
doi: 10.1007/164_2022_591
pmid: 35768553
Introducing precision medicine strategies into routine practice will require robust economic evidence. Decision-makers need to understand the value of a precision medicine strategy compared with alternative ways to treat patients. This chapter describes health economic analysis techniques that are needed to generate this evidence. The value of any precision medicine strategy can be demonstrated early to inform evidence generation and improve the likelihood of translation into routine practice. Advances in health economic analysis techniques are also explained and their relevance to precision medicine is highlighted. Ensuring that constraints on delivery are resolved to increase uptake and implementation will improve the value of a new precision medicine strategy. Empirical methods to quantify stakeholders' preferences can be effective to inform the design of a precision medicine intervention or service delivery model. A range of techniques to generate relevant economic evidence are now available to support the development and translation of precision medicine into routine practice. This economic evidence is essential to inform resource allocation decisions and will enable patients to benefit from cost-effective precision medicine strategies in the future.
Value of information, Budget impact analysis, Cost-effectiveness analysis, Cost-Benefit Analysis, Economic evaluation, Pharmacoeconomics, Decision-analytic model, Discrete choice experiment, Microcosting, Value of implementation, Humans, Stated preferences, Precision Medicine
Value of information, Budget impact analysis, Cost-effectiveness analysis, Cost-Benefit Analysis, Economic evaluation, Pharmacoeconomics, Decision-analytic model, Discrete choice experiment, Microcosting, Value of implementation, Humans, Stated preferences, Precision Medicine
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 2 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
