Top

International Journal of Health Economics and Management

Published in:

01-12-2013

Willingness-to-pay to prevent Alzheimer’s disease: a contingent valuation approach

Author: Rashmita Basu

Published in: International Journal of Health Economics and Management | Issue 3-4/2013

Abstract

As the prevalence of Alzheimer’s disease (AD) increases, the need to develop effective and well-tolerated pharmacotherapies for the prevention of AD is becoming increasingly important. Understanding determinants and magnitudes of individuals’ preferences for AD prevention programs is important while estimating the benefits of any new pharmacological intervention that targets the prevention of the disease. This paper applied contingent valuation, a method frequently used for economic valuation of goods or services not transacted in the markets, to estimate the willingness-to-pay (WTP) to prevent AD based on the nationally representative Health and Retirement Survey data. The WTP was associated in predictable ways with respondent characteristics. The mean estimated WTP for preventing AD is $155 per month (95 % CI $153–$157) based on interval regression. On average, a higher WTP for the prescription drug for AD prevention was reported by respondents with higher perceived risks, and greater household wealth. The findings provide useful information about determinants and the magnitude of individuals’ preferences for AD prevention drugs for healthcare payers and individual families while making decisions to prevent AD.

Available only for authorised users

Participants were given a general statement explaining that the government and universities spend money on medical research and there is a great need to understand how these funds ought to be spent, given that people differed in rating the importance of different health outcomes. Respondents also were told that they should concentrate on their own assessments, and not make any assumption on the way that someone else would respond to these same questions. They were then told that their responses would be used to decide allocation of funds in medical research and not to help drug companies decide how much they could charge for their medicines.

The specific question asked in the survey was: “Did a doctor ever tell you that you had a memory related disease?”

Before taking the natural log, a value of 1 was added to WTP values to avoid the problem of 0 values. In the empirical model dependent variable used as $\ln (WTP)=\log (1+WTP).$

Calculated by summing all assets (excluding second home) minus all debts. (In a sense, it represents net worth).

The logarithmic transformation of the outcome variable reduces the skewness and approximates it to the normal distribution. The use of normal or lognormal distributions is most common in estimating interval regression model.

$lnwealth=\log (1+wealth)$

The detail of this can be found in any standard econometric textbook (Wooldridge 2002). Here a very brief summary of the test is provided. The test is performed at two steps. For the first step, we regress the endogenous regressor (here, perceived risk) on instruments (highly correlated with perceived risks but not associated with WTP such as health risk behaviors) and other exogenous factors that influence perceived risk, then obtain the residual from the regression estimation. For the second step, WTP was regressed on a set of exogenous factors including the residual obtained from the first step. A non-significant test statistic indicates that the variable is not endogenous. Here, decline in self-rated memory, health risk behaviors, and chronic conditions were used as instruments for perceived risk, since these variables were assumed to be uncorrelated with WTP but highly correlated with perceived risk.

It is of interest to compare this perceived risk with actual risk of developing AD for population similar to this sample. Based on the Framingham Study, the lifetime risks (the probability that someone of a given age develops the condition during remaining lifetime) of AD and of any dementia for women at age 65 is 20 % and that of men would be 17 % (Alzheimer’s Disease, Facts & Figures 2012). However, these estimated risks will increase with age. Compared to the mean self-assessed probability of developing AD for this sample is 30 %, it cannot rules out the possibility of slightly higher than estimates obtained from actual epidemiological data. However, it is important to note that these estimates are conservative because of the high threshold used in the Framingham study for categorizing patients with dementia.

There are reasons to believe that respondents can accurately assess their own health risks. In the sample an average respondent reported that there would be 50 % chance that the respondent would be living between 85 and 100 years. This expected probability of living corresponds to the actual probability that US male by age 65 have a 40 % chance of living age 85 and females 53 % chance (based on data extracted from the analysis of the 2007 period Life Table for Social Security Area Population (Society of Actuaries 2012). Smith et al. (2001) also found that observed deaths among HRS respondents were preceded by lower self-assessed longevity estimations in prior years.

