Accessible Requires Authentication Published by De Gruyter July 5, 2013

Economic Perspectives on Personalized Health Care and Prevention

Kathryn A. Phillips, Julie Ann Sakowski, Su-Ying Liang and Ninez A. Ponce


The objective of this paper is to provide an overview of economic evaluation of personalized medicine, focusing particularly on the use of cost-effectiveness analysis and other methods of valuation. We draw on insights from the literature and our work at the University of California, San Francisco Center for Translational and Policy Research on Personalized Medicine (TRANSPERS). We begin with a discussion of why personalized medicine is of interest and challenges to adoption, whether personalized medicine is different enough to require different evaluation approaches, and what is known about the economics of personalized medicine. We then discuss insights from TRANSPERS research and six areas for future research:

  1. Develop and Apply Multiple Methods of Assessing Value

  2. Identify Key Factors in Determining the Value of Personalized Medicine

  3. Use Real World Perspectives in Economic Analyses

  4. Consider Patient Heterogeneity and Diverse Populations in Economic Analyses

  5. Prepare for Upcoming Challenges of Assessing Value of Emerging Technologies

  6. Incorporate Behavioral Economics into Value Assessments

Corresponding author: Kathryn A. Phillips, University of California, San Francisco – Department of Clinical Pharmacy, 3333 California Street Box 0613, San Francisco, CA 94143, USA, Phone: +(415) 502-8271, e-mail:


Armstrong, K. (2012) “Can Genomics Bend the Cost Curve?” Journal of The American Medical Association, 307(10):1031–1032. Search in Google Scholar

Beaulieu, M., S. de Denus and J. Lachaine (2010) “Systematic Review of Pharmacoeconomic Studies of Pharmacogenomic Tests,” Pharmacogenomics, 11(11):1573–1590. Search in Google Scholar

Bloss, C. S., N. J. Schork and E. J. Topol (2011) “Effect of Direct-to-Consumer Genomewide Profiling to Assess Disease Risk,” New England Journal of Medicine, 364(6):524–534. Search in Google Scholar

Bridges, J. F., A. B. Hauber, D. Marshall, A. Lloyd, L. A. Prosser, D. A. Regier, F. R. Johnson and J. Mauskopf (2011) “Conjoint Analysis Applications in Health–A Checklist: A Report of The ISPOR Good Research Practices for Conjoint Analysis Task Force,” Value Health, 14(4):403–413. Search in Google Scholar

Carlson, J. J., N. B. Henrikson, D. L. Veenstra and S. D. Ramsey (2005) “Economic Analyses of Human Genetics Services: A Systematic Review,” Genetics in Medicine, 7(8):519–523. Search in Google Scholar

Davis, J. C., L. Furstenthal, A. A. Desai, T. Norris, S. Sutaria, E. Fleming and P. Ma (2009) “The Microeconomics of Personalized Medicine: Today’s Challenge and Tomorrow’s Promise,” Nature Reviews Drug Discovery, 8(4):279–286. Search in Google Scholar

Deverka, P. A., J. Vernon and H. L. McLeod (2010) “Economic Opportunities and Challenges for Pharmacogenomics,” Annual Review of Pharmacology Toxicology, 50:423–437. Search in Google Scholar

Djalalov, S., Z. Musa, M. Mendelson, K. Siminovitch and J. Hoch (2011) “A Review of Economic Evaluations of Genetic Testing Services and Interventions (2004–2009),” Genetics in Medicine, 13(2):89–94. Search in Google Scholar

Elkin, E. B., D. A. Marshall, N. A. Kulin, I. L. Ferrusi, M. J. Hassett, U. Ladabaum and K. A. Phillips (2011) “Economic Evaluation of Targeted Cancer Interventions: Critical Review and Recommendations,” Genetics in Medicine, 13(10):853–860. Search in Google Scholar

Elstein, A. S. and A. Schwarz (2002) “Clinical Problem Solving and Diagnostic Decision Making: Selective Review of the Cognitive Literature,” British Medical Journal, 324(7339):729–732. Search in Google Scholar

Garber, A. M. and S. R. Tunis (2009) “Does Comparative-Effectiveness Research Threaten Personalized Medicine?” New England Journal of Medicine, 360(19):1925–1927. Search in Google Scholar

Giacomini, M., F. Miller and B. J. O’Brien (2003) “Economic Considerations for Health Insurance Coverage of Emerging Genetic Tests,” Community Genetics, 6(2):61–73. Search in Google Scholar

Gold, M. E., L. B. Russell, J. E. Siegel and M. E. Weinstein, Eds. (1996) Cost-Effectiveness in Health and Medicine. New York, Oxford University Press. Search in Google Scholar

