New Resources for e-Patients

描述（由申请人提供）：“电子患者新资源”解决了在线搜索健康和医疗保健信息的消费者未满足的医疗需求，目前美国人口超过1.6亿。它将填补现有在线健康信息资源的空白并解决其不足。它将最大限度地发挥美国政府来源的公共领域健康信息的价值。将从NIH、FDA和其他政府来源收集文本消费者健康信息。这些信息将使用自然语言处理和统计文本挖掘方法进行自动主题分析和分类，以发现和提取有关i）疾病和病症; ii）治疗，益处和风险; iii）基因组风险和反应的主题。这些主题将被整合并映射到消费者感兴趣的最常见的健康主题。将研究个人控制的电子健康记录和个人基因型对电子患者个性化医疗的潜在贡献。该项目的第一阶段将实现原理验证，并开发一个先进的原型，作为第二阶段构建新的网络资源的基础。 公共卫生相关性：该项目解决了在线搜索健康和医疗保健信息的消费者未满足的医疗需求，目前美国人口超过1.6亿，它将填补现有在线健康信息资源的空白和缺陷，并瞄准基因组和个性化医疗的新机会。在这个过程中，我们将创建消费者友好的自动化系统，使在线信息搜索和检索更有效，更有效，并最大限度地提高美国政府来源的公共领域健康信息的价值。这项工作将为新一代精通网络和社交网络的“电子病人”提供更可靠、个性化和可操作的信息，并将使病人和医疗保健系统之间的接触更有效、更富有成效。

DESCRIPTION (provided by applicant): "New Resources for e-Patients" addresses the unmet medical needs of consumers who search for health and healthcare information online, currently a population of more than 160 million people in the U.S. It will fill gaps and address deficiencies in currently available online health information resources. It will maximize the value of public domain health information from U.S. Government sources. Textual consumer health information will be collected from NIH, FDA and other government sources. This information will be subjected to automated topic analysis and classification using methods of natural language processing and statistical text-mining to discover and extract topics on i) diseases and conditions; ii) treatments, benefits and risks; and iii) genomic risks and responses. These topics will be integrated and mapped to the most frequent health topics of interest to consumers. Personally-controlled electronic health records and personal genotypes will be studied for their potential contributions to personalized medicine for e-patients. Phase I of this project will achieve proof-of-principle and develop an advanced prototype as a foundation for construction of a new web-based resource in Phase II. PUBLIC HEALTH RELEVANCE: This project addresses the unmet medical needs of consumers who search for health and healthcare information online, currently a population of more than 160 million people in the U.S. It will fill gaps and address deficiencies in current online health information resources and also target new opportunities in genomic and personalized medicine. In the process we will create consumer-friendly, automated systems that make online information search and retrieval more efficient more efficient and maximize the value of public domain health information from U.S. Government sources. The work will lead to more reliable, personalized and actionable information for a new generation of web-savvy and socially-networked "e-patients" and will lead to more efficient and productive encounters between patients and healthcare systems.