IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0040995.html
   My bibliography  Save this article

Applying the Net-Benefit Framework for Analyzing and Presenting Cost-Effectiveness Analysis of a Maternal and Newborn Health Intervention

Author

Listed:
  • Sennen Hounton
  • David Newlands

Abstract

Background: Coverage of maternal and newborn health (MNH) interventions is often influenced by important determinants and decision makers are often concerned with equity issues. The net-benefit framework developed and applied alongside clinical trials and in pharmacoeconomics offers the potential for exploring how cost-effectiveness of MNH interventions varies at the margin by important covariates as well as for handling uncertainties around the ICER estimate. Aim: We applied the net-benefit framework to analyze cost-effectiveness of the Skilled Care Initiative and assessed relative advantages over a standard computation of incremental cost effectiveness ratios. Methods: Household and facility surveys were carried out from January to July 2006 in Ouargaye district (where the Skilled Care Initiative was implemented) and Diapaga (comparison site) district in Burkina Faso. Pregnancy-related and perinatal mortality were retrospectively assessed and data were collected on place of delivery, education, asset ownership, place, and distance to health facilities, costs borne by households for institutional delivery, and cost of standard provision of maternal care. Descriptive and regression analyses were performed. Results: There was a 30% increase in institutional births in the intervention district compared to 10% increase in comparison district, and a significant reduction of perinatal mortality rates (OR 0.75, CI 0.70−0.80) in intervention district. The incremental cost for achieving one additional institutional delivery in Ouargaye district compared to Diapaga district was estimated to be 170 international dollars and varied significantly by covariates. However, the joint probability distribution (net-benefit framework) of the effectiveness measure (institutional delivery), the cost data and covariates indicated distance to health facilities as the single most important determinant of the cost-effectiveness analysis with implications for policy making. Conclusion: The net-benefit framework, the application of which requires household-level effects and cost data, has proven more insightful (than traditional ICER) in presenting and interpreting cost-effectiveness results of the Skilled Care Initiative.

