The Intrinsic Value of the Information Contained in Medicine Leaflets

  1. José María Abellán Perpiñán 1
  2. Jorge Eduardo Martínez Pérez 1
  3. Fernando Ignacio Sánchez Martínez 1
  4. Jorge Luis Gómez Torres 1
  1. 1 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

Journal:
Hacienda Pública Española / Review of Public Economics

ISSN: 0210-1173

Year of publication: 2024

Issue Title: Health economics

Issue: 249

Pages: 83-107

Type: Article

DIALNET GOOGLE SCHOLAR lock_openOpen access editor

More publications in: Hacienda Pública Española / Review of Public Economics

Abstract

Este artículo aplica la metodología de la valoración contingente para estimar el valor monetario de la información contenida en los prospectos de los medicamentos. Al encuestar a una muestra de la población general, obtenemos estimaciones de disposición a pagar por el valor de proporcionar información cuantitativa adicional sobre los posibles beneficios y efectos secundarios de un medicamento hipotético, descritos según la mejor evidencia disponible sobre comunicación de riesgos. Las estimaciones de disposición a pagar encontradas en nuestro estudio oscilaron entre 60 centavos y 1 euro por mes. Además, también se presentan algunos test de consistencia de la robustez de nuestras estimaciones, así como evidencia sobre su viabilidad, fiabilidad y validez.

