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The Value of Improved National Exposure Information for Perchloroethylene (Perc): A Case Study for Dry Cleaners

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  • Kimberly M. Thompson
  • John S. Evans

Abstract

Opportunities to improve our information about risk continue to arise and lead decision makers to indirectly address the issue of the value of improved information through resource allocation decisions. Statistical decision analysis techniques provide an analytical framework for valuing information explicitly in the context of regulatory decision making. This paper provides estimates of the value of improved national estimates of perchloroethylene (perc) exposure from U.S. dry cleaners in the context of EPA's recently promulgated National Emissions Standard for Hazardous Air Pollutants (NESHAP) with emphasis on exposure information. Consistent with the NESHAP decision, we relied on EPA's technology and economic assessments. In this first cut analysis, estimates of the exposures of workers, consumers of dry cleaning services, and the general public are probabilistically characterized to reflect uncertainty about exposure and potency. We consider the net benefits of the different control options by assessing the associated changes in the total annual population risks and valuing them in monetary terms, with no constraints placed on maximum individual risks. The results suggest that the expected value of perfect information (EVPI) about potency exceeds the EVPI about exposure. Sensitivity analyses demonstrate how the choices of the valuation parameters and distributions used to characterize uncertainty in the model affect the estimates of the value of information.

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  • Kimberly M. Thompson & John S. Evans, 1997. "The Value of Improved National Exposure Information for Perchloroethylene (Perc): A Case Study for Dry Cleaners," Risk Analysis, John Wiley & Sons, vol. 17(2), pages 253-271, April.
    • Handle: RePEc:wly:riskan:v:17:y:1997:i:2:p:253-271
    DOI: 10.1111/j.1539-6924.1997.tb00864.x
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    Cited by:

    1. Jason Madan & Anthony E. Ades & Malcolm Price & Kathryn Maitland & Julie Jemutai & Paul Revill & Nicky J. Welton, 2014. "Strategies for Efficient Computation of the Expected Value of Partial Perfect Information," Medical Decision Making, , vol. 34(3), pages 327-342, April.
    2. Claxton, K. & Thompson, K. M., 2001. "A dynamic programming approach to the efficient design of clinical trials," Journal of Health Economics, Elsevier, vol. 20(5), pages 797-822, September.
    3. Richard A. Williams & Kimberly M. Thompson, 2004. "Integrated Analysis: Combining Risk and Economic Assessments While Preserving the Separation of Powers," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1613-1623, December.
    4. Elizabeth Fenwick & Karl Claxton & Mark Sculpher & Andrew Briggs, 2000. "Improving the efficiency and relevance of health technology assessent: the role of iterative decision analytic modelling," Working Papers 179chedp, Centre for Health Economics, University of York.
    5. Karl Claxton, 1999. "Bayesian approaches to the value of information: implications for the regulation of new pharmaceuticals," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 269-274, May.
    6. Claire McKenna & Karl Claxton, 2011. "Addressing Adoption and Research Design Decisions Simultaneously," Medical Decision Making, , vol. 31(6), pages 853-865, November.
    7. Karl Claxton & Elisabeth Fenwick & Mark J. Sculpher, 2012. "Decision-making with Uncertainty: The Value of Information," Chapters, in: Andrew M. Jones (ed.), The Elgar Companion to Health Economics, Second Edition, chapter 51, Edward Elgar Publishing.
    8. Fumie Yokota & Kimberly M. Thompson, 2004. "Value of Information Literature Analysis: A Review of Applications in Health Risk Management," Medical Decision Making, , vol. 24(3), pages 287-298, June.
    9. A. E. Ades & S. Cliffe, 2002. "Markov Chain Monte Carlo Estimation of a Multiparameter Decision Model: Consistency of Evidence and the Accurate Assessment of Uncertainty," Medical Decision Making, , vol. 22(4), pages 359-371, August.
    10. John D. Graham, 2001. "Decision-analytic refinements of the precautionary principle," Journal of Risk Research, Taylor & Francis Journals, vol. 4(2), pages 127-141, April.
    11. Stefano Conti & Karl Claxton, 2008. "Dimensions of design space: a decision-theoretic approach to optimal research design," Working Papers 038cherp, Centre for Health Economics, University of York.
    12. A. E. Ades & G. Lu & K. Claxton, 2004. "Expected Value of Sample Information Calculations in Medical Decision Modeling," Medical Decision Making, , vol. 24(2), pages 207-227, March.
    13. Fumie Yokota & George Gray & James K. Hammitt & Kimberly M. Thompson, 2004. "Tiered Chemical Testing: A Value of Information Approach," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1625-1639, December.
    14. Kimberly M. Thompson & Dominika A. Kalkowska & Kamran Badizadegan, 2021. "No Role for Reintroducing OPV into the United States with Respect to Controlling COVID‐19 [Response to the letter to the Editor by Chumakov et al.]," Risk Analysis, John Wiley & Sons, vol. 41(2), pages 389-392, February.
    15. Fumie Yokota & Kimberly M. Thompson, 2004. "Value of Information Analysis in Environmental Health Risk Management Decisions: Past, Present, and Future," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 635-650, June.
    16. K. Claxton & P. J. Neumannn & S. S. Araki & M. C. Weinstein, "undated". "Bayesian Value-of-Information Analysis: An Application to a Policy Model of Alzheimer's Disease," Discussion Papers 00/39, Department of Economics, University of York.
    17. Deborah H. Bennett & Manuele D. Margni & Thomas E. McKone & Olivier Jolliet, 2002. "Intake Fraction for Multimedia Pollutants: A Tool for Life Cycle Analysis and Comparative Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 22(5), pages 905-918, October.
    18. N. J. Welton & A. E. Ades & D. M. Caldwell & T. J. Peters, 2008. "Research prioritization based on expected value of partial perfect information: a case‐study on interventions to increase uptake of breast cancer screening," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 171(4), pages 807-841, October.
    19. Edgar G. Hertwich & Thomas E. McKone & William S. Pease, 1999. "Parameter Uncertainty and Variability In Evaluative Fate and Exposure Models," Risk Analysis, John Wiley & Sons, vol. 19(6), pages 1193-1204, December.
    20. Vicki Bier, 2020. "The Role of Decision Analysis in Risk Analysis: A Retrospective," Risk Analysis, John Wiley & Sons, vol. 40(S1), pages 2207-2217, November.
    21. Sung, Hwansoo & Shortle, James S., 2006. "The Expected Value of Sample Information Analysis for Nonpoint Water Quality Management," 2006 Annual meeting, July 23-26, Long Beach, CA 21296, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    22. Sofia Dias & Alex J. Sutton & Nicky J. Welton & A. E. Ades, 2013. "Evidence Synthesis for Decision Making 6," Medical Decision Making, , vol. 33(5), pages 671-678, July.

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