IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v113y2016ipbp454-459.html
   My bibliography  Save this article

Simulating healthcare quality innovation based on a novel medical treatment: The case of Hepatitis-C in Europe

Author

Listed:
  • Zsifkovits, Martin
  • Zsifkovits, Johannes
  • Pickl, Stefan W.

Abstract

In 2014, a novel medication for treating Hepatitis C virus (HCV) infections caused severe difficulties for European decision makers in the public medical sector. Even though new drugs cure HCV in nearly all cases, related costs in the short run are extremely high. Thus, the estimation of overall costs for the national healthcare systems was of great importance for profound far-reaching decisions on policies regarding the medication and their reimbursement. As this budget estimation is extremely difficult due to the complexity of the virus spread and the existence of further discomforts that lead to additional costs, a new microsimulation model was developed that considers the problem from an individual's perspective and finally aggregates numbers on the macro level. While developing the model, general insights into the cost burden due to the new medication for the next 3years were generated. Using the introduced model, a decision maker is able to test for impact of one financial unit in several policies in order to maximize the overall benefit for the healthcare system. As initial results imply the need to change current reimbursement strategies in Europe, further research demand is discussed at the end of this article.

Suggested Citation

  • Zsifkovits, Martin & Zsifkovits, Johannes & Pickl, Stefan W., 2016. "Simulating healthcare quality innovation based on a novel medical treatment: The case of Hepatitis-C in Europe," Technological Forecasting and Social Change, Elsevier, vol. 113(PB), pages 454-459.
    • Handle: RePEc:eee:tefoso:v:113:y:2016:i:pb:p:454-459
    DOI: 10.1016/j.techfore.2016.07.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162516301573
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2016.07.013?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alexander Gutfraind & Basmattee Boodram & Nikhil Prachand & Atesmachew Hailegiorgis & Harel Dahari & Marian E Major, 2015. "Agent-Based Model Forecasts Aging of the Population of People Who Inject Drugs in Metropolitan Chicago and Changing Prevalence of Hepatitis C Infections," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-23, September.
    2. Kwakkel, Jan H. & Pruyt, Erik, 2013. "Exploratory Modeling and Analysis, an approach for model-based foresight under deep uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 419-431.
    3. Sun-Young Kim & Sue Goldie, 2008. "Cost-Effectiveness Analyses of Vaccination Programmes," PharmacoEconomics, Springer, vol. 26(3), pages 191-215, March.
    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. Škare, Marinko & Soriano, Domingo Riberio & Porada-Rochoń, Małgorzata, 2021. "Impact of COVID-19 on the travel and tourism industry," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
    2. Kim, Rachel H. & Gaukler, Gary M. & Lee, Chang Won, 2016. "Improving healthcare quality: A technological and managerial innovation perspective," Technological Forecasting and Social Change, Elsevier, vol. 113(PB), pages 373-378.

