PharmacoEconomics (2014) 32:423–424 DOI 10.1007/s40273-014-0129-y
LETTER TO THE EDITOR
Capturing Disutility from Waiting Time Afschin Gandjour
Published online: 22 January 2014 Ó Springer International Publishing Switzerland 2014
In many industrialized and developing countries, waiting times for medical tests and procedures are a major public concern. Hence, process disutility resulting from waiting times deserves to be considered in resource allocation decisions. The review by Brennan and Dixon [1] on the methods and results of incorporating process (dis)utility in quality-adjusted life-years (QALYs) is therefore a much welcomed and timely contribution.1 Yet, in my opinion it is important to consider where process disutility from waiting time is coming from as it affects the type of elicitation procedure to be recommended. Process disutility associated with waiting times can be divided into two distinct sources: impatience and anxiety. Other sources of disutility from waiting time exist (e.g. stress and fatigue) but are associated both with impatience and anxiety. That is, they do not represent a distinct category. But waiting time may also cause a utility gain because some individuals may feel positive tension and hope (e.g. when a procedure is expected to provide relief). An individual who waits for a routine medical test is impatient but not anxious if she or he has a small probability for a poor outcome and does not overweight small probabilities. In this case, the individual does not perceive the test as a threat and the disutility from waiting time can be captured using expected health as an outcome in the elicitation procedure (i.e. using a fixed health state). In fact this is the approach taken by the studies mentioned in the review. An example is the study by Howard et al. [2], which—using the standard gamble technique—evaluated different diagnostic strategies with the same final outcome.
However, consider an individual who is not only impatient but also anxious because she or he has a higher risk or overweighs small probabilities. In this case the elicitation procedure needs to consider the downside risk as well because it is this downside risk that makes the individual anxious. Hence, it is insufficient only to contain expected health or a fixed health state as an outcome in the elicitation procedure. A technique to incorporate anxiety from downside risk has been proposed [3] and incorporates the probability distribution over future outcomes in the profile to be assessed. It estimates the certainty-equivalent number of healthy years [4] and, in fact, is a variant of the healthy-years-equivalent (HYE) metric [5–7]. Based on this technique, the disutility from waiting time can be calculated as the utility difference between immediate availability of the test result/procedure and a situation where the individual has to wait. QALYs cannot capture anxiety completely because the underlying estimation procedures consider a constant health state until death. That is, uncertainty about future health is ignored when valuing health states. On the other hand, discrete choice experiments (DCEs) are able to incorporate uncertainty about future health by including risk in the alternatives to be chosen. Under certain circumstances it may be possible to convert the results from DCEs into HYEs, e.g. in case of non-fatal disease [8]. Using the HYE metric also solves the issue of potentially double counting anxiety because this technique values anxiety and health states simultaneously. That is, there is no need to introduce another assessment procedure. 1
A. Gandjour (&) Frankfurt, Germany e-mail: [email protected]
The review also considers process (dis)utility from drug delivery methods and dosing strategies, and therefore is broader in scope. Still, as shown in Tables 3 and 4, roughly half of the studies included in the review address process (dis)utility from waiting time.
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Still, the HYE approach comes with the disadvantage that individuals may not be able to account for the complexity of a profile by a one-step assessment. Individuals may also show insensitivity to scope, i.e. the value of the whole profile may be lower than the summed value of the individual parts [9]. On the other hand, presenting profiles to patients is similar to a situation where clinicians inform patients of risks and benefits of treatment and help the informed patient decide whether he/she prefers treatment or no treatment. Visual aids and written materials can facilitate this process and provide detailed information on patients’ choices, outcomes, probabilities of outcomes and their meaning, and quality of life associated with treatment choice and outcome [10]. In summary, the studies mentioned in the review do not capture the full range of disutility resulting from waiting time, at least in those situations where the anxiety from downside risk is important. As an alternative, I suggest the use of the HYE metric. Acknowledgments There are no potential conflicts of interest. No sources of funding were received to prepare this letter.
