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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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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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  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,

  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

  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,

  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:

  24. 24.

    Document available at

  25. 25.

    The UK Department of Health Policy paper available at

  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

  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

  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 = http%3A%2

  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).


  • Allison M (2008) Is personalized medicine finally arriving? Nat Biotechnol 26:509–517

    Article  Google Scholar 

  • Annemans L, Redekop K, Payne K (2013) Current methodological issues in the economic assessment of personalized medicine. Value Health 16:20–26

    Article  Google Scholar 

  • Bassi J, Lau F (2013) Measuring value for money: a scoping review on economic evaluation of health information systems. J Am Med Inform Assoc 20(4):792–801

    Article  Google Scholar 

  • Behl AS, Goddard KA, Flottemesch TJ, Veenstra D, Meenan RT, Lin JS, Maciosek MV (2012) Cost-effectiveness analysis of screening for KRAS and BRAF mutations in metastatic colorectal cancer. J Natl Cancer Inst 104:1785–1795

    Article  Google Scholar 

  • Bobinac A (2012) Economic evaluations of health technologies: insights into the valuation and measurement of benefits. Erasmus University Rotterda, Rotterdam. ISBN 978-94-6169-250-4

    Google Scholar 

  • Bobinac A, van Exel NJA, Rutten FFH, Brouwer WBF (2013) Valuing QALY gains by applying a societal perspective. Health Econ 22(10):1272–1281

    Article  Google Scholar 

  • Bobinac A, van Exel NJA, Rutten FFH, Brouwer WBF (2014) The value of a QALY: individual willingness to pay for health gains under risk. Pharmacoeconomics 32:75–86

    Article  Google Scholar 

  • Brouwer WBF, Culyer AJ, van Exel NJA, Rutten FFH (2008) Welfarism vs. extra-welfarism. J Health Econ 27:325–338

    Article  Google Scholar 

  • Burns L, Orsini L, L’Italien G (2013) Value-based assessment of pharmacodiagnostic testing from early stage development to real-world use. Value Health 16:16–19

    Article  Google Scholar 

  • Byron SK, Crabb N, George E, Marlow M, Newland A (2014) The Health Technology Assessment of companion diagnostics: experience of NICE. Clin Cancer Res 20(6):1469–1476

    Article  Google Scholar 

  • Claxton K, Longo R, Longworth L, McCabe C, Wailoo A (2009) The value of innovation. Report by the Decision Support Unit. = Accessed 4 Apr 2014

  • Claxton K, Walker S, Palmer S, Sculpher M (2010) Appropriate perspectives for health care decisions. CHE Research Paper 54, Centre for Health Economics, University of York Accessed 5 Apr 2014

  • CVZ (College voor zorgverzekeringen) (2006) Dutch Guidelines for Pharmacoeconomic Research, Updated Version, Accessed 13 Jan 2014

  • CVZ (2009) Accessed 19 Jan 2014

  • Dakin HA, Devlin NJ, Odeyemi IA (2006) “Yes”, “No” or “Yes, but”? Multinomial modelling of NICE decision-making. Health Policy 77(3):352–367

    Article  Google Scholar 

  • Danzon P, Towse A (2002) The economics of gene therapy and of pharmacogenetics. Value Health 5:5–13

    Article  Google Scholar 

  • Dedes KJ, Szucs TD, Imesch P et al (2007) Cost-effectiveness of trastuzumab in the adjuvant treatment of early breast cancer: a model-based analysis of the HERA and FinHer trial. Ann Oncol 18(9):1493–1499

    Article  Google Scholar 

  • Devlin N, Parkin D (2004) Does NICE have a cost effectiveness threshold and what other factors influence its decisions? A binary choice analysis. Health Econ 13:437–452

    Article  Google Scholar 

  • Drummond M (2012) Twenty years of using economic evaluations for reimbursement decisions what have we achieved? CHE Research Paper. 1-16 Accessed 13 Jan 2014

  • Drummond MF, Stoddart GL, Torrance GW (1997) Methods for the economic evaluation of health care programmes, 2nd edn. Oxford University Press, Oxford

    Google Scholar 

  • European Science Foundation (2012) Personalised Medicine for the European Citizen – towards more precise medicine for the diagnosis, treatment and prevention of disease (iPM). Accessed 4 Apr 2014

  • Faulkner E, Annemans L, Garrison L et al (2012) Personalized Medicine Development and Reimbursement Working Group challenges in the development and reimbursement of personalized medicine—payer and manufacturer perspectives and implications for health economics and outcomes research: a report of the ISPOR Personalized Medicine Special Interest Group. Value Health 8:1162–1171