The Duan smearing factor was calculated as [$\sum (\text {exp}(\text {e}_\mathrm{i})$]/n; where e$_{i}$ is the ith residual of the regression in the log scale; and was multiplied to the estimated WTP value to correct for the retransformation bias.

Alzheimer’s Disease, Facts & Figures (2011). http://www.alz.org/downloads/facts_figures_2011.pdf.

Alzheimer’s Disease, Facts & Figures (2012). http://www.alz.org/downloads/facts_figures_2012.pdf.

Amin, M., & Khondoker, F. A. (2004). Contingent valuation study to estimate the parental willingness-to-pay for childhood diarrhoea and gender bias among rural households in India. Health Research Policy and Systems, 2, 3. doi:10.1186/1478-4505-2-3.PubMedCrossRef

Arana, J. E., & Leon, C. J. (2002). Willingness to pay for health risk reduction in the context of altruism. Health Economics, 11, 623–635. doi:10.1002/hec.687.PubMedCrossRef

Barnighausen, T., Liu, Y., Zhang, X., & Sauerborn, R. (2007). Willingness to pay for social health insurance among informal sector workers in Wuhan, China: A contingent valuation study. BMC Health Services Research, 7, 114. doi:10.1186/1472-6963-7-114.PubMedCrossRef

Bateman, R. J., Xiong, C., Bensnger, T. L., Fagan, A. M., Goate, A., et al. (2012). Clinical and biomarker changes in dominantly inherited Alzheimer’s Disease. The New England Journal of Medicine, 367, 795–804. doi:10.1056/NEJMoa1202753.PubMedCrossRef

Cameron, T. A. (1988). A new paradigm for valuing non-market goods using referendum data: Maximum likelihood estimation by censored logistic regression. Journal of Environmental Economics and Management, 1988(15), 355–379. doi:10.1016/0095-0696(88)90008-3.CrossRef

Cameron, T. A. (1991). Interval estimates from non-market resource values for referendum contingent valuation surveys. Land Economy, 67, 413–421. doi:10.2307/3146548.CrossRef

Cameron, T. A., & Huppert, D. D. (1989). OLS verses ML estimation of non-market resource values with payment card interval data. Journal of Environmental Economics and Management, 17, 230–246.CrossRef

Cawley, J. (2008). Contingent valuation analysis of willingness to pay to reduce childhood obesity. Economics & Human Biology, 6, 281–292. doi:10.1016/j.ehb.2008.05.003.CrossRef

Chestnut, L. G., Keller, L. R., Lambert, W. E., & Rowe, R. D. (1996). Measuring heart patients’ willingness to pay for changes in angina symptoms. Medical Decision Making, 16, 65–77. doi:10.1177/0272989X9601600115.PubMedCrossRef

Chung, S., Mehta, K., Shumway, M., Alvidrez, J., & Perez-Stable, E. J. (2009). Risk perception and preference for prevention of Alzheimer’s disease. Value Health, 12, 450–458.PubMedCrossRef

Crimmins, E. M., Kim, J. K., Langa, K. M., & Weir, D. R. (2011). Assessment of cognition using surveys and neuopsychological assessment: The Health and Retirement Study and the Aging Demographics, and Memory Study. The Journals of Gerontology Series B, 66, i162–171. doi:10.1093/geronb/gbr048.CrossRef

Duan, N. (1983). Smearing estimate: A nonparametric retransformation method. American Statistical Association, 78, 605–610. doi:10.2307/2288126.CrossRef

Fischhoff, B., Slovic, P., Lichtenstein, S., Read, S., & Combs, B. (1978). How safe is safe enough? A psychometric study of attitude towards technological risks and benefits. Political Science, 9, 127–152. doi:10.1007/BF00143739.

Gafni, A. (1998). Willingness to pay: What’s in a name? Pharmacoeconomcs, 14, 465–470. doi:10.2165/00019053-199814050-00001.CrossRef

Grossberg, G. T., Pejovic, V., & Miller, M. L. (2007). Current strategies for the treatment and prevention of Alzheimer’s disease. Primary Psychiatry, 14, 39–54.

Hanemann, W. M., & Kanninen, B. (1999). The statistical analysis of discrete-response CV data. In I. Batemen & K. Willis (Eds.), Valuing environmental preferences. Theory and practice of the contingent valuation method in the US, EU and developing countries (pp. 302–441). Oxford University Press: Oxford.

