Application of Analytics to Big Data in Healthcare

Abstract

In the current age of smart phones and wearable devices, vast amounts of patient health data files forming Big Data are being placed into large databases where they can be accessed by multiple users including doctors, caregivers and patients. The estimated spending on healthcare in 2015 in the U.S. is around $3.2 trillion, which triggers the question of improvement of patient care while containing the costs. The objective of the present study is to review a few applications of analytics of Big Data in the healthcare field and the associated outcomes. Big Data is generally characterized by the volume, velocity, variety and veracity of complex data. Many hospitals have applied analytics to big data from various sources including patient health records to achieve overall improvement in healthcare. Operationally, most of the pertinent data of patients are made available on demand so doctors can see how other treatments have worked globally and apply relevant results to facilitate better decision making and interventions. Making proper use of big data analytics in healthcare can lead to improvement in care delivery coupled with significant cost savings. Concurrent challenges to be addressed include accessibility, privacy, security, usability, implementation costs, transportability, interoperability, and standardization. In conclusion, employing efficient and streamlined analytics to big data will contribute to quick and accurate diagnosis, appropriate treatment, reduced costs and improved overall healthcare quality.

Ähnliche Arbeiten