    Article  Google Scholar 

  • Ferrusi IL, Marshall AD, Kulin NA, Leighl NB, Phillips KA (2009) Looking back at 10 years of trastuzumab therapy: what is the role of HER2 testing? A systematic review of health economic analyses. Per Med Mar 6:193–215

    Article  Google Scholar 

  • Fisher ES, Bynum JP, Skinner JS (2009) Slowing the growth of health care costs — lessons from regional variation. N Engl J Med 360:849–852

    Article  Google Scholar 

  • Fishman PA, Hornbrook MC (2009) Assigning resources to health care use for health services research: options and consequences. Med Care 47(Suppl 1):S70–S75

    Google Scholar 

  • Freidlin B, McShane LM, Korn EL (2010) Randomized clinical trials with biomarkers: design issues. J Natl Cancer Inst 102:152–160

    Article  Google Scholar 

  • Frick KD (2010) Micro-costing quantity data collection methods. Med Care 47:76–81

    Article  Google Scholar 

  • Fridlyand J et al (2013) Considerations for the successful co-development of targeted cancer therapies and companion diagnostics. Nat Rev Drug Discov 12(10):743–755

    Article  Google Scholar 

  • Frueh FW (2013) Regulation, reimbursement, and the long road of implementation of personalized medicine—a perspective from the United States. Value Health 16(6):S27–S31

    Article  Google Scholar 

  • Garau M, Towse A, Garrison L et al (2013) Can and should value based pricing be applied to molecular diagnostics? Pers Med 10:61–72

    Article  Google Scholar 

  • Garnock-Jones KP, Keating GM, Scott LJ (2010) Trastuzumab: a review of its use as adjuvant treatment in human epidermal growth factor receptor 2 (HER2)-positive early breast cancer. Drugs 70:215–239

    Article  Google Scholar 

  • Garrison LP, Towse A (2014) Personalized medicine: pricing and reimbursement policies as a potential barrier to development and adoption, economics of. Encyclopedia of Health Econ, 484–490

    Google Scholar 

  • Gold MR, Siegel JE, Russell LB et al (1996) Cost-effectiveness in health and medicine. Oxford University Press, New York

    Google Scholar 

  • Goldberg P (2009) KRAS finding changes oncology practice but poses profound regulatory dilemma. Cancer Lett 35:1–8

    Google Scholar 

  • Gravelle H, Brouwer W, Niessen L, Postma M, Rutten F (2007) Discounting for economic evaluations: stepping forward toward optimal decision rules. Health Econ 16:307–317

    Article  Google Scholar 

  • Hamburg MA, Collins FS (2010) The path to personalized medicine. N Engl J Med 363(4):301–304

    Article  Google Scholar 

  • Herdman M, Gudex C, Lloyd A et al (2011) Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res 20:1727–1736

    Article  Google Scholar 

  • Hewitt RE (2011) Biobanking: the foundation of personalized medicine. Curr Opin Oncol 23(1):112–119

    Article  Google Scholar 

  • Johnson SG, Gruntowicz D, Chua T, Morlock RJ (2015) Financial analysis of CYP2C19 genotyping in patients receiving dual antiplatelet therapy following acute coronary syndrome and percutaneous coronary intervention. J Manag Care Spec Pharm 21(7):552–557

    Article  Google Scholar 

  • Kazi DS, Garber AM, Rashmee SU, Adams DA, Mell M (2014) Cost-effectiveness of genotype-guided and dual antiplatelet therapies in acute coronary syndrome. Ann Intern Med 160:221–232

    Article  Google Scholar 

  • Lamers LM, McDonnell J, Stalmeier PFM, Krabbe PFM, Busschbach JJV (2006) The Dutch tariff: results and arguments for an effective design for national EQ-5D valuations studies. Health Econ 215:1121–1132

    Article  Google Scholar 

  • Ma Q, Lu AY (2011) Pharmacogenetics, pharmacogenomics, and individualized medicine. Pharmacol Rev 63(2):437–459

    Article  Google Scholar 

  • Meckley LM, Neumann PJ (2010) Personalized medicine: factors influencing reimbursement. Health Policy 94(2):91–100

    Article  Google Scholar 

  • Merlin T, Farah C, Schubert C, Mitchell A, Hiller JE, Ryan P (2013) Assessing personalized medicines in Australia: a national framework for reviewing codependent technologies. Med Decis Making 33:333–342

    Article  Google Scholar 

  • Mooney G (1989) QALYs: are they enough? A health economist’s perspective. J Med Ethics 15:148–152

