Abstract

ObjectiveTo describe the promise and potential of big data analytics in healthcare.MethodsThe paper describes the nascent field of big data analytics in healthcare, discusses the benefits, outlines an architectural framework and methodology, describes examples reported in the literature, briefly discusses the challenges, and offers conclusions.ResultsThe paper provides a broad overview of big data analytics for healthcare researchers and practitioners.ConclusionsBig data analytics in healthcare is evolving into a promising field for providing insight from very large data sets and improving outcomes while reducing costs. Its potential is great; however there remain challenges to overcome.

Highlights

  • The healthcare industry historically has generated large amounts of data, driven by record keeping, compliance & regulatory requirements, and patient care [1]

  • We provide examples of big data analytics in healthcare reported in the literature

  • McKinsey estimates that big data analytics can enable more than $300 billion in savings per year in U.S healthcare, two thirds of that through reductions of approximately 8% in national healthcare expenditures

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Summary

Introduction

The healthcare industry historically has generated large amounts of data, driven by record keeping, compliance & regulatory requirements, and patient care [1]. North York is reported to have implemented a scalable real-time analytics application to provide multiple perspectives, including clinical, administrative, and financial [16] Another example, reported by IBM, is that of the large, unnamed healthcare provider that is analyzing data in the electronic medical record (EMR) system with the goal of reducing costs and improving patient care. The Italian Medicines Agency is reported to collect and analyze clinical data on the use of expensive new drugs as one goal in a country-level cost-effectiveness program [6] Another leading example of big data analytics in healthcare is the Department of Veterans Affairs’ (VA) use of applications on its very large data set in an effort to comply with “performance-based accountability framework and disease management practice” [6].

Conclusions
Burghard C
10. Ikanow: Data Analytics for Healthcare
13. Explorys
15. Intel: Leveraging Big Data and Analytics in Healthcare and Life Sciences
17. Savage N
Findings
32. Bollier D
Full Text
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