Goldman Dana P, Gupta Charu, Vasudeva Eshan, Trakas Kostas, Riley Ralph, Lakdawalla Darius, Agus David, Sood Neeraj, Jena Anupam B, Philipson Tomas J
Leonard D. Schaeffer Center for Health Policy and Economics, University of Southern California, Los Angeles, CA, USA.
Precision Health Economics, Los Angeles, CA, USA.
Forum Health Econ Policy. 2013 Sep 1;16(2):S87-S99. doi: 10.1515/fhep-2013-0023.
Personalized medicine - the targeting of therapies to individuals on the basis of their biological, clinical, or genetic characteristics - is thought to have the potential to transform health care. While much emphasis has been placed on the value of personalized therapies, less attention has been paid to the value generated by the diagnostic tests that direct patients to those targeted treatments. This paper presents a framework derived from information economics for assessing the value of diagnostics. We demonstrate, via a case study, that the social value of such diagnostics can be very large, both by avoiding unnecessary treatment and by identifying patients who otherwise would not get treated. Despite the potential social benefits, diagnostic development has been discouraged by cost-based, rather than value-based, reimbursement.
个性化医疗——根据个体的生物学、临床或基因特征为其量身定制治疗方案——被认为具有变革医疗保健的潜力。虽然人们非常强调个性化治疗的价值，但对于将患者导向这些靶向治疗的诊断测试所产生的价值却关注较少。本文提出了一个源自信息经济学的框架，用于评估诊断的价值。通过一个案例研究，我们证明，此类诊断的社会价值可能非常大，既可以避免不必要的治疗，又可以识别出那些原本不会接受治疗的患者。尽管存在潜在的社会效益，但基于成本而非价值的报销方式阻碍了诊断技术的发展。