References 1. Brennan VK, Dixon S. Incorporating process utility into quality adjusted life years: a systematic review of empirical studies. Pharmacoeconomics. 2013;31(8):677–91.
A. Gandjour 2. Howard K, Salkeld G, McCaffery K, Irwig L. HPV triage testing or repeat Pap smear for the management of atypical squamous cells (ASCUS) on Pap smear: is there evidence of process utility? Health Econ. 2008;17(5):593–605. 3. Gandjour A. Incorporating feelings related to the uncertainty about future health in utility measurement. Health Econ. 2008;17(10):1207–13. 4. Johannesson M. The ranking properties of healthy-years equivalents and quality-adjusted life-years under certainty and uncertainty. Int J Technol Assessm Health Care. 1995;11(1):40–8. 5. Mehrez A, Gafni A. Quality-adjusted life years, utility theory, and healthy-years equivalents. Med Decis Making. 1989;9(2): 142–9. 6. Mehrez A, Gafni A. The healthy-years equivalents: how to measure them using the standard gamble approach. Med Decis Making. 1991;11(2):140–6. 7. Mehrez A, Gafni A. Preference based outcome measures for economic evaluation of drug interventions: quality adjusted life years (QALYs) versus healthy years equivalents (HYEs). Pharmacoeconomics. 1992;1(5):338–45. 8. Johnson FR, Hauber AB, Ozdemir S. Using conjoint analysis to estimate healthy-year equivalents for acute conditions: an application to vasomotor symptoms. Value Health. 2009;12(1): 146–52. 9. Towers I, Spencer A, Brazier J. Healthy year equivalents versus quality-adjusted life years: the debate continues. Exp Rev Pharmacoecon Outcomes Res. 2005;5(3):245–54. 10. Levine MN, Gafni A, Markham B, MacFarlane D. A bedside decision instrument to elicit a patient’s preference concerning adjuvant chemotherapy for breast cancer. Ann Intern Med. 1992;117(1):53–8.
LETTER TO THE EDITOR
Capturing Disutility from Waiting Time Afschin Gandjour
Published online: 22 January 2014 Ó Springer International Publishing Switzerland 2014
In many industrialized and developing countries, waiting times for medical tests and procedures are a major public concern. Hence, process disutility resulting from waiting times deserves to be considered in resource allocation decisions. The review by Brennan and Dixon [1] on the methods and results of incorporating process (dis)utility in quality-adjusted life-years (QALYs) is therefore a much welcomed and timely contribution.1 Yet, in my opinion it is important to consider where process disutility from waiting time is coming from as it affects the type of elicitation procedure to be recommended. Process disutility associated with waiting times can be divided into two distinct sources: impatience and anxiety. Other sources of disutility from waiting time exist (e.g. stress and fatigue) but are associated both with impatience and anxiety. That is, they do not represent a distinct category. But waiting time may also cause a utility gain because some individuals may feel positive tension and hope (e.g. when a procedure is expected to provide relief). An individual who waits for a routine medical test is impatient but not anxious if she or he has a small probability for a poor outcome and does not overweight small probabilities. In this case, the individual does not perceive the test as a threat and the disutility from waiting time can be captured using expected health as an outcome in the elicitation procedure (i.e. using a fixed health state). In fact this is the approach taken by the studies mentioned in the review. An example is the study by Howard et al. [2], which—using the standard gamble technique—evaluated different diagnostic strategies with the same final outcome.