Greenberg, D. and P. J. Neumann (2011) “Does Adjusting for Health-Related Quality of Life Matter in Economic Evaluations of Cancer-Related Interventions?” Expert Review of Pharmacoeconomics & Outcomes Research, 11(1):113–119. Search in Google Scholar

Guo, J. J., S. Pandey, J. Doyle, B. Bian, Y. Lis and D. W. Raisch (2010) “A Review of Quantitative Risk-Benefit Methodologies for Assessing Drug Safety and Efficacy-Report of the ISPOR Risk-Benefit Management Working Group,” Value Health, 13(5):657–666. Search in Google Scholar

Haas, J. S., S. Y. Liang, M. J. Hassett, S. Shiboski, E. B. Elkin and K. A. Phillips (2011) “Gene Expression Profile Testing for Breast Cancer and the Use of Chemotherapy, Serious Adverse Effects, and Costs of Care,” Breast Cancer Res Treat, 130(2):619–626. Search in Google Scholar

Hall, P., C. McCabe, R. Stein and D. Cameron (2012) “Economic Evaluation of Genomic Test-Directed Chemotherapy for Early-Stage Lymph Node-Positive Breast Cancer,” Journal of the National Cancer Institute, 104:56–66. Search in Google Scholar

Halpern, S., P. Ubel and D. Asch (2007) “Harnessing the Power of Default Options to Improve Health Care,” New England Journal of Medicine, 357(13):1340–1344. Search in Google Scholar

Institute of Medicine (2009) Race, Ethnicity, and Language Data: Standardization for Health Care Quality Improvement. Washington, DC: The National Academies Press. Search in Google Scholar

Johnson, F. R., A. F. Mohamed, S. Ozdemir, D. A. Marshall and K. A. Phillips (2011) “How Does Cost Matter in Health-Care Discrete-Choice Experiments?” Health Econ, 20(3):323–330. Search in Google Scholar

Kahneman, D. and A. Tversky (1979) “Prospect Theory: An Analysis of Decisions Under Risk,” Econometrica, 47(2):263–291. Search in Google Scholar

Khoury, M. J., R. J. Coates, M. L. Fennell, R. E. Glasgow, M. T. Scheuner, S. D. Schully, M. S. Williams and S. B. Clauser (2012a) “Multilevel Research and the Challenges of Implementing Genomic Medicine,” Journal Of The National Cancer Institute Monograph, 2012(44):112–120. Search in Google Scholar

Khoury, M. J., M. L. Gwinn, R. E. Glasgow and B. S. Kramer (2012b) “A Population Approach to Precision Medicine,” American Journal of Preventive Medicine, 42(6):639–645. Search in Google Scholar

Knight, S. (2011) Value of Genetic Testing for Heritable Disease in a Population-Based Sample of Older Adults. Seattle, WA: AcademyHealth. Search in Google Scholar

Kreft, I. G. G. (1995) “Hierarchical Linear Models: Problems and Perspectives,” Journal of Education and Behavioral Statistics, 20(2):109–113. Search in Google Scholar

Kuppermann, M., G. Wang, S. Wong, A. Blanco, P. Conrad, S. Nakagawa, J. Terdiman, U. Ladabaum (2012) “Preferences for Outcomes Associated with Decisions to Undergo or Forego Genetic Testing for Lynch Syndrome,” Cancer, 119(1):215–225. Search in Google Scholar

Ladabaum, U., G. Wang, J. Terdiman, A. Blanco, M. Kuppermann, C. R. Boland, J. Ford, E. Elkin and K. A. Phillips (2011) “Strategies to Identify the Lynch Syndrome Among Patients with Colorectal Cancer: A Cost-Effectiveness Analysis,” Annals of Internal Medicine, 155(2):69–79. Search in Google Scholar

Liang, S.-Y., K. A. Phillips, G. Wang, C. Keohane, J. Armstrong, W. M. Morris and J. S. Haas (2011) “Tradeoffs of Using Administrative Claims and Medical Records to Identify the Use of Personalized Medicine for Patients with Breast Cancer,” Medical Care, 49(6):e1–e8. DOI: 10.1097/MLR.1090b1013e318207e318287e. Search in Google Scholar

Marchionni, L., R. F. Wilson, S. S. Marinopoulos, A. C. Wolff, G. Parmigiani, E. B. Bass and S. N. Goodman (2008) Impact of Gene Expression Profiling Tests on Breast Cancer Outcomes. Baltimore, MD: Johns Hopkins University Evidence-based Practice Center. Search in Google Scholar

Marshall, D., N. Kulin and I. L. Ferrusi (2012) Assessing the Value of Personalized Medicine (PM) in Practice - Utilization, Economics and Preferences. ISPOR 17th Annual International Meeting, Washington, DC. Search in Google Scholar

