Bates David W, Saria Suchi, Ohno-Machado Lucila, Shah Anand, Escobar Gabriel
David W. Bates (
Suchi Saria is an assistant professor of computer science and health policy management at the Center for Population Health and IT, Johns Hopkins University, in Baltimore, Maryland.
Health Aff (Millwood). 2014 Jul;33(7):1123-31. doi: 10.1377/hlthaff.2014.0041.
The US health care system is rapidly adopting electronic health records, which will dramatically increase the quantity of clinical data that are available electronically. Simultaneously, rapid progress has been made in clinical analytics--techniques for analyzing large quantities of data and gleaning new insights from that analysis--which is part of what is known as big data. As a result, there are unprecedented opportunities to use big data to reduce the costs of health care in the United States. We present six use cases--that is, key examples--where some of the clearest opportunities exist to reduce costs through the use of big data: high-cost patients, readmissions, triage, decompensation (when a patient's condition worsens), adverse events, and treatment optimization for diseases affecting multiple organ systems. We discuss the types of insights that are likely to emerge from clinical analytics, the types of data needed to obtain such insights, and the infrastructure--analytics, algorithms, registries, assessment scores, monitoring devices, and so forth--that organizations will need to perform the necessary analyses and to implement changes that will improve care while reducing costs. Our findings have policy implications for regulatory oversight, ways to address privacy concerns, and the support of research on analytics.
美国医疗保健系统正在迅速采用电子健康记录，这将极大地增加可通过电子方式获取的临床数据量。与此同时，临床分析——即分析大量数据并从该分析中获取新见解的技术——取得了快速进展，这是大数据的一部分。因此，利用大数据降低美国医疗保健成本存在前所未有的机会。我们展示了六个用例——即关键示例——通过使用大数据降低成本的一些最明显机会存在于此：高成本患者、再入院、分诊、失代偿（当患者病情恶化时）、不良事件以及影响多个器官系统疾病的治疗优化。我们讨论了临床分析可能产生的见解类型、获得此类见解所需的数据类型，以及组织进行必要分析并实施既能改善护理又能降低成本的变革所需的基础设施——分析、算法、登记处、评估分数、监测设备等等。我们的研究结果对监管监督、解决隐私问题的方式以及对分析研究的支持具有政策影响。
