IDEAS home Printed from https://ideas.repec.org/p/ipt/iptwpa/jrc96205.html
   My bibliography  Save this paper

Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing (MAFEIP) - Conceptual description of the Monitoring and Assessment Framework for the EIP on AHA

Author

Listed:

Abstract

After having identified a short list of candidate indicators for assessing the impact of the European Innovation Partnership on Active and Healthy Ageing (EIP on AHA) in the first and second reports on outcome indicators for MAFEIP, the next step in this project was to develop a quantitative approach that could be suited to establishing a link between candidate indicators and the EIP on AHA objectives. This report therefore conceptualises a model for estimating the impact of the Partnership's activities on its targets for health and sustainability of health and care system using the outcome indicators that were previously identified. In accordance with the EIP on AHA headline target of increasing the average healthy life expectancy of European citizens by two years by 2020, we took the methods to calculate Healthy Life Years (HLY) as a starting point, but adapted them to better accommodate the needs of MAFEIP. The rationale for this adaptation was to ensure the resulting model can adequately estimate the health impacts achieved by EIP on AHA commitments, and also to utilise data on indicators that are most frequently reported across EIP on AHA participants. The resulting model is based on a Markov process with three generic health states ('baseline health', 'deteriorated health' and 'death'), which can draw upon data from primary and secondary outcome indicators across populations, interventions, commitments and geographic domains. We discuss how the model's flexibility that allows it to be applied to different contexts could be enhanced further through the optional inclusion of additional health states or extensions for incorporating additional secondary indicators. We also discuss how to use the model for estimating the impact of activities delivered within the EIP on AHA on the sustainability of health and care systems in terms of the incremental impact of the interventions on health and care expenditure. We propose that the model should be implemented as a web-based monitoring tool to enable stakeholders within commitments to independently assess the impact of their respective interventions on health and sustainability of health and care systems, with the support and guidance of IPTS.

Suggested Citation

  • Fabienne Abadie & Christian Boehler, 2015. "Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing (MAFEIP) - Conceptual description of the Monitoring and Assessment Framework for the EIP on AHA," JRC Research Reports JRC96205, Joint Research Centre.
    • Handle: RePEc:ipt:iptwpa:jrc96205
    as

    Download full text from publisher

    File URL: https://publications.jrc.ec.europa.eu/repository/handle/JRC96205
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Birch, Stephen & Gafni, Amiram, 2003. "Economics and the evaluation of health care programmes: generalisability of methods and implications for generalisability of results," Health Policy, Elsevier, vol. 64(2), pages 207-219, May.
    2. Aaron A. Stinnett & John Mullahy, 1998. "Net Health Benefits," Medical Decision Making, , vol. 18(2_suppl), pages 68-80, April.
    3. Briggs, Andrew & Sculpher, Mark & Claxton, Karl, 2006. "Decision Modelling for Health Economic Evaluation," OUP Catalogue, Oxford University Press, number 9780198526629, Decembrie.
    4. 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.
    5. John Brazier & Yaling Yang & Aki Tsuchiya & Donna Rowen, 2010. "A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 11(2), pages 215-225, April.
    6. Weinstein, Milton C., 1988. "A QALY is a QALY is a QALY -- Or is it?," Journal of Health Economics, Elsevier, vol. 7(3), pages 289-290, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Christian Boehler & Fabienne Abadie, 2016. "Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing (MAFEIP) - Gap analysis," JRC Research Reports JRC101550, Joint Research Centre.

    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. David Brain & Ruth Tulleners & Xing Lee & Qinglu Cheng & Nicholas Graves & Rosana Pacella, 2019. "Cost-effectiveness analysis of an innovative model of care for chronic wounds patients," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-13, March.
    2. David Brain & Jonathan Mitchell & James O’Beirne, 2020. "Cost-effectiveness analysis of an outreach model of Hepatitis C Virus (HCV) assessment to facilitate HCV treatment in primary care," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-13, June.
    3. Henry Glick, 2011. "Sample Size and Power for Cost-Effectiveness Analysis (Part 1)," PharmacoEconomics, Springer, vol. 29(3), pages 189-198, March.
    4. Marta Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    5. Marta O. Soares & Luísa Canto e Castro, 2012. "Continuous Time Simulation and Discretized Models for Cost-Effectiveness Analysis," PharmacoEconomics, Springer, vol. 30(12), pages 1101-1117, December.
    6. Manuel Antonio Espinoza & Andrea Manca & Karl Claxton & Mark Sculpher, 2018. "Social value and individual choice: The value of a choice‐based decision‐making process in a collectively funded health system," Health Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 28-40, February.
    7. A. E. Ades & Karl Claxton & Mark Sculpher, 2006. "Evidence synthesis, parameter correlation and probabilistic sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 373-381, April.
    8. Jeff Round & Mike Paulden, 2018. "Incorporating equity in economic evaluations: a multi-attribute equity state approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(4), pages 489-498, May.
    9. Basu, Anirban & Jena, Anupam B. & Philipson, Tomas J., 2011. "The impact of comparative effectiveness research on health and health care spending," Journal of Health Economics, Elsevier, vol. 30(4), pages 695-706, July.
    10. Round, Jeff, 2012. "Is a QALY still a QALY at the end of life?," Journal of Health Economics, Elsevier, vol. 31(3), pages 521-527.
    11. 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.
    12. 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.
    13. 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.
    14. Clarke, Philip M. & Hayes, Alison J., 2009. "Measuring achievement: Changes in risk factors for cardiovascular disease in Australia," Social Science & Medicine, Elsevier, vol. 68(3), pages 552-561, February.
    15. 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.
    16. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.
    17. Jordan Amdahl & Jose Diaz & Arati Sharma & Jinhee Park & David Chandiwana & Thomas E Delea, 2017. "Cost-effectiveness of pazopanib versus sunitinib for metastatic renal cell carcinoma in the United Kingdom," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-18, June.
    18. Emma McIntosh, 2006. "Using Discrete Choice Experiments within a Cost-Benefit Analysis Framework," PharmacoEconomics, Springer, vol. 24(9), pages 855-868, September.
    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. Jing Voon Chen & Julia L. Higle & Michael Hintlian, 2018. "A systematic approach for examining the impact of calibration uncertainty in disease modeling," Computational Management Science, Springer, vol. 15(3), pages 541-561, October.

    More about this item

    Keywords

    EIP; Active and Healthy Ageing; EIP on AHA; indicators; monitoring; framework;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ipt:iptwpa:jrc96205. 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: Publication Officer (email available below). General contact details of provider: https://edirc.repec.org/data/ipjrces.html .

    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.