Suggested Citation

  • Sennen Hounton & David Newlands, 2012. "Applying the Net-Benefit Framework for Analyzing and Presenting Cost-Effectiveness Analysis of a Maternal and Newborn Health Intervention," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-8, July.
    • Handle: RePEc:plo:pone00:0040995
    DOI: 10.1371/journal.pone.0040995
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0040995
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0040995&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0040995?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
    2. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits: A New Framework for the Analysis of Uncertainty in Cost-Effectiveness Analysis," NBER Technical Working Papers 0227, National Bureau of Economic Research, Inc.
    3. Drummond, Michael F. & Sculpher, Mark J. & Torrance, George W. & O'Brien, Bernie J. & Stoddart, Greg L., 2005. "Methods for the Economic Evaluation of Health Care Programmes," OUP Catalogue, Oxford University Press, edition 3, number 9780198529453.
    4. Elisabeth Fenwick & Karl Claxton & Mark Sculpher, 2001. "Representing uncertainty: the role of cost‐effectiveness acceptability curves," Health Economics, John Wiley & Sons, Ltd., vol. 10(8), pages 779-787, December.
    5. Hoch, Jeffrey S. & Blume, Jeffrey D., 2008. "Measuring and illustrating statistical evidence in a cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 27(2), pages 476-495, March.
    6. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    7. Claxton, Karl, 1999. "The irrelevance of inference: a decision-making approach to the stochastic evaluation of health care technologies," Journal of Health Economics, Elsevier, vol. 18(3), pages 341-364, June.
    8. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430, July.
    9. Jeffrey Hoch & Carolyn Dewa, 2007. "Lessons from Trial-Based Cost-Effectiveness Analyses of Mental Health Interventions," PharmacoEconomics, Springer, vol. 25(10), pages 807-816, October.
    10. Andrew Briggs & Paul Fenn, 1998. "Confidence intervals or surfaces? Uncertainty on the cost‐effectiveness plane," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 723-740, December.
    11. Laura Ternent & Paul McNamee & David Newlands & Danielle Belemsaga & Adjima Gbangou & Suzanne Cross, 2010. "Willingness to pay for maternal health outcomes," Applied Health Economics and Health Policy, Springer, vol. 8(2), pages 99-109, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hoch, Jeffrey S. & Blume, Jeffrey D., 2008. "Measuring and illustrating statistical evidence in a cost-effectiveness analysis," Journal of Health Economics, Elsevier, vol. 27(2), pages 476-495, March.
    2. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333, March.
    3. Elamin H. Elbasha, 2005. "Risk aversion and uncertainty in cost‐effectiveness analysis: the expected‐utility, moment‐generating function approach," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 457-470, May.
    4. Casey Quinn, 2005. "Generalisable regression methods for costeffectiveness using copulas," Health, Econometrics and Data Group (HEDG) Working Papers 05/13, HEDG, c/o Department of Economics, University of York.
    5. Niklas Zethraeus & Magnus Johannesson & Bengt Jönsson & Mickael Löthgren & Magnus Tambour, 2003. "Advantages of Using the Net-Benefit Approach for Analysing Uncertainty in Economic Evaluation Studies," PharmacoEconomics, Springer, vol. 21(1), pages 39-48, January.
    6. Emma McIntosh, 2006. "Using Discrete Choice Experiments within a Cost-Benefit Analysis Framework," PharmacoEconomics, Springer, vol. 24(9), pages 855-868, September.
    7. Helen Dakin & Sarah Wordsworth, 2013. "Cost‐Minimisation Analysis Versus Cost‐Effectiveness Analysis, Revisited," Health Economics, John Wiley & Sons, Ltd., vol. 22(1), pages 22-34, January.
    8. 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.
    9. Klemen Naveršnik, 2015. "Output correlations in probabilistic models with multiple alternatives," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 133-139, March.
    10. Andrea Manca & Nigel Rice & Mark J. Sculpher & Andrew H. Briggs, 2005. "Assessing generalisability by location in trial‐based cost‐effectiveness analysis: the use of multilevel models," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 471-485, May.
    11. Simon Eckermann & Andrew Willan, 2011. "Presenting Evidence and Summary Measures to Best Inform Societal Decisions When Comparing Multiple Strategies," PharmacoEconomics, Springer, vol. 29(7), pages 563-577, July.
    12. Mohan V. Bala & Gary A. Zarkin & Josephine Mauskopf, 2008. "Presenting results of probabilistic sensitivity analysis: the incremental benefit curve," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 435-440, March.
    13. Nikki McCaffrey & Meera Agar & Janeane Harlum & Jonathon Karnon & David Currow & Simon Eckermann, 2015. "Better Informing Decision Making with Multiple Outcomes Cost-Effectiveness Analysis under Uncertainty in Cost-Disutility Space," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-19, March.
    14. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216, February.
    15. Shiell, Alan & Rush, Bonnie, 2003. "Can willingness to pay capture the value of altruism? An exploration of Sen's notion of commitment," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 32(6), pages 647-660, December.
    16. 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.
    17. Simon Eckermann & Tim Coelli, 2008. "Including quality attributes in a model of health care efficiency: A net benefit approach," CEPA Working Papers Series WP032008, School of Economics, University of Queensland, Australia.
    18. Frank G. Sandmann & Julie V. Robotham & Sarah R. Deeny & W. John Edmunds & Mark Jit, 2018. "Estimating the opportunity costs of bed‐days," Health Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 592-605, March.
    19. Martin Henriksson & Fredrik Lundgren & Per Carlsson, 2006. "Informing the efficient use of health care and health care research resources ‐ the case of screening for abdominal aortic aneurysm in Sweden," Health Economics, John Wiley & Sons, Ltd., vol. 15(12), pages 1311-1322, December.
    20. Rachael L. Fleurence, 2007. "Setting priorities for research: a practical application of 'payback' and expected value of information," Health Economics, John Wiley & Sons, Ltd., vol. 16(12), pages 1345-1357.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0040995. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.