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Healthcare cloud based analytics market forecast 2017-2022 scrutinized in new research

Healthcare cloud based analytics market forecast 2017-2022 scrutinized in new research

The global cloud-based analytics market is estimated to be USD XX billion in 2016 and is projected to reach USD XX billion by 2021, growing at a CAGR of XX% during the forecast period from 2016 to 2021.

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Cloud-based analytics is a technological term used for analytical tools and techniques specifically designed to help customers in extracting meaningful information from a huge chunk of data, where data storage, computing, and other services are carried out outside the organization. It offers on-demand delivery of IT resources and applications including computing, storage and database services via the internet.

Global Healthcare Cloud-Based Analytics Market-Market Dynamics

The healthcare analytics technology, which extensively uses data for quantitative and qualitative analysis, is undergoing an industry transformation from volume-based medicines and reimbursement to value-based medicines and reimbursement, and so is the cloud-based analytics. 

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Drivers

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Some of the key factors driving the market are:
Faster deployment and scalability
Capability of storing, maintaining and computing massive data
Access to advanced IT capabilities like machine learning
Emphasis on improved quality healthcare
Lower IT cost burden on healthcare providers
Integration of big data in healthcare
Technological advancements
Restraints

The technology also has certain constraints to overcome, such as:
Lack of properly trained IT professionals in healthcare
Healthcare providers‰Ûª inability to share data with the third party (i.e. cloud provider) due to policies like Protected Health Information (PHI), which draws very high penalty in case of any breach
Healthcare providers own reluctance to share data because of business reasons
Data integrity and safety concerns
Opportunities

Some of the opportunities in this market for the market players are:
Introduction and implementation of Electronic Health Records (EHR)
Rising investments in venture capital funds
Implementation of trends in the medical-IT field, such as precision medicines, EHR, analytics-driven personalized medicines, clinical DSS, health and disease management, and so on

The key benefit of cloud-based analytics, which is also hindering its growth, is that its usage moves healthcare providers out of the business of ‰ÛÏracking and stacking‰Û. They are anyway not very good at this due to various reasons like high initial investment and lack of skilled professionals, and the introduction of cloud-based analytics will make them focus once again on treating people.

Some of the other benefits of cloud-based analytics are the rapid exchange of information, clarity, and transparency of information, time and cost efficiency, timely emergency/preventive care, and ease of handling a big volume of data.

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The global healthcare cloud-based analytics market is segmented on the basis of technology/platform (predictive analytics, prescriptive analytics, and descriptive analytics), application (clinical data analytics, financial data analytics, administrative data analytics, and research data analytics), component (software, hardware, and services), end-user (healthcare, pharmaceuticals, biotechnology, academia, research, and others), and geography (North America, Europe, Asia-Pacific, Middle East & Africa and Latin America).

In spite of being on the advantageous side, this technology has not been able to attract as many customers (healthcare providers) as it should have. According to a recent HIMSS Analytics Survey, only three percent of surveyed healthcare providers with 101-plus beds have deployed a cloud-based model for analytics and not even 20% are planning to adopt this technology in the near future, which is a very sad reality for everyone, including the ultimate customers (patients) as well as providers.

The main reason for this is a trust deficit between healthcare providers and cloud providers but as technology advances and cloud providers grow in size, this gap will be bridged, and one can hope for a better relationship between them, leading to better, reliable and faster service.

The primary stakeholders of this technology are healthcare IT firms, healthcare analytics vendors, care organizations, health insurance providers, healthcare payers, healthcare providers, research firms, consultants, ambulatory services, and venture capitalists.

Some of the key players in the market are:
Allscripts Healthcare Solutions, Inc. 
Cerner Corporation 
CitiusTech 
HP 
McKesson 
Optum Health 
Verisk Analytics

Key Deliverables in the Study 
Market analysis for the cloud-based analytics market, with region-specific assessments and competition analysis on the global and regional scale.
Market definition along with the identification of key drivers and restraints.

Identification of factors instrumental in changing the market scenario, rising prospective opportunities, and identification of key companies that can influence this market on a global and regional scale.
Extensively researched competitive landscape section with profiles of major companies along with their market share.

Identification and analysis of the macro and micro factors that affect the cloud-based analytics market on both global and regional scale.
A comprehensive list of key market players along with the analysis of their current strategic interests and key financial information.
A wide-ranging knowledge and insights about the major players in this industry and the key strategies adopted by them to sustain and grow in the studied market.
Insights on the major countries/regions in which this industry is blooming and to also identify the regions that are still untapped.

Browse Complete Report @ www.orbisresearch.com/reports/inde…recast-2017-2022   .

Some points from TOC:

  1. Introduction 
    1.1. Study deliverables 
    1.2. Market Definition 
    1.3. Sizing Units 
    1.4. Base Currency 
    1.5. Review and forecast period years 
    1.6. General Study Assumptions 
    1.7 Report Description
  2. Research Methodology 
    2.1. Introduction 
    2.2. Analysis Methodology 
    2.3. Econometric forecast models 
    2.4. Research Assumptions

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