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The impact of using different imputation methods for missing quality of life scores on the estimation of the cost‐effectiveness of lung‐volume‐reduction surgery

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  • David K. Blough
  • Scott Ramsey
  • Sean D. Sullivan
  • Roger Yusen

Abstract

A post hoc analysis of data from a prospective cost‐effectiveness analysis (CEA) conducted alongside a randomized controlled trial (National Emphysema Treatment Trial – NETT) was used to assess the impact of using different imputation methods for missing quality of life data on the estimation of the incremental cost‐effectiveness ratio (ICER). The NETT compared lung‐volume‐reduction surgery plus medical therapy with medical therapy alone in patients with severe chronic obstructive pulmonary disease due to emphysema. One thousand sixty‐six patients were followed for up to 3 years after randomization. The cost per quality‐adjusted life‐year gained was obtained, computing costs from a societal perspective and using the self‐administered Quality of Well Being questionnaire to measure quality of life. Different methods of imputation resulted in substantial differences in ICERs as well as differences in estimates of the uncertainty in the point estimates as reflected in the CEA acceptability curves. Paradoxically, the use of a conservative single imputation method resulted in relatively less uncertainty (anticonservative) about the ICER. Owing to the effects of different imputation methods for missing quality of life data on the estimation of the ICER, we recommend use of a minimum of two imputation methods that always include multiple imputation. Copyright © 2008 John Wiley & Sons, Ltd.

Suggested Citation

  • David K. Blough & Scott Ramsey & Sean D. Sullivan & Roger Yusen, 2009. "The impact of using different imputation methods for missing quality of life scores on the estimation of the cost‐effectiveness of lung‐volume‐reduction surgery," Health Economics, John Wiley & Sons, Ltd., vol. 18(1), pages 91-101, January.
    • Handle: RePEc:wly:hlthec:v:18:y:2009:i:1:p:91-101
    DOI: 10.1002/hec.1347
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    References listed on IDEAS

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    1. Ting Lin, 2006. "Missing Data Imputation in Quality-of-Life Assessment," PharmacoEconomics, Springer, vol. 24(9), pages 917-925, September.
    2. Horton N. J. & Lipsitz S. R., 2001. "Multiple Imputation in Practice: Comparison of Software Packages for Regression Models With Missing Variables," The American Statistician, American Statistical Association, vol. 55, pages 244-254, August.
    3. Jan B. Oostenbrink & Maiwenn J. Al, 2005. "The analysis of incomplete cost data due to dropout," Health Economics, John Wiley & Sons, Ltd., vol. 14(8), pages 763-776, August.
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    1. Lukas Kwietniewski & Mareike Heimeshoff & Jonas Schreyögg, 2017. "Estimation of a physician practice cost function," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(4), pages 481-494, May.
    2. Richard Grieve & John Cairns & Simon G. Thompson, 2010. "Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 939-954, August.
    3. Bernhard Michalowsky & Wolfgang Hoffmann & Kevin Kennedy & Feng Xie, 2020. "Is the whole larger than the sum of its parts? Impact of missing data imputation in economic evaluation conducted alongside randomized controlled trials," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 21(5), pages 717-728, July.
    4. Heiko Stüber & Markus M. Grabka & Daniel D. Schnitzlein, 2023. "A tale of two data sets: comparing German administrative and survey data using wage inequality as an example," Journal for Labour Market Research, Springer;Institute for Employment Research/ Institut für Arbeitsmarkt- und Berufsforschung (IAB), vol. 57(1), pages 1-18, December.
    5. Rita Faria & Manuel Gomes & David Epstein & Ian White, 2014. "A Guide to Handling Missing Data in Cost-Effectiveness Analysis Conducted Within Randomised Controlled Trials," PharmacoEconomics, Springer, vol. 32(12), pages 1157-1170, December.
    6. Mohamed El Alili & Johanna M. van Dongen & Jonas L. Esser & Martijn W. Heymans & Maurits W. van Tulder & Judith E. Bosmans, 2022. "A scoping review of statistical methods for trial‐based economic evaluations: The current state of play," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2680-2699, December.

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