    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. Basmattee Boodram & Mary Ellen Mackesy-Amiti & Aditya Khanna & Bryan Brickman & Harel Dahari & Jonathan Ozik, 2022. "People who inject drugs in metropolitan Chicago: A meta-analysis of data from 1997-2017 to inform interventions and computational modeling toward hepatitis C microelimination," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-17, January.
    2. Elizabeth Gibson & Tugrul Daim & Edwin Garces & Marina Dabic, 2018. "Technology Foresight: A Bibliometric Analysis to Identify Leading and Emerging Methods," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 12(1), pages 6-24.
    3. Bethany Robinson & Jonathan D. Herman, 2019. "A framework for testing dynamic classification of vulnerable scenarios in ensemble water supply projections," Climatic Change, Springer, vol. 152(3), pages 431-448, March.
    4. Auping, Willem L. & Pruyt, Erik & de Jong, Sijbren & Kwakkel, Jan H., 2016. "The geopolitical impact of the shale revolution: Exploring consequences on energy prices and rentier states," Energy Policy, Elsevier, vol. 98(C), pages 390-399.
    5. Olivier Ethgen & Baudouin Standaert, 2012. "Population–versus Cohort–Based Modelling Approaches," PharmacoEconomics, Springer, vol. 30(3), pages 171-181, March.
    6. Georgios Tsaples & Jason Papathanasiou & Andreas C. Georgiou, 2022. "An Exploratory DEA and Machine Learning Framework for the Evaluation and Analysis of Sustainability Composite Indicators in the EU," Mathematics, MDPI, vol. 10(13), pages 1-27, June.
    7. Hidayatno, Akhmad & Jafino, Bramka Arga & Setiawan, Andri D. & Purwanto, Widodo Wahyu, 2020. "When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles," Energy Policy, Elsevier, vol. 138(C).
    8. Seyed Ahmad Reza Mir Mohammadi Kooshknow & Rob den Exter & Franco Ruzzenenti, 2020. "An Exploratory Agent-Based Modeling Analysis Approach to Test Business Models for Electricity Storage," Energies, MDPI, vol. 13(7), pages 1-14, April.
    9. Luciano Raso & Jan Kwakkel & Jos Timmermans, 2019. "Assessing the Capacity of Adaptive Policy Pathways to Adapt on Time by Mapping Trigger Values to Their Outcomes," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    10. van Ackere, Ann & Schulz, Peter J., 2020. "Explaining vaccination decisions: A system dynamics model of the interaction between epidemiological and behavioural factors," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    11. Andrija S Grustam & Nasuh Buyukkaramikli & Ron Koymans & Hubertus J M Vrijhoef & Johan L Severens, 2019. "Value of information analysis in telehealth for chronic heart failure management," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-23, June.
    12. Robert Ward & James Houghton & Ivan A. Perl, 2015. "SDXchange: stand-alone translators to enable XMILE model adaptation, transportation, and exchange," System Dynamics Review, System Dynamics Society, vol. 31(1-2), pages 86-95, January.
    13. Santos, Maria João & Ferreira, Paula & Araújo, Madalena, 2016. "A methodology to incorporate risk and uncertainty in electricity power planning," Energy, Elsevier, vol. 115(P2), pages 1400-1411.
    14. Anna K. Lugnér & Sido D. Mylius & Jacco Wallinga, 2010. "Dynamic versus static models in cost‐effectiveness analyses of anti‐viral drug therapy to mitigate an influenza pandemic," Health Economics, John Wiley & Sons, Ltd., vol. 19(5), pages 518-531, May.
    15. Anthony Newall & Mark Jit & Philippe Beutels, 2012. "Economic Evaluations of Childhood Influenza Vaccination," PharmacoEconomics, Springer, vol. 30(8), pages 647-660, August.
    16. da Silva Stefano, Gustavo & Antunes, Tiago dos Santos & Lacerda, Daniel Pacheco & Wolf Motta Morandi, Maria Isabel & Piran, Fabio Sartori, 2022. "The impacts of inventory in transfer pricing and net income: Differences between traditional accounting and throughput accounting," The British Accounting Review, Elsevier, vol. 54(2).
    17. Kolosz, B.W. & Athanasiadis, I.N. & Cadisch, G. & Dawson, T.P. & Giupponi, C. & Honzák, M. & Martinez-Lopez, J. & Marvuglia, A. & Mojtahed, V. & Ogutu, K.B.Z. & Van Delden, H. & Villa, F. & Balbi, S., 2018. "Conceptual advancement of socio-ecological modelling of ecosystem services for re-evaluating Brownfield land," Ecosystem Services, Elsevier, vol. 33(PA), pages 29-39.
    18. Eker, Sibel & van Daalen, Els, 2015. "A model-based analysis of biomethane production in the Netherlands and the effectiveness of the subsidization policy under uncertainty," Energy Policy, Elsevier, vol. 82(C), pages 178-196.
    19. Kokshagina, Olga & Gillier, Thomas & Cogez, Patrick & Le Masson, Pascal & Weil, Benoit, 2017. "Using innovation contests to promote the development of generic technologies," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 152-164.
    20. Deuten, Sebastiaan & Gómez Vilchez, Jonatan J. & Thiel, Christian, 2020. "Analysis and testing of electric car incentive scenarios in the Netherlands and Norway," Technological Forecasting and Social Change, Elsevier, vol. 151(C).

    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:eee:tefoso:v:113:y:2016:i:pb:p:454-459. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.