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Measuring intangible cost-of-morbidity due to substance dependence: implications of using alternative preference-based instruments

Author

Listed:
  • Bruno Casal

    (University of A Coruña, Campus de Elviña)

  • Eva Rodríguez-Míguez

    (University of Vigo, Campus As Lagoas-Marcosende)

  • Berta Rivera

    (University of A Coruña, Campus de Elviña)

Abstract

Objective Drug and/or alcohol dependence (DAD) generates substantial costs to society. One of the main consequences of DAD is its negative impact on health-related quality of life (HRQoL). The main objective of this study is to analyse the impact of using EQ-5D-5L, SF-6DSG (SF-6D using standard-gamble as the preference-eliciting method) and SF-6DPG (SF-6D using a paired-gamble method), to estimate the HRQoL burden, attributable to DAD, within the cost-of-illness framework. Methods A convenience sample of 109 patients with a diagnosis of substance use disorder was recruited. SF-6D and EQ-5D-5L were administered and then the utility scores were computed. The impact of employing different instruments to estimate the HRQoL burden was assessed by comparing the utility scores of patients and general population after controlling for sex and age through regression analysis. The analysis was reproduced for two subgroups of severity. Results All instruments detect that DAD significantly affects the HRQoL. However, the estimated impact changes, according to the instrument used, whose pattern varies by severity group. Nonetheless, regardless of severity, SF-6DPG always estimates a higher or equal DAD burden than the other instruments considered. These results are compatible with the presence of the floor effect in SF-6DSG, the ceiling effect in EQ-ED-5L, and a smaller presence of both biases in SF-6DPG. Conclusions The SF-6DPG instrument emerges as a good candidate to avoid under-estimating intangible costs within the cost-of-illness framework. However, further research is needed to assess the validity of our results in the context of other health problems.

Suggested Citation

  • Bruno Casal & Eva Rodríguez-Míguez & Berta Rivera, 2020. "Measuring intangible cost-of-morbidity due to substance dependence: implications of using alternative preference-based instruments," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(7), pages 1039-1048, September.
  • Handle: RePEc:spr:eujhec:v:21:y:2020:i:7:d:10.1007_s10198-020-01196-7
    DOI: 10.1007/s10198-020-01196-7
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    as
    1. Mark McCord & Richard de Neufville, 1986. ""Lottery Equivalents": Reduction of the Certainty Effect Problem in Utility Assessment," Management Science, INFORMS, vol. 32(1), pages 56-60, January.
    2. Brazier, John & Roberts, Jennifer & Deverill, Mark, 2002. "The estimation of a preference-based measure of health from the SF-36," Journal of Health Economics, Elsevier, vol. 21(2), pages 271-292, March.
    3. Peter Wakker & Daniel Deneffe, 1996. "Eliciting von Neumann-Morgenstern Utilities When Probabilities Are Distorted or Unknown," Management Science, INFORMS, vol. 42(8), pages 1131-1150, August.
    4. Jacinto Nogueira & Eva Rodríguez-Míguez, 2015. "Using the SF-6D to measure the impact of alcohol dependence on health-related quality of life," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(4), pages 347-356, May.
    5. Louise Longworth & Stirling Bryan, 2003. "An empirical comparison of EQ‐5D and SF‐6D in liver transplant patients," Health Economics, John Wiley & Sons, Ltd., vol. 12(12), pages 1061-1067, December.
    6. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    7. Muennig, P. & Lubetkin, E. & Jia, H. & Franks, P., 2006. "Gender and the burden of disease attributable to obesity," American Journal of Public Health, American Public Health Association, vol. 96(9), pages 1662-1668.
    8. Fan Yang & Titus Lau & Evan Lee & A. Vathsala & Kee Chia & Nan Luo, 2015. "Comparison of the preference-based EQ-5D-5L and SF-6D in patients with end-stage renal disease (ESRD)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(9), pages 1019-1026, December.
    9. John Brazier & Jennifer Roberts & Aki Tsuchiya & Jan Busschbach, 2004. "A comparison of the EQ‐5D and SF‐6D across seven patient groups," Health Economics, John Wiley & Sons, Ltd., vol. 13(9), pages 873-884, September.
    10. Stavros Petrou & Christine Hockley, 2005. "An investigation into the empirical validity of the EQ‐5D and SF‐6D based on hypothetical preferences in a general population," Health Economics, John Wiley & Sons, Ltd., vol. 14(11), pages 1169-1189, November.
    11. David G. T. Whitehurst & Stirling Bryan & Martyn Lewis, 2011. "Systematic Review and Empirical Comparison of Contemporaneous EQ-5D and SF-6D Group Mean Scores," Medical Decision Making, , vol. 31(6), pages 34-44, November.
    12. Petrie, Dennis & Doran, Chris & Shakeshaft, Anthony & Sanson-Fisher, Rob, 2008. "The relationship between alcohol consumption and self-reported health status using the EQ5D: Evidence from rural Australia," Social Science & Medicine, Elsevier, vol. 67(11), pages 1717-1726, December.
    13. Torrance, George W., 1976. "Social preferences for health states: An empirical evaluation of three measurement techniques," Socio-Economic Planning Sciences, Elsevier, vol. 10(3), pages 129-136.
    14. José María Abellán Perpiñán & Fernando Ignacio Sánchez Martínez & Jorge Eduardo Martínez Pérez & Ildefonso Méndez, 2012. "Lowering The ‘Floor’ Of The Sf‐6d Scoring Algorithm Using A Lottery Equivalent Method," Health Economics, John Wiley & Sons, Ltd., vol. 21(11), pages 1271-1285, November.
    15. Jeff Richardson & Munir A. Khan & Angelo Iezzi & Aimee Maxwell, 2015. "Comparing and Explaining Differences in the Magnitude, Content, and Sensitivity of Utilities Predicted by the EQ-5D, SF-6D, HUI 3, 15D, QWB, and AQoL-8D Multiattribute Utility Instruments," Medical Decision Making, , vol. 35(3), pages 276-291, April.
    16. Johan Jarl & Pia Johansson & Antonina Eriksson & Mimmi Eriksson & Ulf-G. Gerdtham & Örjan Hemström & Klara Selin & Leif Lenke & Mats Ramstedt & Robin Room, 2008. "The societal cost of alcohol consumption: an estimation of the economic and human cost including health effects in Sweden, 2002," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 9(4), pages 351-360, November.
    17. Han Bleichrodt, 2002. "A new explanation for the difference between time trade‐off utilities and standard gamble utilities," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 447-456, July.
    18. Tsuchiya, Aki & Brazier, John & Roberts, Jennifer, 2006. "Comparison of valuation methods used to generate the EQ-5D and the SF-6D value sets," Journal of Health Economics, Elsevier, vol. 25(2), pages 334-346, March.
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    1. Chris Sampson’s journal round-up for 7th September 2020
      by Chris Sampson in The Academic Health Economists' Blog on 2020-09-07 11:00:07

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    More about this item

    Keywords

    EQ-5D-5L; SF-6D; Paired-gamble; Substance dependence; Intangible cost;
    All these keywords.

    JEL classification:

    • I10 - Health, Education, and Welfare - - Health - - - General
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General

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