A Comparison of Disability Weights for Alcohol Use Disorders

Authors

  • Jiraluck Nontarak Health Systems Research Institute, Mueang, Nonthaburi 11000, Thailand. and 2Department of Epidemiology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand.
  • Jiraluck Nontarak Health Systems Research Institute, Mueang, Nonthaburi 11000, Thailand. and 2Department of Epidemiology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand.
  • Jiraluck Nontarak Health Systems Research Institute, Mueang, Nonthaburi 11000, Thailand. and Department of Epidemiology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand.
  • Sawitri Assanangkornchai Department of Epidemiology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla 90110, Thailand.
  • Sarah Callinan Centre for Alcohol Policy Research, Latrobe University, Victoria 3083, Australia.

DOI:

https://doi.org/10.31584/jhsmr.2020759

Keywords:

alcohol-use disorders, disability weight, EQ-5D, time trade-off, visual analogue scale

Abstract

Objective: This study aims to determine and compare the disability weights of alcohol use disorders (AUD) based on responses from AUD patients and a non-patient population using three valuation methods.
Material and Methods: Cross-sectional data were collected from three hospitals in southern Thailand. Two groups of participants were recruited: 150 patients diagnosed with AUD and a control group containing 150 persons without AUD. Both groups were asked to rate the AUD health states using a visual analogue scale (VAS), and again using either the European Quality of Life-5 Dimension (EQ-5D) instrument or the time trade-off (TTO) technique. Data were collected via face-to-face interviews.
Results: The mean disability weights, based on the VAS, TTO and EQ-5D valuation methods obtained from AUD patients were: 0.485, 0.405, and 0.311, respectively, while those obtained from the control group were: 0.541, 0.330, and 0.237, respectively. Disability weights had a positive correlation with AUD severity levels. Employment status and family income were significantly associated with VAS disability weight among the control group.
Conclusion: The use of three different instruments to calculate disability weights for people with AUD is feasible in Thailand. The disability weights differ depending on the valuation methods used and respondent groups.

References

Griswold MG, Fullman N, Hawley C, Arian N, Zimsen SRM, Tymeson HD, et al. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet 2018;392: 1015–35.

Burden of diseases Thailand study group. Burden of diseases and Injuries of Thailand 2015. Nonthaburi: International Health Policy Program; 2017.

Burden of diseases Thailand study group. Thailand burden of diseases attributable to risk factors 2014. Nonthaburi: International Health Policy Program; 2018.

Salomon JA, Haagsma JA, Davis A, de Noordhout CM, Polinder S, Havelaar AH, et al. Disability weights for the Global Burden of Disease 2013 study. Lancet Glob Health 2017;3: e712–23.

Torrance GW. Utility approach to measuring health-related quality of life. J Chronic Dis 1987;40:593–603.

Dolan P, Gudex C, Kind P, Williams A. The time trade-off method: results from a general population study. Health Econ 1996;5:141–54.

Nord E. The person-trade-off approach to valuing health care programs. Med Decis Making 1995;15:201–8.

Maheswaran H, Petrou S, Rees K, Stranges S. Estimating EQ-5D utility values for major health behavioural risk factors in England. J Epidemiol Community Health 2013;67:172–80.

Chavez LJ, Bradley K, Tefft N, Liu CF, Hebert P, Devine B. Preference weights for the spectrum of alcohol use in the U.S. Population. Drug Alcohol Depend 2016;161:206–13.

Günther O, Roick C, Angermeyer MC, König HH. The EQ-5D in alcohol dependent patients: relationships among healthrelated quality of life, psychopathology and social functioning. Drug Alcohol Depend 2007;86:253–64.

Dolan P, Sutton M. Mapping visual analogue scale health state valuations onto standard gamble and time trade-off values. Soc Sci Med 1997;44:1519–30.

Rehm J, Frick U. Establishing disability weights from pairwise comparisons for a US burden of disease study. Int J Methods Psychiatr Res 2013;22:144–54.

Haagsma JA, Maertens de Noordhout C, Polinder S, Vos T, Havelaar AH, Cassini A, et al. Assessing disability weights based on the responses of 30,660 people from four European countries. Popul Health Metr 2015;13:10.

Ock M, Lee JY, Oh IH, Park H, Yoon SJ, Jo MW. Disability Weights Measurement for 228 Causes of Disease in the Korean Burden of Disease Study 2012. J Korean Med Sci 2016; 31(Suppl 2):S129–38.

Bundhamcharoen K, Odton P, Phulkerd S, Tangcharoensathien V. Burden of disease in Thailand: changes in health gap between 1999 and 2004. BMC Public Health 2011;11:53.

Burden of diseases Thailand study group. Thai disability weight 2009. Nonthaburi: International Health Policy Program; 2016.