However, consider an individual who is not only impatient but also anxious because she or he has a higher risk or overweighs small probabilities. In this case the elicitation procedure needs to consider the downside risk as well because it is this downside risk that makes the individual anxious. Hence, it is insufficient only to contain expected health or a fixed health state as an outcome in the elicitation procedure. A technique to incorporate anxiety from downside risk has been proposed [3] and incorporates the probability distribution over future outcomes in the profile to be assessed. It estimates the certainty-equivalent number of healthy years [4] and, in fact, is a variant of the healthy-years-equivalent (HYE) metric [5–7]. Based on this technique, the disutility from waiting time can be calculated as the utility difference between immediate availability of the test result/procedure and a situation where the individual has to wait. QALYs cannot capture anxiety completely because the underlying estimation procedures consider a constant health state until death. That is, uncertainty about future health is ignored when valuing health states. On the other hand, discrete choice experiments (DCEs) are able to incorporate uncertainty about future health by including risk in the alternatives to be chosen. Under certain circumstances it may be possible to convert the results from DCEs into HYEs, e.g. in case of non-fatal disease [8]. Using the HYE metric also solves the issue of potentially double counting anxiety because this technique values anxiety and health states simultaneously. That is, there is no need to introduce another assessment procedure. 1
A. Gandjour (&) Frankfurt, Germany e-mail: [email protected]
The review also considers process (dis)utility from drug delivery methods and dosing strategies, and therefore is broader in scope. Still, as shown in Tables 3 and 4, roughly half of the studies included in the review address process (dis)utility from waiting time.
424
Still, the HYE approach comes with the disadvantage that individuals may not be able to account for the complexity of a profile by a one-step assessment. Individuals may also show insensitivity to scope, i.e. the value of the whole profile may be lower than the summed value of the individual parts [9]. On the other hand, presenting profiles to patients is similar to a situation where clinicians inform patients of risks and benefits of treatment and help the informed patient decide whether he/she prefers treatment or no treatment. Visual aids and written materials can facilitate this process and provide detailed information on patients’ choices, outcomes, probabilities of outcomes and their meaning, and quality of life associated with treatment choice and outcome [10]. In summary, the studies mentioned in the review do not capture the full range of disutility resulting from waiting time, at least in those situations where the anxiety from downside risk is important. As an alternative, I suggest the use of the HYE metric. Acknowledgments There are no potential conflicts of interest. No sources of funding were received to prepare this letter.
References 1. Brennan VK, Dixon S. Incorporating process utility into quality adjusted life years: a systematic review of empirical studies. Pharmacoeconomics. 2013;31(8):677–91.
A. Gandjour 2. Howard K, Salkeld G, McCaffery K, Irwig L. HPV triage testing or repeat Pap smear for the management of atypical squamous cells (ASCUS) on Pap smear: is there evidence of process utility? Health Econ. 2008;17(5):593–605. 3. Gandjour A. Incorporating feelings related to the uncertainty about future health in utility measurement. Health Econ. 2008;17(10):1207–13. 4. Johannesson M. The ranking properties of healthy-years equivalents and quality-adjusted life-years under certainty and uncertainty. Int J Technol Assessm Health Care. 1995;11(1):40–8. 5. Mehrez A, Gafni A. Quality-adjusted life years, utility theory, and healthy-years equivalents. Med Decis Making. 1989;9(2): 142–9. 6. Mehrez A, Gafni A. The healthy-years equivalents: how to measure them using the standard gamble approach. Med Decis Making. 1991;11(2):140–6. 7. Mehrez A, Gafni A. Preference based outcome measures for economic evaluation of drug interventions: quality adjusted life years (QALYs) versus healthy years equivalents (HYEs). Pharmacoeconomics. 1992;1(5):338–45. 8. Johnson FR, Hauber AB, Ozdemir S. Using conjoint analysis to estimate healthy-year equivalents for acute conditions: an application to vasomotor symptoms. Value Health. 2009;12(1): 146–52. 9. Towers I, Spencer A, Brazier J. Healthy year equivalents versus quality-adjusted life years: the debate continues. Exp Rev Pharmacoecon Outcomes Res. 2005;5(3):245–54. 10. Levine MN, Gafni A, Markham B, MacFarlane D. A bedside decision instrument to elicit a patient’s preference concerning adjuvant chemotherapy for breast cancer. Ann Intern Med. 1992;117(1):53–8.
