The advent of clinical genome sequencing to identify patients at risk for serious diseases and to tailor treatments promises to greatly improve health outcomes and provide a foundation for the delivery of Precision Medicine. However, even as laboratory methods to perform sequencing become highly efficient, uncertainty around the optimal breadth and economic value of sequencing as well as ambiguity around which individuals should be tested presents a critical barrier to wider use. As we rapidly approach an era of inexpensive sequencing, new approaches to quantify and optimize the economic and clinical value of genome-tailored care are needed. For the Rational Integration of Sequencing (RISE) project, we propose to develop a Discrete Event Simulation (DES) to estimate the average clinical efficacy and cost-effectiveness of prospectively acquiring sequence data across a diverse patient population. The simulation will leverage literature-based estimates of clinical outcome rates, costs, and utilities combined with clinical exome and pharmocogenomic implementation program data describing how results are returned and reacted to within clinical care.
The first Aim will develop a conceptual framework and computational infrastructure to understand the drivers of economic value in genomic screening.
The second Aim will externally validate the RISE model using real-world use data.
The third Aim will assess the cost effectiveness of genomic screening scenarios, identify key drivers of value and inform research priorities in genomic screening.
Uncertainty surrounding the clinical and economic value of genetic sequencing is a major impediment to broader adoption of this technology. The Rational Integration of SEquencing (RISE) project will estimate the long term clinical and economic value of sequencing adults and using the information to diagnose genetic diseases, personalize preventative care, and tailor therapies based on genetic risks. The project will also help prioritize research and implementation projects and provide a foundation for the implementation of Precision Medicine.
| Chang, Alex R; Evans, Michael; Yule, Christina et al. (2016) Using pharmacists to improve risk stratification and management of stage 3A chronic kidney disease: a feasibility study. BMC Nephrol 17:168 |