    Article  Google Scholar 

  • National Institute for Health and Clinical Excellence (NICE) (2011) Diagnostics Assessment Programme manual (DAP), from Accessed 13 Sept 2014

  • National Institute for Health and Clinical Excellence (NICE) (2013) Our guidance. Accessed 30 Sept 2014

  • Neumann PJ, Greenberg D (2009) Is the United States ready for QALYs? Health Aff 28:1366–1371

    Article  Google Scholar 

  • Neumann PJ, Cohen JT, Hammitt JK, Concannon TW, Auerbach HR, Fang C, Kent DM (2012) Willingness‐to‐pay for predictive tests with no immediate treatment implications: a survey of US residents. Health Econ 21(3):238–251

    Article  Google Scholar 

  • Olson JE, Bielinski SJ, Ryu E, Winkler EM, Takahashi PY, Pathak J, Cerhan JR (2014) Biobanks and personalized medicine. Clin Genet 86(1):50–55

    Article  Google Scholar 

  • Payne K, Annemans L (2013) Reflections on market access for personalized medicine: recommendations for Europe. Value Health 16:32–38

    Article  Google Scholar 

  • Payne K, Shabaruddin FH (2010) Cost-effectiveness analysis in pharmacogenomics. Pharmacogenomics 11(5):643–646

    Article  Google Scholar 

  • Perez EA, Romond EH, Suman VJ (2007) Updated results of the combined analysis of NCCTG N9831 and NSABP B-31 adjuvant chemotherapy with/without trastuzumab in patients with HER2-positive breast cancer. Proc Am Soc Clin Oncol 25(6s)

    Google Scholar 

  • Phillips KA, Marshall DA, Haas JS et al (2009) Clinical practice patterns and cost-effectiveness of HER2 testing strategies in breast cancer patients. Cancer 115:5166–5174

    Article  Google Scholar 

  • Rawlins MD, Barnett D, Stevens A (2010) Pharmacoeconomics: NICE’s approach to decision making. Br J Clin Pharmacol 70:346–349

    Article  Google Scholar 

  • Redekop K, Mladsi D (2013) The faces of personalized medicine: a framework for understanding its meaning and scope. Value Health 16:4–9

    Article  Google Scholar 

  • Russell LB (1999) Modelling for cost-effectiveness analysis. Stat Med 18:3235–3244

    Article  Google Scholar 

  • Shimazawa R, Ikeda M (2013) Are there any differences in the regulations of personalized medicine among the USA, EU, and Japan? Br J Clin Pharmacol 75:1365–1367

    Article  Google Scholar 

  • Simon R (2010) Clinical trial designs for evaluating the medical utility of prognostic and predictive biomarkers in oncology. Pers Med 7:33–47

    Article  Google Scholar 

  • Simon R, Roychowdhury S (2013) Implementing personalized cancer genomics in clinical trials. Nat Rev Drug Discov 12(5):358–369

    Article  Google Scholar 

  • Skedgel C, Rayson D, Younis T (2013) Is adjuvant trastuzumab a cost-effective therapy for HER-2/neu-positive T1bN0 breast cancer? Ann Oncol 24:1834–1840

    Article  Google Scholar 

  • Szende A, Oppe M, Devlin N (2007) EQ-5D value sets: inventory, comparative review and user guide. Springer, Dordrecht

    Book  Google Scholar 

  • Towse A, Garrison LP (2013) Economic incentives for evidence generation: promoting an efficient path to personalized medicine. Value Health 16:39–43

    Article  Google Scholar 

  • Towse A, Ossa D, Veenstra D, Carlson J, Garrison L (2013) Understanding the economic value of molecular diagnostic tests: case studies and lessons learned. J Pers Med 3(4):288–305

    Article  Google Scholar 

  • UK Department of Health (2014) Personalised health and care 2020. Policy paper Accessed 15 Dec 2014

  • US Food and drugs administration (2014) Paving the way for personalized medicine – FDA’s role in a new era of medical product development. Policy paper Accessed 5 Jan 2015

  • Vegter S, Boersma C, Rozenbaum M, Wilffert B, Navis G, Postma MJ (2008) Pharmacoeconomic evaluations of pharmacogenetic and genomic screening programmes. Pharmacoeconomics 26:569–58710

    Article  Google Scholar 

  • Wolff AC, Hammond ME, Schwartz JN et al (2007) American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol 25:118–145

    Article  Google Scholar 

  • Wong JB (2014) Evidence-based medicine, pharmacogenetics, and antiplatelet therapy decision making for acute coronary syndrome. Ann Intern Med 160:284–285

    Google Scholar 

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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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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.

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