TY - JOUR
T1 - Big data in health care
T2 - Using analytics to identify and manage high-risk and high-cost patients
AU - Bates, David W.
AU - Saria, Suchi
AU - Ohno-Machado, Lucila
AU - Shah, Anand
AU - Escobar, Gabriel
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
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U2 - 10.1377/hlthaff.2014.0041
DO - 10.1377/hlthaff.2014.0041
M3 - Article
C2 - 25006137
AN - SCOPUS:84905990877
SN - 0278-2715
VL - 33
SP - 1123
EP - 1131
JO - Health Affairs
JF - Health Affairs
IS - 7
ER -