Michigan State University College of Human Medicine, Traverse City Campus, 1400 Medical Campus Drive, Traverse City, MI, 49684, USA.
ChronoRecord Association, Inc, Fullerton, CA, 92834, USA.
Int J Bipolar Disord. 2016 Dec;4(1):10. doi: 10.1186/s40345-016-0051-7. Epub 2016 Apr 11.
The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.
精神科护理的提供正在发生变化，新的重点是综合护理、预防措施、人群健康和疾病的生物学基础。这一转变的基础是大数据和分析这些数据的能力的进步。本文讨论了大数据对目前和不久的将来双相情感障碍常规治疗的影响，其中包括与卫生政策、新关联的发现以及罕见事件研究相关的例子。目前大数据的主要来源是电子病历 (EMR)、提供者和支付者的索赔和登记数据。在不久的将来，患者通过主动监测、互联网和智能手机活动的被动监测以及传感器创建的数据可能会与 EMR 集成。来自医学以外的各种数据源，如政府财务数据，将被用于研究。从长远来看，遗传和成像数据将与 EMR 集成，预测模型将更加重视。在分析与 EMR 中的大小、异质性、复杂性和非结构化文本数据相关的大数据时，仍然存在许多技术挑战。人类判断和主题专业知识是大数据分析的关键部分，精神病学家需要在整个分析过程中积极参与。