Babor TF, Higgins-Biddle JC, Saunders JB, Monteiro MG. The alcohol use disorders identification test: guidelines for use in primary care. 2nd ed. Geneva: WHO; 2014.

Craig BM, Oppe M. From a different angle: a novel approach to health valuation. Soc Sci Med 2010;70:169–74.

Pattanaphesaj J, Thavorncharoensap M, Ramos-Goñi JM, Tongsiri S, Ingsrisawang L, Teerawattananon Y. The EQ-5D-5L Valuation study in Thailand. Expert Rev Pharmacoecon Outcomes Res 2018;18:551–8.

Ock M, Ahn J, Yoon SJ, Jo MW. Estimation of disability weights in the general population of South Korea using a paired comparison. PLOS ONE 2016;11. doi: 10.1371/journal. pone.0162478

Arnesen TM, Norheim OF. Quantifying quality of life for economic analysis: time out for time tradeoff. Med Humanit 2003;29: 81–6.

Arnesen T, Nord E. The value of DALY life: problems with ethics and validity of disability adjusted life years. BMJ 1999;319: 1423–5.

Lundberg L, Johannesson M, Isacson DGL, Borgquist L. Healthstate utilities in a general population in relation to age, gender and socioeconomic factors. Eur J Public Health 1999;9:211–7.

Dolan P, Roberts J. To what extent can we explain time trade-off values from other information about respondents? Soc Sci Med 2002;54:919–29.

Haagsma JA, Polinder S, Cassini A, Colzani E, Havelaar AH. Review of disability weight studies: comparison of methodological choices and values. Popul Health Metr 2014;12:20.

Ock M, Park B, Park H, Oh IH, Yoon SJ, Cho B, et al. Disability weights measurement for 289 causes of disease considering disease severity in Korea. J Korean Med Sci 2019;34(Suppl 1). doi: 10.3346/jkms.2019.34.e60.

Ock M, Ko S, Lee HJ, Jo MW. Review of issues for disability weight studies. Health Policy Manag 2016;26:352.

Crisp AH, Gelder MG, Rix S, Meltzer HI, Rowlands OJ. Stigmatisation of people with mental illnesses. Br J Psychiatry 2000;177:4–7.

Keyes KM, Hatzenbuehler ML, McLaughlin KA, Link B, Olfson M, Grant BF, et al. Stigma and treatment for alcohol disorders in the United States. Am J Epidemiol 2010;172:1364–72.

Badia X, Monserrat S, Roset M, Herdman M. Feasibility, validity and test-retest reliability of scaling methods for health states: the visual analogue scale and the time tradeoff. Qual Life Res 1999;8:303–10.

Jelsma J, Ferguson G. The determinants of self-reported health-related quality of life in a culturally and socially diverse South African community. Bull World Health Organ 2004;82: 206–12.

Torrance GW, Feeny D. Utilities and quality-adjusted life years. Int J Technol Assess Health Care 1989;5:559–75.

Tijhuis G, Jansen S, Stiggelbout A, Zwinderman A, Hazes J, Vlieland T. Value of the time trade off method for measuring utilities in patients with rheumatoid arthritis. Ann Rheum Dis 2000;59:892–7.

Attema AE, Edelaar-Peeters Y, Versteegh MM, Stolk EA. Time trade-off: one methodology, different methods. Eur J Health Econ 2013;14(Suppl 1):S53–64.

Boyd NF, Sutherland HJ, Heasman KZ, Tritchler DL, Cummings BJ. Whose utilities for decision analysis? Med Decis Making 1990;10:58–67.

Weyler EJ, Gandjour A. Empirical validation of patient versus population preferences in calculating QALYs. Health Serv Res 2011;46:1562–74.

Little MHR, Reitmeir P, Peters A, Leidl R. The impact of differences between patient and general population EQ- 5D-3L values on the mean tariff scores of different patient groups. Value Health 2014;17:364–71.

Ogorevc M, Murovec N, Fernandez NB, Rupel VP. Questioning the differences between general public vs. patient based preferences towards EQ-5D-5L defined hypothetical health states. Health Policy 2019;123:166–72.

Mann R, Brazier J, Tsuchiya A. A comparison of patient and general population weightings of EQ-5D dimensions. Health Econ 2009;10:363-72.

Burstrom K, Sun S, Gerdtham UG, Henriksson M, Johannesson M. Swedish experience-based value sets for EQ-5D health states. Qual Life Res 2014;12:431-42.

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Published

2022-03-15

How to Cite

1.
Nontarak J, Nontarak J, Nontarak J, Assanangkornchai S, Callinan S. A Comparison of Disability Weights for Alcohol Use Disorders. J Health Sci Med Res [Internet]. 2022 Mar. 15 [cited 2024 Nov. 22];39(2):101-13. Available from: https://he01.tci-thaijo.org/index.php/jhsmr/article/view/255242

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