Dixon Brian E, Rosenman Marc, Xia Yuni, Grannis Shaun J
School of Informatics and Computing, Indiana University-Purdue University Indianapolis, Indianapolis, IN, USA.
Stud Health Technol Inform. 2013;192:884-8.
In parallel with the implementation of information and communications systems, health care organizations are beginning to amass large-scale repositories of clinical and administrative data. Many nations seek to leverage so-called Big Data repositories to support improvements in health outcomes, drug safety, health surveillance, and care delivery processes. An unsupported assumption is that electronic health care data are of sufficient quality to enable the varied use cases envisioned by health ministries. The reality is that many electronic health data sources are of suboptimal quality and unfit for particular uses. To more systematically define, characterize and improve electronic health data quality, we propose a novel framework for health data stewardship. The framework is adapted from prior data quality research outside of health, but it has been reshaped to apply a systems approach to data quality with an emphasis on health outcomes. The proposed framework is a beginning, not an end. We invite the biomedical informatics community to use and adapt the framework to improve health data quality and outcomes for populations in nations around the world.
在实施信息和通信系统的同时，医疗保健机构开始积累大规模的临床和管理数据存储库。许多国家试图利用所谓的大数据存储库来支持改善健康结果、药物安全、健康监测和护理提供流程。一个未经证实的假设是，电子医疗数据的质量足以满足卫生部设想的各种用例。现实情况是，许多电子健康数据源的质量欠佳，不适用于特定用途。为了更系统地定义、描述和提高电子健康数据质量，我们提出了一个新的健康数据管理框架。该框架改编自健康领域以外先前的数据质量研究，但经过重塑后采用了系统方法来处理数据质量，并强调健康结果。所提出的框架只是一个开端，而非终点。我们邀请生物医学信息学界使用并调整该框架，以提高全球各国人群的健康数据质量和健康结果。
