Economic evaluations of big data analytics for clinical decision-making: a scoping review.
OBJECTIVE
Much has been invested in big data analytics to improve health and reduce costs. However, it is unknown whether these investments have achieved the desired goals. We performed a scoping review to determine the health and economic impact of big data analytics for clinical decision-making.


MATERIALS AND METHODS
We searched Medline, Embase, Web of Science and the National Health Services Economic Evaluations Database for relevant articles. We included peer-reviewed papers that report the health economic impact of analytics that assist clinical decision-making. We extracted the economic methods and estimated impact and also assessed the quality of the methods used. In addition, we estimated how many studies assessed "big data analytics" based on a broad definition of this term.


RESULTS
The search yielded 12 133 papers but only 71 studies fulfilled all eligibility criteria. Only a few papers were full economic evaluations; many were performed during development. Papers frequently reported savings for healthcare payers but only 20% also included costs of analytics. Twenty studies examined "big data analytics" and only 7 reported both cost-savings and better outcomes.


DISCUSSION
The promised potential of big data is not yet reflected in the literature, partly since only a few full and properly performed economic evaluations have been published. This and the lack of a clear definition of "big data" limit policy makers and healthcare professionals from determining which big data initiatives are worth implementing.
['Bakker|Lytske|L|', 'Aarts|Jos|J|', 'Uyl-de Groot|Carin|C|', 'Redekop|William|W|']
D000077558:Big Data D000066491:Clinical Decision-Making D017046:Cost Savings D003362:Cost-Benefit Analysis D000077488:Data Science D003695:Delivery of Health Care D006801:Humans D018803:Models, Economic
economics big data clinical decision-making data science, cost-effectiveness