Hanemann, W. M., Loomis, J., & Kanninen, B. (1991). Statistical efficiency of double bounded dichotomous choice contingent valuation. American Journal of Agricultural Economics, 73, 1255–1263. doi:10.2307/1242453.CrossRef

Hann, M. N., & Weldon, M. (1996). The influence of diabetes, hypertension, and stroke on ethnic differences in physical, and cognitive functioning in an ethnically diverse elderly population. Annals of Epidemiology, 6, 392–398. doi:10.1016/S1047-2797(96)00062-2.CrossRef

Hausman, J. A. (1983). Specification and estimation of simultaneous equation models. In: Z. Griliches & M.D. Intriligator (Eds.), Handbook of econometrics (Vol. I). North-Holland Publishing Company: Amsterdam.

Hebert, L. E., Scherr, P. A., Bienias, J. L., Bennett, D. A., & Evans, D. A. (2003). Alzheimer disease in the US population: Prevalence estimates using the 2000 census. Archives of Neurology, 60, 1119–1122. doi:10.1001/archneur.60.8.1119.PubMedCrossRef

Herzog, A. R., & Wallace, R. B. (1997). Measures of cognitive functioning in the AHEAD study. The Journals of Gerontology Series B, 52, 37–48. doi:10.1093/geronb/52B.Special_Issue.37.CrossRef

Johnson, F. R., Manjunath, R., Mansfield, C. A., Clayton, L. J., Hoerger, T. J., & Zhang, P. (2006). High-risk individuals’ willingness to pay for diabetes risk-reduction programs. Diabetes Care, 29, 1351–1356. doi:10.2337/dc05-2221.PubMedCrossRef

Juster, F. T., & Suzman, R. (1995). An overview of the health and retirement study. Journal of Human Resources, 30(Suppl), S7–S56. doi:10.2307/146277.CrossRef

Kasperson, R. E., Renn, O., Slovic, P., Brown, H. S., et al. (1988). The social amplification of risk: A conceptual framework. Risk analysis, 8, 177–187. doi:10.1111/j.1539-6924.1988.tb01168.x.CrossRef

Klose, T. (1999). Contingent valuation method in health care. Health Policy, 47, 97–123. doi:10.1016/S0168-8510(99)00010-X.PubMedCrossRef

Langa, K.M., Kabeto, M., Weir, D. (2010). Report on race and cognitive impairment using HRS in 2010 Alzheimer’s disease facts and figures. Retrieved July 12, 2010 from http://www.alz.org/documents_custom/report_alzfactsfigures2010.pdf.

Lewin Group (2004) Saving lives, saving money: Dividends for American investing in Alzheimer’s research. Retrieved January, 2012 from http://www.lewin.com/~/media/Lewin/Site_Sections/Publications/2867.pdf.

McCullagh, P. (1980). Regression models for ordinal data. Journal of the Royal Statistical Society, 42, 109–142.

Milligan, M., Bohara, A., & Pagan, J. (2010). Assessing willingness to pay for cancer prevention. International Journal of Health Care Finance and Economics, 10, 301–314. doi:10.1007/s10754-010-9082-2.PubMedCrossRef

Narbro, K., & Sjostrom, L. (2000). Willingness to pay for obesity treatment. International Journal of Technology Assessment in Health Care, 16, 50–59. doi:10.1017/S0266462300016159.PubMedCrossRef

Nguyen, T., Jakus, P. M., Riddel, M., & Shaw, W. D. (2010). An empirical model of perceived mortality risks for selected U.S Arsenic hot spots. Risk Analysis, 30, 1550–1562. doi:10.1111/j.1539-6924.2010.01450.x.PubMedCrossRef

O’brien, B., Georee, R., Gani, A., Torrance, G., Pauly, M., Erder, H., et al. (1998). Assessing the value of a new pharmaceutical: A feasibility study of contingent valuation in managed care. Medical Care, 36, 370–384. doi:10.1097/00005650-199803000-00013.PubMedCrossRef

