InheRET: A SaaS solution to identify patients at increased risk for hereditary disease.

项目摘要 本项目旨在扩展InheRET遗传风险评估工具，以纳入以下测试建议： 遗传性疾病风险增加的患者，增加患者导航功能和可定制的数据库 医疗保健提供者的入口。这将包括InheRET 3.0的开发、集成和测试 然后在5个不同的诊所进行试点测试。InheRET的目标是快速轻松地识别个人， 增加遗传性疾病的风险，使他们能够获得下游护理，降低发病率， mortality. InheRET的独特功能减少了临床确定障碍，简化了工作流程， 提高卫生系统的盈利能力。该项目的目标是在silico（计算机 InheRET的认知计算引擎的测试遵循回顾性测试，最后，试点 在各种临床环境中进行测试，以确定在 商业化此外，我们还将扩大InheRET计划与EPIC电子产品的整合， 健康记录系统，在患者报告可用时为提供者提供硬和/或软警报。 如果我们与计算机模拟测试（即认知测试）达到100%一致，则确定成功 计算引擎功能正确），与临床试验中的临床测定结果的一致性为98%， 在集成测试中实现100%的一致性（所有患者报告均适当且无缝地发送至 正确的医疗记录）。 我们的主要目标是制作一份准确、易于使用和理解的报告，以确保患者 那些可能在不知不觉中携带遗传基因突变的人被识别出来，从而使他们能够获得 遗传咨询师和测试沿着适当的下游护理。虽然病人和医生 报告，医生报告将通过提供推荐的基因进行测试来增强， 简化的订购流程。通过这样做，患者可以降低患病风险， 治疗，如果他们招致疾病，并降低总体死亡率。

PROJECT SUMMARY This project is to expand the InheRET Inherited Risk Evaluation Tool to include recommendations for testing of patients at increased risk for hereditary disease, adding patient navigation features and customizable database entries for healthcare providers. This will include the development, integration and testing of InheRET 3.0 followed by pilot testing in 5 diverse clinics. InheRET's aim is to quickly and easily identify individuals at increased risk for hereditary diseases enabling them to access downstream care, reducing morbidity and mortality. InheRET's unique features reduces clinical ascertainment barriers, streamlines workflows and enhances profitability within health systems. The aims for this project are to complete in silico (computer generated) testing of the cognitive computing engine of InheRET followed retrospective testing and finally, pilot testing in a variety of clinical settings to determine if any additional changes are needed to the product prior to commercialization. In addition, we will expand the integration of the InheRET program with an EPIC electronic health record system, providing hard and/or soft alerts for providers as patient reports become available. Success will be determined if we achieve 100% concordance with the in silico testing (i.e. the cognitive computing engine functions correctly), 98% concordance with clinical determinations in the clinical pilot testing, and 100% concordance in the integration testing (all patient reports are appropriately and seamlessly routed to the proper medical records). Our primary objective is to produce an accurate, easy-to-use and understandable report to ensure patients who may unknowingly harbor inherited genetic mutations are identified, thereby enabling them to access genetic counselors and testing along with appropriate downstream care. While both patient and physician reports are provided, the physician reports will be enhanced by providing recommended genes for testing with streamlined ordering processes. By doing so, patients can reduce their risk of disease, receive tailored treatment if they incur disease, and reduce overall mortality.