Bibliographic References

  • Bateman, I., Cameron, M. P. and Tsoumas, A. (2006), “Investigating the characteristics of stated preferences for reducing the impacts of air pollution: a contingent valuation experiment”, Working Papers in Economics, 06/08, University of Waikato, New Zealand.
  • Bateman, I., Day, B., Loomes, G. and Sugden, R. (2007), “Can ranking techniques elicit robust values?”, Journal of Risk and Uncertainty, 34: 49-66.
  • Bateman, I. J., Carson, R., Day, B., Hanemann, M., Hanley, N., Hett, T., Jones-Lee, M. and Loomes, G. (2002), Economic Valuation with Stated Preference Techniques: A Manual, Cheltenham, United Kingdom: Edward Elgar.
  • Bateman, I. J., Munro, A., Rhodes, B., Starmer, C. and Sugden, R. (1997), “Does part-whole bias exist? An experimental investigation”, Economic Journal, 107: 322-332.
  • Bordalo, P., Gennaioli, N. and Shleifer, A. (2013), “Salience and Consumer Choice”, Journal of Political Economy, 121: 803-843
  • Bordalo, P., Gennaioli, N. and Shleifer, A. (2016), “Competition for Attention”, The Review of Economic Studies, 83: 481-513.
  • Butler, D. J. and Loomes, G. C. (2007), “Imprecision as an account of the preference reversal phenomenon”, American Economic Review, 97(1): 277-297.
  • Carson, R. T. and Mitchell, R. C. (1995), “Sequencing and nesting in contingent valuation surveys”, Journal of Environmental Economics and Management, 28: 155-173.
  • Carson, R. T. (1997), “Contingent valuation surveys and tests of insensitivity to scope”, in Kopp, R. J., Pommerhene, W. and Schwartz, N. (eds,), Determining the Value of Non-marketed Goods, Boston: Kluwer Academic Publishers, 127-163.
  • Carthy, T., Chilton, S., Covey, J., Hopkins, L., Jones-Lee, M., Loomes, G., Pidgeon, N. and Spencer, A. (1999), “On the contingent valuation of safety and the safety of contingent valuation: Part 2-The CV/ SG ‘Chained’ approach”, Journal of Risk and Uncertainty, 17(3): 187-213.
  • Clark, J. and Friesen, L. (2008), “The causes of order effects in contingent valuation surveys: An experimental investigation”, Journal of Environmental Economics and Management, 56: 195-206.
  • Cokely E. T., Ghazal S. and García-Retamero R. (2014), “Measuring numeracy” in Anderson, B. L. and Schulkin, J. (eds.), Numerical reasoning in judgments and decision making about health, Cambridge, UK: Cambridge University Press.
  • Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S. and García-Retamero, R. (2012), “Measuring risk literacy: The Berlin numeracy test”, Judgment and Decision Making, 7(1): 25-47.
  • Dealy, B. C., Horn, B. P., Bohara, A. K., Berrens, R. P. and Bryan, A. D. (2017), “The Impact of Behavioural Risk-reduction Interventions on Willingness to Pay to Avoid Sexually Transmitted Infections: A Stated Preference Study of Justice-involved Youth”, Applied Economics, 49(56): 5673-5685.
  • Dealy, B. D., Kearsley, A., Wolff, C., Botkins, E., Lew, N. and Nardinelli, C. (2021), “Willingness to pay to standardize patient medication information”, Applied Economics, 53(9): 1112-1126.
  • Donaldson, C. and Shackley, P. (1997), “Does “process utility ”exist? A case study of willingness to pay for laparoscopic cholecystectomy”, Social Science & Medicine, 44: 699-707.
  • DuBourg, W. R., Jones-Lee, M. W. and Loomes, G. (1994), “Imprecise Preferences and the WTP-WTA Disparity”, Journal of Risk and Uncertainty, 9: 115-133.
  • Dubourg, W. R., Jones-Lee, M. W. and Loomes, G. (1997), “Imprecise preferences and survey design in contingent valuation”, Economica, 64: 681-702.
  • Educainee (2013), “Programa Internacional para la Evaluación de las Competencias de la población adulta (PIAAC) I”, Boletín de Educación INEE, N.º 15, Ministerio de Educación, Cultura y Deporte, 8 Octubre 2013.
  • García-Retamero, R. and Galesic, M. (2011), “Using plausible group sizes to communicate information about medical risks”, Patient education and counseling, 84(2): 245-250.
  • García-Retamero, R., Sobkow, A., Petrova, D., Garrido, D. and Traczyk, J. (2019), ”Numeracy and Risk Literacy: What Have We Learned so Far?”, The Spanish Journal of Psychology, 22, e10: 1-11.
  • Gigerenzer, G., Gaissmaier, W., Kurz-Milcke, E., Schwartz, L. M. and Woloshin, S. (2007), “Helping doctors and patients make sense of health statistics”, Psychological science in the public interest, 8(2): 53-96.
  • Haab, T. C., Interis, M. G., Petrolia, D. R. and Whitehead, J. C. (2013), “From Hopeless to Curious? Thoughts on Hausman’s “Dubious to Hopeless” Critique of Contingent Valuation”, Applied Economic Perspectives and Policy, 35(4): 593-612.
  • Hamrosi, K., Dickinson, R., Knapp, P., Raynor, D., Krass, I., Sowter, J. and Aslani, R. (2013), “It’s for your benefit: exploring patients’ opinions about the inclusion of textual and numerical benefit information in medicine leaflets”, International Journal of Pharmacy Practice, 21: 216-225.
  • Kahneman, D. and Knetsch, J. L. (1992), “Valuing public goods: The purchase of moral satisfaction”, Journal of Environmental Economics and Management, 2(1): 57-70.
  • Kling, C. L., Phaneuf, D. J. and Zhao, J. (2012), “From Exxon to BP: Has Some Number Become Better Than No Number?”, Journal of Economic Perspectives, 26(4): 3-26.
  • Latvala, T. and Kola, J. (2000), “Consumers’ Willingness to Pay for Information about Food Safety and Quality: Case Beef”, Contributed paper at the International Food and Agribusiness Management Association IAMA 10 th World Congress and Forum, Chicago, USA, (http://agecon.tamu.edu/iama/ 2000Congress/2000_forum_papers.htm).
  • MacCrimmon, K. and Smith, M. (1986), “Imprecise equivalences: Preference reversals in money and probability”. Working paper, University of British Columbia, Vancouver, BC, Canada.
  • Mitchell, R. C. and Carson, R. T. (1989), Using Surveys to Value Public Goods: The Contingent Valuation Method, Resources for the Future, New York, NY: Resources for the Future.
  • Pinto, J. L., Sánchez, F. I. and Rovira, J. (1998), “Medición de los beneficios intangibles de un tratamiento médico a través de la valoración contingente”, Hacienda Pública Española/Review of Public Economics, 147: 51-62.
  • Pinto-Prades, J. L., Martínez-Pérez, J. E. and Abellán-Perpiñán, J. M. (2006), “The influence of the ratio bias phenomenon on the elicitation of health states utilities”, Judgment and Decision Making, 1(2): 118-133.
  • Poe, G. L. (2016), “Behavioral Anomalies in Contingent Values and Actual Choices”, Agricultural and Resource Economics Review, 45(2): 246-269.
  • Protiere, C., Donaldson, C., Luchini, S., Moatti, J. P. and Shackley, P. (2004), “The impact of information on non-health attributes on willingness to pay for multiple health care programs”, Social Science & Medicine, 58: 1257-1269.
  • Sánchez-Martínez, F. I., Martínez-Pérez, J. E., Abellán-Perpiñán, J. M. and Pinto-Prades, J. L. (2021), “The value of statistical life in the context of road safety: new evidence on the contingent valuation/ standard gamble chained approach”, Journal of Risk and Uncertainty, 63(2): 203-228.
  • Shono, A., Kondo, M., Ohmae, H. and Okubo, I. (2014), “Willingness to Pay for Public Health Services in Rural Central Java, Indonesia: Methodological Considerations When Using the Contingent Valuation Method”, Social Science & Medicine, 110: 31-40.
  • Sirota, M. and Juanchich, M. (2019), “Ratio format shapes health decisions: the pratical significance of the 1 in X effect”, Medical Decision Making, 32(2): 179-193.
  • Sirota, M., Juanchich, M., Petrova, D., García-Retamero, R., Walasek, L. and Bhatia, S. (2018), “Health Professionals Prefer to Communicate Risk-Related Numerical Information using ‘1-in-X’ Ratios”, Medical Decision Making, 38(3): 1-11.
  • Tversky, A. and Kahneman, D. (1974), “Judgment under uncertainty: Heuristics and biases”, Science, 185: 1124-1130.
  • Tversky, A., Sattath, S. and Slovic, P. (1988), “Contingent weighting in judgment and choice”, Psychological Review, 95(3): 371-384.
  • Webster, R., Weinman, J. and Rubin, G. (2018), “Positively Framed Risk Information in Patient Information Leaflets Reduces Side Effect Reporting: A Double-Blind Randomized Controlled Trial”, Annals of Behavioral Medicine, 52: 920-929.
  • Yamagishi, K. (1997), “When a 12,86% mortality is more dangerous than 24,14%: implications for risk communication”, Applied Cognitive Psychology, 11: 495-506.
  • Yi, Y., Stvilia, B. and Mon, L. (2012), “Cultural influences on seeking quality health information: An exploratory study of the korean community”, Libray and Information Science Research, 34(1): 45-51.
Data source: Dialnet