New york, Nov. 11, 2019 (GLOBE NEWSWIRE) -- Exponential increase in healthcare database volume, increasing investments on digital tech to effectively manage available information, rising adoption of electronic health records to effectively manage patients health, adoption of advanced analytics, growing need for cost curbing tools such as healthcare predictive analytics software are key factors contributing to high CAGR of Healthcare Predictive Analytics market during forecast period.

According to the current analysis of Reports and Data, the global Healthcare Predictive Analytics market was valued at USD 2,904.2 million in 2018 and is expected to reach USD 22,390.3 million by the year 2026, at a CAGR of 28.9 %. The study covers Healthcare predictive analytics - analytical technique that analyses and predicts outcomes using statistical methods and technology, operating on massive amounts of relevant data for individual patients. Healthcare Predictive Analytics is widely being used in the healthcare sector all over the globe.

The recent emergence of Healthcare Predictive Analytics as a time saving and cost minimizing tool is a major disruptive finding in the healthcare sector. In line with this, numerous firms and hospitals are adopting Healthcare Predictive Analytics, for time saving and cost cutting purpose. For instance, West Tennessee Healthcare saved more than 8,000 hours annually using Cerner's Continuous Advancement Services from an optimization project which reduced the number of discrete task assays that nurses completed on a timely basis.

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Knowledge discovery, data mining, and machine learning techniques have recently attracted considerable attention, due to the growing amount of data available, and to the growing necessity to base the reasoning on evidence taken from physical measurements. Data-driven approaches to knowledge extraction have been developed as a consequence, complementing the more traditional human-centered approaches, by enabling systems to create new knowledge, update existing knowledge, and improve their performance without intervention and reprogramming.

The organization (or representation) of medical knowledge is a very active research field, characterized by a wide range of tools, models and languages, which, together with the availability of increasing computer abilities, allows one to specify and emulate systems of growing complexity. Frame representations, semantic networks, conceptual graph representations are few popular basic representational schemes heavily used in the industry today. Exponential increase in healthcare database volume, increasing investments on digital tech to effectively manage available information, rising adoption of electronic health records to effectively manage patients health, adoption of advanced analytics, growing need for cost curbing tools such as healthcare predictive analytics, are some of the key factors propelling Healthcare Predictive Analytics market growth in the industry.

However, the high cost of analytics solutions, the dearth of skilled personnel, and operational gaps between payers and providers are the major hindrance for market growth during 2019-2026. Problems such as inaccurate diagnoses and poor drug-adherence pose challenges to individual health and safety. These challenges are now being alleviated, if not completely eradicated, with Healthcare Predictive Analytics using personalized drug regimes, follow-up alerts and real-time diagnosis monitoring. Pervasive and context-aware monitoring solutions are improving the quality of life for both patients suffering from chronic conditions and their relatives, as well as reducing long-term healthcare costs and improving the quality of care.

The acquisition and representation of knowledge in clinical decision support systems is an actively evolving research field, characterized by modeling and software engineering issues of increasing complexity. The scope of designing knowledge-based systems in medicine is continuously evolving from being a mere diagnostic task to the broader issue of patient management, leading to a better integration in hospital information systems These benefits are expected to positively affect the Healthcare Predictive Analytics market.

Further key findings from the report suggest

  • Healthcare Predictive Analytics market is growing at a CAGR of 3% in North America followed by Asia Pacific and Europe, respectively. Growing adoption of electronic health records system to effectively manage patient health and reduce overall cost is the prominent factor to accelerate the market growth during forecast period across all regions
  • As of 2018, financial application type segment is the dominating Healthcare Predictive Analytics which holds a significant share of the global healthcare predictive analytics market. European regional market is the prominent revenue generating source for this product segment, followed by North America, Asia-Pacific, and other regions
  • Population health application type segment is expected to be the fastest growing market segment during the forecast period 2019 - 2026 with a value of USD 767 million for the year 2018. However, Patient Data Confidentiality is major challenge for the market growth of this market segment
  • The ‘Payers’ End use sub-segment was valued the highest in the year 2018 and it is expected to remain the highest growing sub-segment by 2026, in the same sector.
  • Asia Pacific is expected to account for the third largest share of the global Healthcare Predictive Analytics market. Developing nations such China, and India are likely to witness significant growth
  • The European region for Healthcare Predictive Analytics was valued the second-highest amongst all regions
  • Reluctance to adopt healthcare predictive analytics in emerging countries and dearth of skilled professionals is likely to hinder the market growth during the forecast period
  • Exponential increase in healthcare database volume, increasing investments on digital tech to effectively manage available information, rising adoption of electronic health records to effectively manage patients health are expected to alleviate restraints to industry growth
  • Key participants include Cerner Corporation, McKesson Corporation, Verisk Analytics, Inc., IBM, Oracle, MedeAnalytics, Inc., SAS, Optum, Inc., Allscripts, and Inovalon

To identify the key trends in the industry, click on the link below:   https://www.reportsanddata.com/report-detail/healthcare-predictive-analytics-market

Segments covered in the report:

For the purpose of this report, Reports and Data has segmented the Healthcare Predictive Analytics market on the basis of application, end use, and region:

Application Type (Revenue, USD Million; 2016–2026)

  • Operations Management
  • Financial
  • Population Health
  • Clinical Data

End Use (Revenue, USD Million; 2016–2026)

  • Payers
  • Providers
  • Others

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Regional Outlook (Revenue in USD Million; 2016–2026)

  • North America
    • U.S.
    • Canada
  • Europe
    • Germany
    • France
    • UK
    • Spain
    • Italy
    • Rest of the Europe
  • Asia Pacific
    • China
    • India
    • Japan
    • Rest of Asia-Pacific
  • Middle East & Africa
    • Latin America
  • Brazil

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