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Value of Information Literature Analysis: A Review of Applications in Health Risk Management

Author

Listed:
  • Fumie Yokota

    (Department of Health Policy and Management, Harvard School of Public Health, Cambridge, MA.)

  • Kimberly M. Thompson

    (Department of Health Policy and Management, Harvard School of Public Health, Cambridge, MA.)

Abstract

This article provides the first comprehensive review of value of information (VOI) analyses related to health risk management published in English in peer-reviewed journals by the end of 2001. VOI analysis represents a decision analytic technique that explicitly evaluates the benefit of collecting additional information to reduce or eliminate uncertainty. Through a content analysis of VOI applications, this article characterizes various attributes of VOI applications, shows the evolution of the methodology and advances in computing tools that allow analysis of increasingly complex problems, and suggests the need for some standardization of reporting methods and results. The authors’ analysis shows a lack of cross-fertilization across topic areas and the tendency of articles to focus on demonstrating the usefulness of the VOI approach rather than applications to actual management decisions. This article provides important insights for VOI applications in medical decision making.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:medema:v:24:y:2004:i:3:p:287-298
    DOI: 10.1177/0272989X04263157
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    References listed on IDEAS

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    Cited by:

    1. Peter I. Frazier & Warren B. Powell, 2010. "Paradoxes in Learning and the Marginal Value of Information," Decision Analysis, INFORMS, vol. 7(4), pages 378-403, December.
    2. repec:cup:judgdm:v:7:y:2012:i:2:p:119-148 is not listed on IDEAS
    3. L. Raso & S. V. Weijs & M. Werner, 2018. "Balancing Costs and Benefits in Selecting New Information: Efficient Monitoring Using Deterministic Hydro-economic Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 339-357, January.
    4. Jill Johnston & Jacqueline MacDonald Gibson, 2015. "Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making," IJERPH, MDPI, vol. 12(12), pages 1-18, November.
    5. 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.
    6. Oakley, Jeremy E. & Brennan, Alan & Tappenden, Paul & Chilcott, Jim, 2010. "Simulation sample sizes for Monte Carlo partial EVPI calculations," Journal of Health Economics, Elsevier, vol. 29(3), pages 468-477, May.
    7. Bjorn Meder & Jonathan D. Nelson, 2012. "Information search with situation-specific reward functions," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 7(2), pages 119-148, March.
    8. Silke Gabbert & Hans‐Peter Weikard, 2010. "A theory of chemicals regulation and testing," Natural Resources Forum, Blackwell Publishing, vol. 34(2), pages 155-164, May.
    9. Junggi Yang & Ungu Kang & Youngho Lee, 2016. "Clinical decision support system in medical knowledge literature review," Information Technology and Management, Springer, vol. 17(1), pages 5-14, March.
    10. Williams, Byron K. & Eaton, Mitchell J. & Breininger, David R., 2011. "Adaptive resource management and the value of information," Ecological Modelling, Elsevier, vol. 222(18), pages 3429-3436.
    11. Douglas J Bruggeman, 2015. "The Value of Learning about Natural History in Biodiversity Markets," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-21, December.
    12. Laura McCullagh & Cathal Walsh & Michael Barry, 2012. "Value-of-Information Analysis to Reduce Decision Uncertainty Associated with the Choice of Thromboprophylaxis after Total Hip Replacement in the Irish Healthcare Setting," PharmacoEconomics, Springer, vol. 30(10), pages 941-959, October.
    13. Byron K Williams & Fred A Johnson, 2018. "Value of sample information in dynamic, structurally uncertain resource systems," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-16, June.
    14. François Destandau & Youssef Zaiter, 2020. "Optimisation « économique » vs « physique » des réseaux de surveillance de la qualité de l'eau," Post-Print hal-03373478, HAL.
    15. Hans Olav Vogt Myklebust & Jo Eidsvik & Iver Bakken Sperstad & Debarun Bhattacharjya, 2020. "Value of Information Analysis for Complex Simulator Models: Application to Wind Farm Maintenance," Decision Analysis, INFORMS, vol. 17(2), pages 134-153, June.
    16. Toni Greif & Nikolai Stein & Christoph M. Flath, 2023. "Information Value Analysis for Real-Time Silo Fill-Level Monitoring," Interfaces, INFORMS, vol. 53(4), pages 283-294, July.
    17. Esther De Gourville & Radboud J. Duintjer Tebbens & Nalinee Sangrujee & Mark A. Pallansch & Kimberly M. Thompson, 2006. "Global Surveillance and the Value of Information: The Case of the Global Polio Laboratory Network," Risk Analysis, John Wiley & Sons, vol. 26(6), pages 1557-1569, December.
    18. 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.
    19. Janzwood, Scott, 2021. "R&D priority-setting for global catastrophic risks: The case of the NASA planetary defense mission," Research Policy, Elsevier, vol. 50(6).
    20. Wesley J. Marrero & Mariel S. Lavieri & Jeremy B. Sussman, 2021. "Optimal cholesterol treatment plans and genetic testing strategies for cardiovascular diseases," Health Care Management Science, Springer, vol. 24(1), pages 1-25, March.
    21. Brennan, Alan & Kharroubi, Samer A., 2007. "Efficient computation of partial expected value of sample information using Bayesian approximation," Journal of Health Economics, Elsevier, vol. 26(1), pages 122-148, January.

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