econometrica 37(3), 424–438 (1969)CrossRef
20.
go back to reference Toda, H.Y., Yamamoto, T.: Statistical-inference in vector autoregressions with possibly integrated processes. J Econometrics 66(1–2), 225–250 (1995)CrossRef Toda, H.Y., Yamamoto, T.: Statistical-inference in vector autoregressions with possibly integrated processes. J Econometrics 66(1–2), 225–250 (1995)CrossRef
21.
go back to reference Johansen, S.: Estimation and hypothesis-testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59(6), 1551–1580 (1991)CrossRef Johansen, S.: Estimation and hypothesis-testing of cointegration vectors in Gaussian vector autoregressive models. Econometrica 59(6), 1551–1580 (1991)CrossRef
22.
go back to reference The Swedish Agency for Public Management: Det kommunala utjämningssystemet - en beskrivning av systemet från 2014 (2014:2). Statskontoret, Stockholm (2014) The Swedish Agency for Public Management: Det kommunala utjämningssystemet - en beskrivning av systemet från 2014 (2014:2). Statskontoret, Stockholm (2014)
23.
go back to reference The Swedish Agency for Public Management: Den kommunala utjämningen sedan mitten av 1990-talet - utveckling, funktionssätt och problemområden (2013:19). Statskontoret, Stockholm (2013) The Swedish Agency for Public Management: Den kommunala utjämningen sedan mitten av 1990-talet - utveckling, funktionssätt och problemområden (2013:19). Statskontoret, Stockholm (2013)
24.
go back to reference Statistics Sweden: Life expectancy in Sweden 2001–2010. Life tables for the country and by county. In: Demographic reports (2011:2). SCB-tryck, Örebro (2011) Statistics Sweden: Life expectancy in Sweden 2001–2010. Life tables for the country and by county. In: Demographic reports (2011:2). SCB-tryck, Örebro (2011)
25.
go back to reference Steiger, D., Stock, J.H.: Instrumental variables regression with weak instruments. Econometrica 65(3), 557–586 (1997)CrossRef Steiger, D., Stock, J.H.: Instrumental variables regression with weak instruments. Econometrica 65(3), 557–586 (1997)CrossRef
26.
go back to reference Stock, J.H., Yogo, M.: Testing for weak instruments in linear IV regression. In: Andrews, D.W.K., Stock, J.H. (eds.) Identification and inference for econometric models: essays in honor of Thomas Rothenberg, pp. 80–108. Cambridge University Press, New York (2005)CrossRef Stock, J.H., Yogo, M.: Testing for weak instruments in linear IV regression. In: Andrews, D.W.K., Stock, J.H. (eds.) Identification and inference for econometric models: essays in honor of Thomas Rothenberg, pp. 80–108. Cambridge University Press, New York (2005)CrossRef
27.
go back to reference Driscoll, J.C., Cray, A.C.: Consistent covariance matrix estimation with spatially dependent panel data. Rev. Econ. Stat. 80(4), 549–560 (1998)CrossRef Driscoll, J.C., Cray, A.C.: Consistent covariance matrix estimation with spatially dependent panel data. Rev. Econ. Stat. 80(4), 549–560 (1998)CrossRef
28.
go back to reference MacKinnon, J.G., White, H.: Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. J. Econometrics. 29(3), 305–325 (1985)CrossRef MacKinnon, J.G., White, H.: Some heteroskedasticity-consistent covariance matrix estimators with improved finite sample properties. J. Econometrics. 29(3), 305–325 (1985)CrossRef
29.
go back to reference Croissant, Y., Millo, G.: Panel data econometrics in R: the plm package. J. Stat. Softw. 27(2), 1–43 (2008)CrossRef Croissant, Y., Millo, G.: Panel data econometrics in R: the plm package. J. Stat. Softw. 27(2), 1–43 (2008)CrossRef
30.
go back to reference Kleiber, C., Zeileis, A.: Applied econometrics with R. Springer-Verlag, New York (2008)CrossRef Kleiber, C., Zeileis, A.: Applied econometrics with R. Springer-Verlag, New York (2008)CrossRef
31.
go back to reference Millo, G.: Robust standard error estimators for panel models: a unifying approach. J. Stat. Softw. 82(3), 1–27 (2017)CrossRef Millo, G.: Robust standard error estimators for panel models: a unifying approach. J. Stat. Softw. 82(3), 1–27 (2017)CrossRef
32.
go back to reference Burström, K., Sun, S., Gerdtham, U.G., Henriksson, M., Johannesson, M., Levin, L.A., Zethraeus, N.: Swedish experience-based value sets for EQ-5D health states. Qual. Life Res. 23(2), 431–442 (2014)CrossRefPubMed Burström, K., Sun, S., Gerdtham, U.G., Henriksson, M., Johannesson, M., Levin, L.A., Zethraeus, N.: Swedish experience-based value sets for EQ-5D health states. Qual. Life Res. 23(2), 431–442 (2014)CrossRefPubMed
33.
go back to reference Small, D.S.: Sensitivity analysis for instrumental variables regression with overidentifying restrictions. J. Am. Stat. Assoc. 102(479), 1049–1058 (2007)CrossRef Small, D.S.: Sensitivity analysis for instrumental variables regression with overidentifying restrictions. J. Am. Stat. Assoc. 102(479), 1049–1058 (2007)CrossRef
34.
go back to reference Hall, A.R., Rudebusch, G.D., Wilcox, D.W.: Judging instrument relevance in instrumental variables estimation. Int. Econ. Rev. 37(2), 283–298 (1996)CrossRef Hall, A.R., Rudebusch, G.D., Wilcox, D.W.: Judging instrument relevance in instrumental variables estimation. Int. Econ. Rev. 37(2), 283–298 (1996)CrossRef
35.
go back to reference Chen, T.C., Wanniarachige, D., Murphy, S., Lockhart, K., O’Mahony, J.: Surveying the cost-effectiveness of the 20 procedures with the largest public health services waiting lists in Ireland: implications for ireland’s cost-effectiveness threshold. Value Health 21(8), 897–904 (2018)CrossRefPubMed Chen, T.C., Wanniarachige, D., Murphy, S., Lockhart, K., O’Mahony, J.: Surveying the cost-effectiveness of the 20 procedures with the largest public health services waiting lists in Ireland: implications for ireland’s cost-effectiveness threshold. Value Health 21(8), 897–904 (2018)CrossRefPubMed
Metadata
Title
Estimating the marginal cost of a life year in Sweden’s public healthcare sector
Authors
Jonathan Siverskog
Martin Henriksson
Publication date
01-07-2019
Publisher
Springer Berlin Heidelberg
Published in
The European Journal of Health Economics / Issue 5/2019
Print ISSN: 1618-7598
Electronic ISSN: 1618-7601
DOI
https://doi.org/10.1007/s10198-019-01039-0

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