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Economic Evaluations of Personalized Health Technologies: An Overview of Emerging Issues

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Personalized Medicine

Part of the book series: Europeanization and Globalization ((EAG,volume 2))

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Abstract

Personalized medicine seeks to integrate data on the entire dynamic biological makeup of each individual as well as the environmental and lifestyle factors that interface with this makeup to generate a complex, individual phenotype. The information about the individual’s phenotype enables physicians to prescribe more effective treatments, hence avoiding ineffective treatments with known side effects, reducing trial-and-error inefficiencies that may increase health care costs on one hand and cause harm to patients on the other. Personalized medicine is generating increasingly tailored interventions that also need to be carefully assessed to determine their cost-effectiveness. Because the vast majority of conventionally applied health technologies are tested on broad populations and prescribed using statistical averages, the approach of personalized medicine may prove challenging for the conventional methods of economic evaluations because of its increasing focus on the individual patient. This chapter aims to bring a concise overview of some of the methodological issues related to the economic assessment of personalized medicine and the related outcomes research, which are only now starting to be addressed. It puts forward examples of economic evaluations of personalized medicine and highlights some of the areas in which future methodological work may be required, hence contributing to a growing debate on economic evaluations of personalized medical products.

Ana Bobinac, Ph.D., Institute of Health Policy and Management & the Institute for Health Technology Assessment, Erasmus University Rotterdam, the Netherlands.

Professor Maja Vehovec, Ph.D., The Institute of Economics, Zagreb, Croatia.

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Notes

  1. 1.

    For further details, see Drummond et al. (1997).

  2. 2.

    For more details, National Institute for Health and Care Excellence (NICE) (2013).

  3. 3.

    Further discussion on this topic available from Drummond (2012), pp. 1–16.

  4. 4.

    For examples of country-specific guidelines, see NICE (2013) and Netherlands College van Zorgverzekeringen (CVZ) (2006).

  5. 5.

    This definition is available in the brochure titled “Personalised Medicine for the European Citizen – Towards more precise medicine for the diagnosis, treatment and prevention of disease” published by the European Science Foundation in 2012.

  6. 6.

    Examples of the debates revolving around the definition of personalized medicine available in Faulkner et al. (2012), pp. 1162–1171.

  7. 7.

    The definition available at FDA website, http://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm301431.htm.

  8. 8.

    For further insight into the debate, see, for instance, US Food and Drugs Administration (FDA), 2014 Policy paper titled “Paving the Way for Personalized Medicine – FDA’s Role in a New Era of Medical Product Development,” available at http://www.fda.gov/downloads/ScienceResearch/SpecialTopics/PersonalizedMedicine/UCM372421.pdf.

  9. 9.

    Technical efficiency refers to maximizing the level of output from a given level of input.

  10. 10.

    For instance, by Mooney (1989) and Neumann and Greenberg (2009).

  11. 11.

    Interventions compete for implementation; allocative efficiency is achieved when it is impossible to increase overall benefits produced by the health care system by reallocating resources between interventions. This occurs when the ratio of marginal benefits to marginal costs is equal across health care interventions in the system.

  12. 12.

    User guide is available on the Euro-QoL website, http://www.euroqol.org/.

  13. 13.

    The five-level instrument is being developed; for more details, see, for instance, Herdman et al. (2011), pp. 1727–1736.

  14. 14.

    For details and further analysis on costing methods, see Gold et al. (1996), Fishman and Hornbrook (2009), pp. 70–75; and Frick (2010), pp. 76–81.

  15. 15.

    More debate on the important topic of an appropriate perspective for economic evaluations available in Gold et al. (1996); Brouwer et al. (2008), pp. 325–338; Gravelle et al. 2007, pp. 307–317; Claxton et al. (2010); Bobinac (2012).

  16. 16.

    Further details available in Bobinac (2012).

  17. 17.

    For further discussion on the monetary value of health gains, see Bobinac (2012).

  18. 18.

    Examples of empirical studies are Bobinac et al. (2013), pp. 1272–1281; and Bobinac et al. (2014), pp. 75–86.

  19. 19.

    Further details on the threshold used in the UK, see, for instance, Rawlins et al. (2010), pp. 346–349.

  20. 20.

    As shown, for instance, by Devlin and Parkin (2004), pp. 437–452; Dakin et al. (2006), pp. 352–367.

  21. 21.

    Russell (1999), pp. 3235–3244.

  22. 22.

    Byron et al. (2014), pp. 1469–1476.

  23. 23.

    For further details, we refer the reader to Kazi et al. (2014), pp. 221–232, and also the FDA website: http://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm301431.htm.

  24. 24.

    Document available at http://www.nice.org.uk/Media/Default/About/what-we-do/NICE-guidance/NICE-diagnostics-guidance/Diagnostics-assessment-programme-manual.pdf.

  25. 25.

    The UK Department of Health Policy paper available at https://www.gov.uk/government/publications/personalised-health-and-care-2020/using-data-and-technology-to-transform-outcomes-for-patients-and-citizens.