Oremus, M., Tarride, J. E., Clayton, N., & Raina, P. (2009). Support for a tax increase to provide unrestricted access to an Alzheimer’s disease medication: A survey of the general public in Canada. BMC Health Services Research, 9, 246. doi:10.1186/1472-6963-9-246.PubMedCrossRef

Prosser, L. A., Ray, G. T., O‘Brien, M., Kleinman, K., Santoli, J., & Lieu, T. A. (2004). Preferences and willingness to pay for health states prevented by pneumococcal conjugate vaccine. Pediatrics, 113, 283–290. doi:10.1542/peds.113.2.283.PubMedCrossRef

Roux, L., Ubach, C., Donaldson, C., & Ryan, M. (2004). Valuing the benefits of weight loss programs: An application of the discrete choice experiment. Obesity Research, 12, 1342–1351. doi:10.1038/oby.2004.169.PubMedCrossRef

Sloane, P. D., Zimmerman, S., Suchindran, C., Reed, P., Wang, L., Boustani, M., et al. (2002). The public health impact of Alzheimer’s disease, 2000–2050: Potential implication for treatment advances. Annual Review of Public Health, 23, 213–231. doi:10.1146/annurev.publhealth.23.100901.140525.PubMedCrossRef

Slovic, P., Fischhoff, B., Lichtenstein, S., & Roe, F. J. C. (1978). Perceived Risks: Psychological factors and social implications [and discussion]. Proceedings of the Royal Society of London, 376, 17–34. doi:10.1098/rspa.1981.0073.

Smith, V. K., Taylor, D. H., & Sloan, F. A. (2001). Longevity expectations and death: Can people predict their own demise. American Economic Review, 91, 1126–1134. doi:10.1257/aer.91.4.1126.CrossRef

Society of Actuaries (2012). Key findings and issues: Longevity, 2011 risks and process of retirement survey report. Retrieved January, 2013 from www.soa.org/files/research/projects/research-key-finding-longevity.pdf.

Taylor, D. H, Jr, & Sloan, F. A. (2000). How much do Alzheimer’s disease cost medicare? Journal of the American Geriatrics Society, 48, 639–646.PubMed

Venkatachalam, L. (2004). The contingent valuation method: A review. Environmental Impact Assessment Review, 24, 89–124. doi:10.1016/S0195-9255(03)00138-0.CrossRef

Viscusi, W. K. (1990). Do smokers underestimate risks? Journal of Political Economy, 98, 1253–1269. doi:10.1086/261733.CrossRef

Wagner, T. H., Hu, T., Duenas, G. V., Kaplan, C. P., Nguyen, B. H., & Pasick, R. J. (2001). Does willingness to pay vary by race/ethnicity? An analysis using mammography among low-income women. Health Policy, 58, 275–288. doi:10.1016/S0168-8510(01)00177-4.PubMedCrossRef

Watson, V., & Ryan, M. (2007). Exploring preference anomalies in double bounded contingent valuation. Journal of Health Economics, 26, 463–482. doi:10.1016/j.jhealeco.2006.10.009.PubMedCrossRef

Whitehead, J. C. (2002). Incentive incompatibility and starting point bias in iterative valuation questions. Land Economy, 78, 285–297. doi:10.2307/3147274.CrossRef

Wooldridge, J. M. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.

Title: Willingness-to-pay to prevent Alzheimer’s disease: a contingent valuation approach
Author: Rashmita Basu
Publication date: 01-12-2013
Publisher: Springer US
Published in: International Journal of Health Economics and Management / Issue 3-4/2013
Print ISSN: 2199-9023
Electronic ISSN: 2199-9031
DOI: https://doi.org/10.1007/s10754-013-9129-2

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Willingness-to-pay to prevent Alzheimer’s disease: a contingent valuation approach

Abstract

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Please log in to get access to this content

Other articles of this Issue 3-4/2013

Evaluating an employee wellness program

Sleeping money: investigating the huge surpluses of social health insurance in China

Does healthcare financing converge? Evidence from eight OECD countries

Regulated medical fee schedule of the Japanese health care system

Who funds their health savings account and why?

Awareness and utilization of preventive care services among the elderly under National Health Insurance