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利用多阵列传感和非侵入性数据捕获进行 ONCHIT 前病例生物监测的拟议模型。

Proposed model for ONCHIT pre-case biosurveillance using multiple array sensing and non-invasive data capture.

机构信息

Center for Technology Assessment, University Park, PA 16802, USA.

出版信息

J Med Syst. 2010 Aug;34(4):695-700. doi: 10.1007/s10916-009-9283-8. Epub 2009 Apr 24.

Abstract

Recent initiatives by the US ONCHIT highlight the need for electronic population health data collection relating to aspects of Public Health Case (PH Case) reporting and Adverse Event (AE) reporting. Proposed solutions to date have been primarily provider-based, limited by organization-wide startup & maintenance costs, and hampered by risk-averse data distribution policies. Little attention has been given to consumer-focused, distributed data collection models, where objective, consumer-provided standardized data can be used prior to case identification to facilitate earlier use of extensible and distributed information networks in biosurveillance. We propose here one promising model for pre-case biosurveillance management, employing the use of breath-based, multiple array sensing and data capture. The conceptual applications employed in this technology set are provided by way of illustration, and may also serve as a transformative model for emerging EMR/EHR requirements.

摘要

美国 ONCHIT 的最新举措强调了电子人口健康数据收集的必要性,这些数据与公共卫生病例报告和不良事件报告的各个方面相关。迄今为止,提出的解决方案主要基于供应商,受到组织范围启动和维护成本的限制,并受到规避风险的数据分发政策的阻碍。很少关注以消费者为中心的分布式数据收集模型,在这种模型中,可以在确定病例之前使用客观的、由消费者提供的标准化数据,以促进在生物监测中更早地使用可扩展和分布式信息网络。在这里,我们提出了一个有前途的病例前生物监测管理模型,采用基于呼吸的多阵列传感和数据采集。该技术集中采用的概念应用仅用于说明,也可能成为新兴 EMR/EHR 要求的变革性模型。

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