Global Healthcare Predictive Analytics Market - Segmented by Application, Component, Deployment, End User, and Geography - Growth, Trends, and Forecast (2018 - 2023)

SKU ID : INH- 12346221

Publishing Date : 01-Apr-2018

No. of pages : 105

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  • The global healthcare predictive analytics market is expected to register a CAGR of around 9.8% during the forecast period of 2018-2023. Predictive analytics is the second stage of analytics in healthcare and organizations that are convinced that they have a complete and accurate descriptive analytics program move to the next stage of analytics. Predictive analytics uses data mining, machine learning, predictive modeling and statistical techniques, and other advanced computing techniques, to determine the probable future, based on the available descriptive data.

    Emergence of Personalized and Evidence-based Medicine

    Personalized medicine, as the name suggests, differentiates patient population into different groups, with the medical decisions, practices, or treatments being tailored to suit individual needs. It has a wide range of applications in the healthcare industry, including clinical trials and drug developments. However, apart from a few success stories, the technique has recorded limited success. One of the major reasons for this limited success can be attributed to the basic flaw in the technique itself. Predictive analytics has the potential to include the environment, lifestyle, and other factors, along with genetic makeup. This is expected to help improve the success rate, thus leading to a greater adoption of the technique. Evidence-based medicine has also witnessed rapid growth rates, especially in the developed regions, such as North America and Europe. In this case too, predictive analytics can prove to be vital for success. As predictive analytics is crucial for the successful implementation of evidence-based or personalized medicine, the growth of the predictive analytics market is expected to be bolstered by the growth of personalized and evidence-based medicine.
    In addition, the growing need for increasing efficiency in the healthcare sector, increasing demand to curtail healthcare costs by reducing unnecessary costs, and avoiding penalties for failing to control adverse events that are preventable, are expected to supplement the growth of the market studied.

    Lack of Robust Infrastructure for Effective Functioning

    The healthcare industry has begun to adopt predictive analytics for various purposes, such as identifying individuals at the risk of health treatments. Robust infrastructure is crucial effective operations, in addition to scalability of Big Data project in both the models - on premises and cloud-based. In cloud-based model, analytical and storage services can be availed from third-party vendors. In the on premises model, storage and maintenance functions are the responsibility of with healthcare providers. For storing and maintaining, secure platforms need to be made, which are expensive. In an on-premise model, the complete setup of hardware and software is being installed in health centers, i.e., hospitals or clinics, for their respective functions.
    Storing healthcare data is a tedious task, because of the quantity of data being generated every fraction of a second. Moreover, maintaining the integrity of the data is a challenging job in itself, in the modern era of cybercrime. Therefore, to store or maintain healthcare data, a completely secure platform is mandatory in any institution. This demands significant investments, which most developing countries lack. Additionally, in developed regions, small and medium healthcare providers are not willing to invest big on predictive analytics. Thus, considerable investments to create a robust infrastructure are proving to be a major restraining factor for the market. The other factors, such as lack of skilled and trained IT professionals in healthcare and the healthcare provider’s reluctance to share data with third parties are hindering the market’s growth.

    Asia-Pacific Expected to Register the Highest CAGR

    Owing to the available polices and economic development that are expected to contribute to the growth of the market, Asia-Pacific is expected to record the highest CAGR over the forecast period. Additionally, the growth of the Information Technology (IT) industry is boosting the growth of this region. Currently, North America accounts for the largest share, followed by Europe.

    Key Developments in the Market

    • October 2017 - Allscripts acquired McKesson’s Enterprise Information Solutions business.

    Major Players: IBM, CERNER CORPORATION, ORACLE CORPORATION, MEDEANALYTICS INC., OPTUM INC., ALLSCRIPTS HEALTHCARE SOLUTIONS INC., TRUVEN HEALTHANALYTICS INC., VERISK ANALYTICS, and INFORMATION BUILDERS INC., among others.

    Reasons to Purchase this Report

    • Current and future global healthcare predictive analytics market outlook in the developed and emerging markets.
    • Analyzing various perspectives of the market, with the help of Porter’s five forces analysis.
    • The segment that is expected to dominate the market.
    • The regions that are expected to witness the fastest growth during the forecast period.
    • Identify the latest developments, market shares, and strategies employed by the major market players.
    • 3 months analyst support along with the Market Estimate sheet (in excel).

    Customization of the Report

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    This market study covers the global and regional market with an in-depth analysis of the overall growth prospects in the market. Furthermore, it sheds light on the comprehensive competitive landscape of the global market. The report further offers a dashboard overview of leading companies encompassing their successful marketing strategies, market contribution, recent developments in both historic and present contexts.

    • By product type
    • By End User/Applications
    • By Technology
    • By Region

    The report provides a detailed evaluation of the market by highlighting information on different aspects which include drivers, restraints, opportunities, and threats. This information can help stakeholders to make appropriate decisions before investing.
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