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Big data analytics (BDA) is a combination of data management tools, techniques, and application for effectively analysing big data sets, in order to derive information on business processes and customer interactions. Big data analytics can process both structure as well as unstructured data obtained from various sources. Big data analytics has paved a new path for healthcare organizations to devise actionable insights, boost up the outcomes, reduce time to value, and organize their future vision. This approach has been deemed helpful in providing insightful information to healthcare enterprises with regard to their planning, measurements, and management. The evaluated results further help in enhancing decision making capacity of these enterprises. By recording disease outbreaks and analyzing disease patterns, big data analytics approach can improve public health issues. Large quantity of data help in determining needs, offering required services, and predicting & preventing future crises. Big data analytics approach also helps in evaluating standard medical data, structured or unstructured, for predicting patients at risk and providing them with effective care.
Drive toward electronic medical records, coupled with favorable government policies has further driven the adoption of big data analytics in healthcare sector. However, majority of medical professionals lack the skill set needed for leveraging information offered by the big data analytics, which continues to be a major restraint for growth of the market. Government and healthcare organizations are therefore focusing on proper training of professionals for making them capable of utilizing the data obtained in a meaningful manner for better drafting of healthcare policies and improving patient outcomes.
FactMR’s recently compiled report estimates the global market for big data analytics in healthcare to register an outstanding expansion during the forecast period (2017-2026). Revenues from global sales of big data analytics in healthcare sector are estimated to exceed US$ 45,000 Mn by 2026-end. Asia-Pacific excluding Japan (APEJ) is expected to remain the fast-expanding market for big data analytics in healthcare. North America is also expected to showcase a promising growth in the market, which can be mainly attributed to big data initiatives of the federal government. Initiatives such as HITECH Act are promoting big data and reducing healthcare expenses in North America. Europe will also account for a major portion of the market’s revenue share during the forecast period.
On the back of rising pressure of curbing healthcare costs, growing adherence toward electronic health records (EHRs), emphasis on improving patient outcomes and reducing hospital readmission rates have spurred the adoption of CRM analytics tool. CRM analytics will remain the most lucrative tool in the market, followed by financial analytics, production reporting, and supply chain analytics, which are increasingly adopted for complying with federal mandates regarding ICD-10 code sets’ implementation.
Key Research Findings from FactMR’s Report on Big Data Analytics in Healthcare Market
- Healthcare provider will continue to be the dominant spender in the global big data analytics in healthcare market
- Access operational information will remain the fastest expanding application of big data analytics in healthcare, followed by access transactional data
- Sales of cloud-based deployment of big data analytics in healthcare will register the highest CAGR through 2026
Competition in the global big data analytics in healthcare market is expected to intensify on the back of mergers and partnerships between prominent players. New marker entrant face barriers such as high deployment cost, and find it difficult to cope up with well-established players in terms of innovation and quality. Key market players identified by the report include IBM Corporation, OptumHealth Care Solutions, Microsoft Corp, McKesson, MedeAnalytics, Verisk Analytics, Allscripts Healthcare Solutions, Oracle Corp, Zephyr Health, Cisco Systems Inc., Infosys, SAS Institute, Alteryx, SAP SE, and Denodo Technologies Inc.
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