Wednesday, February 26, 2020

Healthcare Predictive Analytics Market Analysis by Application 2025


27th February 2020 – Latest Research Report on Healthcare Predictive Analytics Market begins with a deep introduction and then search broad into specific segments such as raw material, application, end user, and region, policy study, value chain structure, and upcoming trends in particular segments or regions. The report on Healthcare Predictive Analytics prepare a case for investments in different regions based on a practical view of their regulatory outline, manufacturing dynamics, and availability of skills and resources in that region.

Global healthcare predictive analytics market is expected to reach USD 19.5 billion by 2025. Healthcare predictive analytics is a transformative tool that may allow preventative and proactive treatment options. It uses enhanced computing techniques like data mining, statistical techniques and predictive modeling, and machine learning. The healthcare predictive analytics market is estimated to grow at a significant CAGR of 29.3% over the forecast period as the scope and its applications are rising enormously across the globe.


Top key Players
·         MedeAnalytics Inc
·         IBM
·         Optum Inc
·         Cerner Corporation
·         Allscripts
·         Verisk Analytics Inc
·         Oracle
·         McKesson Corporation
·         SAS

The factors that are playing a major role in the growth of healthcare predictive analytics market are the rising healthcare cost, the rise of personalized and evidence-based medicine, and rising efficacy in the healthcare sector. However, the lack of skilled IT professionals in the healthcare sector may restrain overall market growth in the years to come. Healthcare predictive analytics industry is segmented based on component, application, end-user, and region. Services, software, and hardware are the components that could be explored in healthcare predictive analytics in the forecast period.

The market may be categorized based on applications like research data analytics, clinical data analytics, operations management, population health, financial, and others could be explored in the forecast period. Operation management sector comprises outpatient and inpatient scheduling, demand forecasting, and workforce planning and scheduling. Population health sector comprises population therapy management, population risk management, and patient engagement. Financial sector comprises fraud detection and revenue cycle management.

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