  26. 26.

    Merlin et al. (2013), pp. 333–342, provide an overview of the Australian guidelines.

  27. 27.

    This idea is further discussed by Annemans et al. (2013), pp. 20–26, and Payne and Annemans (2013), pp. 32–38.

  28. 28.

    Discussed further by Merlin et al. (2013), pp. 333–342.

  29. 29.

    The issue is further discussed in NICE DAP document available at http://www.nice.org.uk/Media/Default/About/what-we-do/NICE-guidance/NICE-diagnostics-guidance/Diagnostics-assessment-programme-manual.pdf.

  30. 30.

    NICE DAP (2011), p. 8.

  31. 31.

    As discussed by Phillips et al. (2009), pp. 5166–5174, and Ferrusi et al. (2009), pp. 193–215.

  32. 32.

    Further debate available in Byron et al. (2014), pp. 1469–1476.

  33. 33.

    The discussion on the relation between genetic variations and drug response, see, for instance, Hamburg and Collins (2010), pp. 301–304, Ma and Lu (2011), pp. 437–459.

  34. 34.

    Further details available in Ferrusi et al. (2009), pp. 193–215.

  35. 35.

    Further information available at their website, at http://personalizedmedicine.partners.org/.

  36. 36.

    The review on the topic of value of information systems is provided by Bassi and Lau (2013), pp. 792–801.

  37. 37.

    As discussed, from various perspectives by different authors, e.g., Goldberg (2009), pp. 1–8; Hamburg and Collins (2010), pp. 301–304; Annemans et al. (2013), pp. 20–26.

  38. 38.

    As reviewed by Payne and Shabaruddin (2010), pp. 643–646.

  39. 39.

    A problem highlighted by various authors, such as Vegter et al. (2008), pp. 569–587; Phillips et al. (2009), pp. 5166–5174; and Wong (2014), pp. 284–285.

  40. 40.

    For further details, see Allison (2008), pp. 9–517.

  41. 41.

    A problem recognized by many authors, e.g., Hamburg and Collins (2010), pp. 301–304; Freidlin et al. (2010); Simon (2010), pp. 33–47; Simon and Roychowdhury (2013), pp. 358–369.

  42. 42.

    Danzon and Towse (2002), pp. 5–13.

  43. 43.

    For further discussion on this issue, we refer readers to Frueh (2013), pp. S21–S37; and Garrison and Towse (2014), pp. 484–490; Burns et al. (2013), pp. 16–19.

  44. 44.

    Payne and Annemans (2013), pp. 32–38; Towse et al. (2013), pp. 288–305.

  45. 45.

    Frueh (2013), pp. S21–S37.

  46. 46.

    Annemans et al. (2013), pp. 20–26.

  47. 47.

    For further discussion on the topic of value-based pricing for molecular diagnostics, also see Garau et al. (2013), pp. 61–72.

  48. 48.

    Garrison and Towse (2014), pp. 484–490.

  49. 49.

    For further discussion, see Claxton et al. (2009), report by the Decision Support Unit available at https://www.nice.org.uk/proxy/?sourceUrl = http%3A%2 F%2Fwww.nice.org.uk%2Fmedia%2FED8%2F7A%2FNICESubmissionAppendix.pdf.

  50. 50.

    As noted by other authors as well, such as Perez et al. (2007), p. 25.

  51. 51.

    As shown by Wolff et al. (2007), pp. 118–145.

  52. 52.

    As discussed, for instance, by Fridlyand et al. (2013).

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Acknowledgements

This work is part of the VENI research programme, which is financed by the Netherlands Organisation for Scientific Research (NWO). The researchers were free in study design, data collection, analysis and interpretation, as well as writing and submitting the manuscript for publication. The views expressed in this chapter are those of the authors.

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  1. Institute of Health Policy and Management & the Institute for Health Technology Assessment, Erasmus University Rotterdam, Rotterdam, The Netherlands

    Ana Bobinac Ph.D.

  2. The Institute of Economics, Zagreb, Croatia

    Maja Vehovec Ph.D.

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  1. Jean Monnet Department of European Public Law, University of Rijeka, Rijeka, Croatia

    Nada Bodiroga-Vukobrat

  2. Croatian Academy of Sciences and Arts, Rijeka, Croatia

    Daniel Rukavina

  3. Department of Biotechnology, University of Rijeka , Rijeka, Croatia

    Krešimir Pavelić

  4. University of Applied Sciences, Hochschule für öffentliche Verwaltung und Finanzen Ludwigsburg, Ludwigsburg, Germany

    Gerald G. Sander

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Bobinac, A., Vehovec, M. (2016). Economic Evaluations of Personalized Health Technologies: An Overview of Emerging Issues. In: Bodiroga-Vukobrat, N., Rukavina, D., Pavelić, K., Sander, G. (eds) Personalized Medicine. Europeanization and Globalization, vol 2. Springer, Cham. https://doi.org/10.1007/978-3-319-39349-0_7

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