Marshall, D. A., F. R. Johnson, N. A. Kulin, S. Ozdemir, J. M. Walsh, J. K. Marshall, S. Van Bebber and K. A. Phillips (2009) “How do Physician Assessments of Patient Preferences for Colorectal Cancer Screening Tests Differ from Actual Preferences? A Comparison in Canada and the United States Using a Stated-Choice Survey,” Health Econ, 18(12):1420–1439. Search in Google Scholar

Mauskopf, J. A., S. D. Sullivan, L. Annemans, J. Caro, C. D. Mullins, M. Nuijten, E. Orlewska, J. Watkins and P. Trueman (2007) “Principles of Good Practice for Budget Impact Analysis: Report of the ISPOR Task Force on Good Research Practices – Budget Impact Analysis,” Value in health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research, 10(5):336–347. Search in Google Scholar

Myers, E., A. J. McBroom, L. Shen, R. E. Posey, R. Gray and G. D. Sanders (2012) Value-of-information Analysis for Patient-centered Outcomes Research Prioritization. Durham, NC: Duke University Evidence-based Practice Center. Search in Google Scholar

National Research Council (2011) Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease. Washington, DC: The National Academies Press. Search in Google Scholar

National Pharmaceutical Council (2011) “NPC Outlines Heterogeneity Issues at AHRQ Methods Symposium,” E.V.I.dently Today. Search in Google Scholar

Neumann, P. J. (2005) Using Cost-Effectiveness Analysis to Improve Health Care: Opportunities and Barriers. Oxford: Oxford University Press. Search in Google Scholar

Neumann, P. J., J. T. Cohen, J. K. Hammitt, T. W. Concannon, H. R. Auerbach, C. Fang and D. M. Kent (2012) “Willingness-to-Pay for Predictive Tests with No Immediate Treatment Implications: A Survey of US Residents,” Health Econ, 21(3):238–251. Search in Google Scholar

Odierna, D., A. Afable-Munsuz, O. Ikediobi, M. Beattie, S. Knight, M. Ko, A. Wilson and N. Ponce (2011) “Early Developments in Gene-Expression Profiling of Breast Tumors: Potential for Increasing Black-White Patient Disparities in Breast Cancer Outcomes?” Personalized Medicine, 8(6):669–679. Search in Google Scholar

Philipson, T. J. and E. Sun (2011) Blue Pill or Red Pill: The Limits of Comparative Effectiveness Research. Project FDA, Manhattan Institute. Search in Google Scholar

Phillips, K. A. (2008) “Closing the Evidence Gap in the Use of Emerging Testing Technologies in Clinical Practice,” Journal of The American Medical Association, 300(21):2542–2544. Search in Google Scholar

Phillips, K. A., M. J. Ackerman, J. Sakowski and C. I. Berul (2005) “Cost-Effectiveness Analysis of Genetic Testing for Familial Long QT Syndrome in Symptomatic Index Cases,” Heart Rhythm, 2(12):1294–1300. Search in Google Scholar

Phillips, K. A., F. R. Johnson and T. Maddala (2002) “Measuring What People Value: A Comparison of ‘Attitude’ and ‘Preference’ Surveys,” Health Services Research, 37(6):1659–1679. Search in Google Scholar

Phillips, K. A., D. A. Marshall, J. S. Haas, E. B. Elkin, S. Y. Liang, M. J. Hassett, I. Ferrusi, J. E. Brock and S. L. Van Bebber (2009) “Clinical Practice Patterns and Cost Effectiveness of Human Epidermal Growth Receptor 2 Testing Strategies in Breast Cancer Patients,” Cancer, 115(22):5166–5174. Search in Google Scholar

Phillips, K. A., S. Van Bebber and A. M. Issa (2006) “Diagnostics and Biomarker Development: Priming the Pipeline,” Nature Reviews Drug Discovery, 5(6):463–469. Search in Google Scholar

Phillips, K. A. and S. L. Van Bebber (2004) “A Systematic Review of Cost-Effectiveness Analyses of Pharmacogenomic Interventions,” Pharmacogenomics, 5(8):1139–1149. Search in Google Scholar

Phillips, K. A. and S. L. Van Bebber (2005) “Measuring the Value of Pharmacogenomics,” Nature Reviews Drug Discovery, 4(6):500–509. Search in Google Scholar

Phillips, K. A., D. Veenstra, S. L. Van Bebber and J. Sakowski (2003) “An Introduction to Cost-Effectiveness and Cost-Benefit Analysis of Pharmacogenomics,” Pharmacogenomics, 4(3):231–239. Search in Google Scholar

