Experience-Based Swedish TTO and VAS Value Sets for EQ-5D-5L Health States
Kristina Burström, Fitsum Sebsibe Teni, Ulf-G Gerdtham, Reiner Leidl, Gert Helgesson, Ola Rolfson, Martin Henriksson, Kristina Burström, Fitsum Sebsibe Teni, Ulf-G Gerdtham, Reiner Leidl, Gert Helgesson, Ola Rolfson, Martin Henriksson
Abstract
Background and objective: Although value sets for the five-level version of the generic health-related quality-of-life instrument EQ-5D are emerging, there is still no value set available in the literature based on time trade-off valuations made by individuals experiencing the valued health states. The aim of this study was to estimate experience-based value sets for the EQ-5D-5L for Sweden using time trade-off and visual analogue scale valuation methods.
Methods: In a large, cross-sectional, population-based, self-administered postal health survey, the EQ-5D-5L descriptive system, EQ visual analogue scale and a time trade-off question were included. Time trade-off and visual analogue scale valuations of the respondent's current health status were used in statistical modelling to estimate a single-index value of health for each of the 3125 health states. Ordinary least-squares and generalised linear models were estimated with the main effect within each of the five dimensions represented by 20 dummy variables reflecting the additional decrement in value for levels 2-5 when the severity increases by one level sequentially beginning from having no problem. Interaction variables representing the occurrence of severity levels in at least one of the dimensions were tested: severity level 2 or worse (N2); severity level 3 or worse (N3); severity level 4 or worse (N4); severity level 5 (N5).
Results: A total of 896 health states (28.7% of the 3125 possible EQ-5D-5L health states) were reported by the 25,867 respondents. Visual analogue scale (n = 23,899) and time trade-off (n = 13,381) responders reported valuations of their currently experienced health state. The preferred regression models used ordinary least-squares estimation for both time trade-off and visual analogue scale values and showed consistency in all coefficients after combining certain levels. Levels 4 and 5 for the dimensions of mobility, self-care and usual activities were combined in the time trade-off model. Including the interaction variable N5, indicating severity level 5 in at least one of the five dimensions, made it possible to distinguish between the two worst severity levels where no other dimension is at level 5 as this coefficient is applied only once. In the visual analogue scale regression model, levels 4 and 5 of the mobility dimension were combined. The interaction variables N2-N4 were included, indicating that each of these terms reflect a statistically significant decrement in visual analogue scale value if any of the dimensions is at severity level 2, 3 or 4, respectively.
Conclusions: Time trade-off and visual analogue scale value sets for the EQ-5D-5L are now available for Sweden. The time trade-off value set is the first such value set based on experience-based time trade-off valuation. For decision makers with a preference for experience-based valuations of health states from a representative population-based sample, the reported value sets may be considered fit for purpose to support resource allocation decision as well as evaluating population health and healthcare performance.
References
- Rabin R, de Charro F. EQ-5D: a measure of health status from the EuroQol group. Ann Med. 2001;33(5):337–43.
- Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20:1727–36.
- Stolk E, Ludwig K, Rand K, van Hout B, Ramos-Goñi JM. Overview, update, and lessons learned from the international EQ-5D-5L valuation work: version 2 of the EQ-5D-5L valuation protocol. Value Health. 2019;22(1):23–30.
- Pullenayegum EM, Perampaladas K, Gaebel K, Doble B, Xie F. Between-country heterogeneity in EQ-5D-3L scoring algorithms: how much is due to differences in health state selection? Eur J Health Econ. 2015;16(8):847–55.
- Xie F, Gaebel K, Perampaladas K, Doble B, Pullenayegum E. Comparing EQ-5D valuation studies: a systematic review and methodological reporting checklist. Med Decis Making. 2014;34(1):8–20.
- Devlin NJ, Shah KK, Feng Y, Mulhern B, van Hout B. Valuing health-related quality of life: an EQ-5D-5L value set for England. Health Econ. 2018;27:7–22.
- Hernández-Alava M, Pudney S, Wailoo A. Quality review of a proposed EQ-5D-5L value set for England. Policy Research Unit in Economic Evaluation of Health & Care Interventions (EEPRU) Report October 2018. Available from: . Accessed 17 Dec 2019.
- Weinstein MC, Torrance G, McGuire A. QALYs: the basics. Value Health. 2009;12(Suppl. 1):S5–9.
- National Institute for Health and Care Excellence (NICE). Guide to the methods of technology appraisal. 2013. London: NICE; 2013. Available from: . Accessed 17 Dec 2019.
- The Dental and Pharmaceutical Benefits Agency (TLV). General guidelines for economic evaluations from the Pharmaceutical Benefits Board LFNAR 2003:2. Stockholm: TLV; 2003. Available from: . Accessed 17 Dec 2019.
- The Dental and Pharmaceutical Benefits Agency (TLV). Ändring i Tandvårds- och läkemedelsförmånsverkets allmänna råd (TLVAR 2003:2) om ekonomiska utvärderingar (in Swedish). [Changes in the Dental and Pharmaceutical Benefits Agency´s guidance for economic evaluations]. Stockholm: TLV; 2017. Available from: . Accessed 17 Dec 2019.
- Dolan P. Modeling valuations for EuroQol health states. Med Care. 1997;35(11):1095–108.
- Burström K, Sun S, Gerdtham UG, Henriksson M, Johannesson M, Levin LÅ. Swedish experience-based value sets for EQ-5D health states. Qual Life Res. 2014;23:431–42.
