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Data Analytics and HealthCare: Delivering Health as a Service (HaaS)
Data analytics and “as a service”-based apps are slowly transforming the way that healthcare is provided. The biggest segment of the Big Data as a Service market is in health care and is valued at $1.09 billion in 2015, according to a report by Technavio. Some of the growth is driven by a desire to reduce the costs for providing health care. There is also the factor that the ever increasing amounts of health data that are being created are better handled by centralized organizations that specialize in managing data.
Sunil Kumar Singh, lead analyst at Technavio, said that “the healthcare sector is undergoing rapid technological changes in electronic medical records, medical imaging, and telemedicine, to improve patient care. Thus, big data in healthcare is gaining prominence for enhancing the quality of services. Big data as a service solutions are supporting a wide range of healthcare functions such as disease surveillance, clinical decision support, and population health management. Therefore, the need for digital transformation is driving healthcare institutions to spend more on big data technology.”
85 percent of the healthcare as a service (HaaS) market is being managed within Amazon AWS, according to Technavio. Amazon Elastic MapReduce and Hadoop are the principle tools that are used. Other products being used in the HaaS sector include Microsoft HDInsight, Cloudera CDH, and IBM Infosphere BigInsights.
Danny Sands, MD, founder of the Society for Participatory Medicine, doesn’t agree fully agree with a data centric solution, although he finds merit in the use of data as a tool. He calls putting too much reliance on data and analytics a “carwash model”. Healthcare is “not a service industry, it’s a collaboration. Healthcare cannot be successful unless both parties are involved in what’s going on.”














I think it’s cool to see healthcare technology advancing. I think that data analytics is very important to have! That way you can look at data collected over thousands of patients.