Phillips, K. A., D. L. Veenstra, E. Oren, J. K. Lee and W. Sadee (2001) “Potential Role of Pharmacogenomics in Reducing Adverse Drug Reactions: A Systematic Review,” Journal of the American Medical Association, 286(18):2270–2279. Search in Google Scholar

Phillips, K. A., D. L. Veenstra and W. Sadee (2000) “Implications of the Genetics Revolution for Health Services Research: Pharmacogenomics and Improvements in Drug Therapy,” Health Services Research, 35(5 (Part 3)):128–140. Search in Google Scholar

Polsky, D. (2005) “Does Willingness to Pay Per Quality-Adjusted Life Year Bring Us Closer to a Useful Decision Rule for Cost-Effectiveness Analysis?” Medical Decision Making, 25(6):605–606. Search in Google Scholar

Ponce, N. A., J. Tsui, S. Knight, A. Aafable-Munsuz, U. Ladabaum, R. A. Hiatt and J. S. Haas (2012) “Disparities in Cancer Screening in Individuals with a Family History of Breast or Colorectal Cancers,” Cancer, 118:1656–1663. Search in Google Scholar

Raman, G., B. Wallace, K. Patel, J. Lau and T. Trikalinos. (2011) Technology Assessment: Update on Horizon Scans of Genetic Tests Currently Available for Clinical Use in Cancers. Medford, MA: Tufts University Evidence-based Practice Center. Search in Google Scholar

Rice, T. (2013) “The Behavioral Economics of Health and Health Care,” Annual Review of Public Health, 34, PMID:23297657. Search in Google Scholar

Roth, J. A., L. P. Garrison Jr, W. Burke, S. D. Ramsey, R. Carlson and D. L. Veenstra (2011) “Stakeholder Perspectives on a Risk-Benefit Framework for Genetic Testing,” Public Health Genomics, 14(2):59–67. Search in Google Scholar

Sculpher, M. (2008) “Subgroups and Heterogeneity in Cost-Effectiveness Analysis,” Pharmacoeconomics, 26(9):799–806. Search in Google Scholar

Trosman, J. R., S. L. Van Bebber and K. A. Phillips (2010) “Coverage Policy Development for Personalized Medicine: Private Payer Perspectives on Developing Policy for the 21-Gene Assay,” Journal of Oncology Practice, 6(5):238–242. Search in Google Scholar

Trosman, J. R., S. L. Van Bebber and K. A. Phillips (2011) “Health Technology Assessment and Private Payers’ Coverage of Personalized Medicine,” Journal of Oncology Practice, 7(3S):18s–24s. Search in Google Scholar

Tversky, A. and D. Kahneman (1974) “Judgment Under Uncertainty: Heuristics and Biases,” Science (4157):1124–1131. Search in Google Scholar

Veenstra, D. L., J. A. Roth, L. P. Garrison, Jr., S. D. Ramsey and W. Burke (2010) “A Formal Risk-Benefit Framework for Genomic Tests: Facilitating the Appropriate Translation of Genomics into Clinical Practice,” Genetics in Medicine, 12(11):686–693. Search in Google Scholar

Vegter, S., C. Boersma, M. Rozenbaum, B. Wilffert, G. Navis and M. J. Postma (2008) “Pharmacoeconomic Evaluations of Pharmacogenetic and Genomic Screening Programmes: A Systematic Review on Content and Adherence to Guidelines,” Pharmacoeconomics, 26(7):569–587. Search in Google Scholar

Volpp, K., D. Asch, R. Galvin and G. Loewenstein (2011) “Redesigning Employee Health Incentives – Lessons from Behavioral Economics,” New England Journal of Medicine, 365:388–390. Search in Google Scholar

Wang, G., M. Kuppermann, B. Kim, K. A. Phillips and U. Ladabaum (2012) “Influence of Patient Preferences on the Cost-Effectiveness of Screening for Lynch Syndrome,” American Journal of Managed Care, 18(5):e179–185. Search in Google Scholar

Wang, K., H. Zhang, C. S. Bloss, V. Duvvuri, W. Kaye, N. J. Schork, W. Berrettini and H. Hakonarson (2011) “A Genome-Wide Association Study on Common SNPs and Rare CNVs in Anorexia Nervosa,” Molecular Psychiatry, 16(9):949–959. Search in Google Scholar

Wong, W. B., J. J. Carlson, R. Thariani and D. L. Veenstra (2010) “Cost Effectiveness of Pharmacogenomics: A Critical and Systematic Review,” Pharmacoeconomics, 28(11):1001–1013. Search in Google Scholar

Published Online: 2013-07-05
Published in Print: 2013-09-01

©2013 by Walter de Gruyter Berlin Boston