- Cubi-Molla P, Shah K, Burström K. Experience-based values: a framework for classifying different types of experience in health valuation research. Patient. 2018;11(3):253–70.
- Leidl R, Reitmeir P. A value set for the EQ-5D based on experienced health states: development and testing for the German population. Pharmacoeconomics. 2011;29(6):521–34.
- Sun S, Chen J, Kind P, Xu L, Zhang Y, Burström K. Experience-based VAS values for EQ-5D-3L health states in a national general population health survey in China. Qual Life Res. 2015;24(3):693–703.
- Leidl R, Reitmeir P. An experience-based value set for the EQ-5D-5L in Germany. Value Health. 2017;20(8):1150–6.
- Versteegh MM, Brouwer WBF. Patient and general public preferences for health states: a call to reconsider current guidelines. Soc Sci Med. 2016;165:66–74.
- CDUST Region 2018. Liv & hälsa 2017 i Mellansverige: resultat från en undersökning om livsvillkor, levnadsvanor och hälsa (in Swedish). [Life and health 2017: results from a survey on living conditions, health-related behaviors and health]. Available from: . Accessed 17 Dec 2019.
- Dolan P. Thinking about it: thoughts about health and valuing QALYs. Health Econ. 2011;20(12):1407–16.
- Burström K, Johannesson M, Diderichsen F. A comparison of individual and social time trade-off values for health states in the general population. Health Policy. 2006;76:359–70.
- Bardage C, Isacson D, Ring L, Bingefors K. A Swedish population-based study on the relationship between the SF-36 and health utilities to measure health in hypertension. Blood Press. 2003;12(4):203–10.
- Lundberg L, Johannesson M, Isacson DG, Borgquist L. Health-state utilities in a general population in relation to age, gender and socioeconomic factors. Euro J Public Health. 1999;3:211–7.
- Chai T, Draxler RR. Root mean square error (RMSE) or mean absolute error (MAE)? Arguments against avoiding RMSE in the literature. Geosci Model Dev. 2014;7:1247–50.
- Sammut C, Webb GI, editors. Mean absolute error. Encyclopedia of machine learning. Boston (MA): Springer; 2011. Available from: . Accessed 17 Dec 2019.
- Willmott CJ, Matsuura K. Advantages of the mean absolute error (MAE) over the root mean square error (RMSE) in assessing average model performance. Clim Res. 2005;30:79–82.
- Wooldridge JM. Inverse probability weighted M-estimators for sample selection, attrition, and stratification. Port Econ J. 2002;1(2):117–39.
- Versteegh MM, Vermeulen KM, Evers SMAA, de Wit GA, Prenger R, Stolk EA. Dutch tariff for the five-level version of EQ-5D. Value Health. 2016;19:343–52.
- Ludwig K, Graf von der Schulenburg J-M, Greiner W. German value set for the EQ-5D-5L. Pharmacoeconomics. 2018;36:663–74.
- Hobbins A, Barry L, Kelleher D, Shah K, Devlin N, Goni JMR, et al. Utility values for health states in Ireland: a value set for the EQ-5D-5L. Pharmacoeconomics. 2018;36:1345–53.
- Ramos-Goñi JM, Craig BM, Oppe M, Ramallo-Fariña Y, Pinto-Prades JL, Luo N, et al. Handling data quality issues to estimate the Spanish EQ-5D-5L value set using a hybrid interval regression approach. Value Health. 2018;21:596–604.
- Helgesson G, Ernstsson O, Åström M, Burström K. Whom should we ask? A systematic literature review of the arguments regarding the most accurate source of information for valuation of health states. Qual Life Res. 2020. .
- Wolff J, Edwards S, Richmond S, Orr S, Rees G. Evaluating interventions in health: a reconciliatory approach. Bioethics. 2012;26(9):455–63.
- Dolan P. NICE should value real experiences over hypothetical opinions. Nature. 2009;462(7269):35.
- Dolan P, Kahneman D. Interpretations of utility and their implications for the valuation of health. Econ J. 2008;118:215–34.
- Brazier J, Akehurst R, Brennan A, Dolan P, Claxton K, McCabe C, et al. Should patients have a greater role in valuing health states? Appl Health Econ Health Policy. 2005;4(4):201–8.
- Emilsson L, Lindahl B, Köster M, Lambe M, Ludvigsson JF. Review of 103 Swedish healthcare quality registries. J Intern Med. 2015;277:94–136.
- Stamuli E. Health outcomes in economic evaluation: who should value health? Br Med Bull. 2011;97:197–210.
- Happich M, von Lengerke T. Valuing the health state ‘tinnitus’: differences between patients and the general public. Hear Res. 2005;207:50–8.
- Ubel PA, Loewenstein G, Jepson C. Whose quality of life? A commentary exploring discrepancies between health state evaluations of patients and the general public. Qual Life Res. 2003;12:599–607.
- 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(2):166–72.
- Ubel PA, Nord E, Gold M, Menzel P, Prades JL, Richardson J. Improving value measurement in cost-effectiveness analysis. Med Care. 2000;38(9):892–901.
- Leidl R. Zum Beitrag der gesundheitsökonomischen Forschung zur medizinischen Versorgung [in German]. [On the contribution of health economic research to medical care] (abstract in English). Gesundh ökon Qual Manag. 2018;23(3):159–65.
Source: PubMed