Productivity Costs in Health-State Valuations

Objectives:The purpose of this study was to empirically explore whether individuals take their expected income into consideration when directly valuing predefined health states. This was intended to help determine how to handle productivity costs due to morbidity in a cost-effectiveness analysis.Methods:Two hundred students each valued four hypothetical health states by using time trade-off (TTO) and a visual analogue scale (VAS). The students were randomly assigned to two groups. One group was simply asked, without mentioning income, to value the different health states (the non-income group). The other group was explicitly asked to consider their expected income in relation to the health states in their valuations (the income group).Results:For health states that are usually assumed to have a large effect on income, the valuations made by the income group seemed to be lower than the valuations made by the non-income group. Among the students in the non-income group, 96 percent stated that they had not thought about their expected income when they valued the health states. In the income group, 40 percent believed that their expected income had affected their valuations of the health states.Conclusion:The results show that, as long as income is not mentioned, most individuals do not seem to consider their expected income when they value health states. This indicates that productivity costs due to morbidity are not captured within individuals' health state valuations. These findings, therefore, suggest that productivity costs due to morbidity should be included as a cost in cost-effectiveness analyses.

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Establishing health state valuations for disease specific states: an example from heart disease

Health Economics ◽

10.1002/(sici)1099-1050(200003)9:2<149::aid-hec501>3.0.co;2-n ◽

2000 ◽

Vol 9 (2) ◽

pp. 149-158 ◽

Cited By ~ 30

Author(s):

J. Kirsch ◽

A. McGuire

Keyword(s):

Heart Disease ◽

Health State ◽

Health State Valuations ◽

Disease Specific

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Time preference, duration and health state valuations

Health Economics ◽

10.1002/hec.4730040405 ◽

1995 ◽

Vol 4 (4) ◽

pp. 289-299 ◽

Cited By ~ 79

Author(s):

Paul Dolan ◽

Claire Gudex

Keyword(s):

Time Preference ◽

Health State ◽

Health State Valuations

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Treatment of venous thromboembolism with vitamin K antagonists: patients’ health state valuations and treatment preferences

Thrombosis and Haemostasis ◽

10.1160/th04-02-0075 ◽

2004 ◽

Vol 92 (12) ◽

pp. 1336-1341 ◽

Cited By ~ 40

Author(s):

Patrick Bossuyt ◽

Peep Stalmeier ◽

Mirjam Sprangers ◽

Carlo van Dongen ◽

Saskia Middeldorp ◽

...

Keyword(s):

Venous Thromboembolism ◽

Vitamin K ◽

Vitamin K Antagonists ◽

Patient Characteristics ◽

Haemorrhagic Stroke ◽

Treatment Preferences ◽

Health State ◽

Health States ◽

Health State Valuations ◽

Cessation Of Treatment

SummaryDetermining the optimal duration of vitamin K antagonist (VKA) therapy for patients with venous thromboembolism (VTE) requires a weighting of the benefits and risks of treatment. The objectives of our study were to investigate patient variability in health state valuations associated with VKA therapy and treatment preferences, and to investigate the extent to which valuations and treatment preferences are associated with prior experience with these health states and other patient characteristics. Valuations of outcomes after VTE scaled from 0 (tantamount to death) to 1 (tantamount to perfect health) were elicited from 53 patients who had experienced VTE, 23 patients who had experienced major bleeding during treatment, and 48 patients with the post-thrombotic syndrome. In addition, patients’ treatment preferences were evaluated using treatment trade-off questions. Median health state valuations ranged from 0.33 for ‘non-fatal haemorrhagic stroke’ to 0.96 for ‘no VKA treatment’. Variability between patients was substantial. Patients’ treatment preferences also varied: 25% of patients chose cessation of treatment, regardless of the probability of recurrent VTE presented, whereas 23% of patients were never willing to choose cessation of treatment. Differences in valuations and treatment preferences were not associated with type of event experienced. Due to the substantial and unpredictable variability in valuations and treatment preferences, recommendations regarding treatment duration should be tailored to patients’ specific values and concerns.

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Advocating a Paradigm Shift in Health-State Valuations: The Estimation of Time-Preference Corrected QALY Tariffs

Value in Health ◽

10.1016/j.jval.2018.01.016 ◽

2018 ◽

Vol 21 (8) ◽

pp. 993-1001 ◽

Cited By ~ 10

Author(s):

Marcel F. Jonker ◽

Bas Donkers ◽

Esther W. de Bekker-Grob ◽

Elly A. Stolk

Keyword(s):

Paradigm Shift ◽

Time Preference ◽

Health State ◽

Health State Valuations ◽

Estimation Of Time

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Manipulating the 5 Dimensions of the EuroQol Instrument: The Effects on Self-Reporting Actual Health and Valuing Hypothetical Health States

Medical Decision Making ◽

10.1177/0272989x19851049 ◽

2019 ◽

Vol 39 (4) ◽

pp. 380-392 ◽

Cited By ~ 4

Author(s):

Aki Tsuchiya ◽

Nick Bansback ◽

Arne Risa Hole ◽

Brendan Mulhern

Keyword(s):

Discrete Choice ◽

Online Survey ◽

Self Report ◽

Discrete Choice Experiments ◽

Health State ◽

Health States ◽

Different Types ◽

Health State Valuations ◽

The Uk ◽

Actual Health

Background. The EQ-5D instrument has 5 dimensions. This article reports on the effects of manipulating a) the order in which the 5 dimensions are presented (appearing first v. last), b) splitting of the composite dimensions (“pain or discomfort” and “anxiety or depression”), and c) removing or “bolting off” 1 of the 5 EQ-5D dimensions at a time. The effects were examined in 2 contexts: 1) self-reporting health and 2) health state valuations. Methods. Three different types of discrete choice experiments (DCE) including a duration attribute were designed. An online survey with 12 subtypes, each with 10 DCE tasks, was designed and completed by 2494 members of the UK general public. Results. Of the 3 manipulations in the self-reporting context, only b) splitting anxiety or depression had a significant effect. In the health state valuation context, b) splitting level 5 pain or discomfort (relative to pain) and splitting level 5 anxiety or depression (relative to anxiety) had significant effects as did c) bolting off dimensions. Conclusions. We find that the values given to certain health dimensions are sensitive to the way in which it is described and the other health dimensions presented. Of particular interest is the effect of splitting composite dimensions: a given EQ-5D(-5L) profile may mean different things depending on whether the profile is used to self-report one’s health or to value hypothetical states, so that the health state values of EQ-5D(-5L) in population tariffs may not correspond to the states that patients self-report themselves in.

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