Clinical and Translational Informatics, Dana-Farber Cancer Institute, Boston, Massachusetts 02115-6084, USA.
Hum Mutat. 2011 May;32(5):512-6. doi: 10.1002/humu.21456. Epub 2011 Mar 10.
The Information Technology (IT) roadmap for personalized medicine requires Electronic Health Records (EHRs), extension of Healthcare IT (HIT) standards, and understanding of how genetics/genomics should be integrated into the clinical applications. For reduced overall costs and development times, these three initiatives should run in parallel. EHRs must contain structured data and infrastructure that enables quality analysis, Clinical Decision Support (CDS) and messaging within the healthcare information network. Fortunately, as a result of sustained financial commitment to nongenetic-based healthcare, the industry has HIT data standards and understanding of EHR functionality that improves patient safety and outcomes while reducing overall healthcare costs. However, the HIT standards and EHR functional requirements, needed for personalized medicine, are only beginning to support simple genetic tests and need significant extension. In addition, our understanding of the clinical implications of genomic data is evolving and translation of new discovery into clinical care remains a challenge. Therefore, priority areas include CDS, educational resources, and knowledgebases for the EHR, clinical and research data warehouses, messaging frameworks, and continued review of healthcare policies and regulations supporting personalized medicine. Where core infrastructure remains to be developed and implemented, funding is needed for pilot projects, data standards, policy, and stakeholder collaboration.
个性化医学的信息技术 (IT) 路线图需要电子健康记录 (EHR)、扩展医疗保健信息技术 (HIT) 标准，以及了解如何将遗传学/基因组学整合到临床应用中。为了降低总体成本和开发时间，这三个倡议应该并行进行。EHR 必须包含结构化数据和基础设施，以便在医疗保健信息网络中进行质量分析、临床决策支持 (CDS) 和消息传递。幸运的是，由于对非基于遗传的医疗保健的持续财务承诺，该行业已经拥有 HIT 数据标准和 EHR 功能的理解，这提高了患者安全性和结果，同时降低了总体医疗保健成本。然而，个性化医学所需的 HIT 标准和 EHR 功能要求才刚刚开始支持简单的基因测试，并且需要进行重大扩展。此外，我们对基因组数据的临床影响的理解还在不断发展，将新发现转化为临床护理仍然是一个挑战。因此，优先领域包括 EHR 的 CDS、教育资源和知识库、临床和研究数据仓库、消息传递框架，以及对支持个性化医学的医疗保健政策和法规的持续审查。在需要开发和实施核心基础设施的地方，需要为试点项目、数据标准、政策和利益相关者合作提供资金。
