Feb 16, 2020 (The Expresswire) -- Global Healthcare Predictive Analytics Market Report is a pro and comprehensive analysis on the Healthcare Predictive Analytics sector which highlights the key trends and market drivers in the present scenario and offers on-the-ground insights(2020-2023).
The " Healthcare Predictive Analytics " Market (2019-2023) research report gives an expert and top to bottom analysis on the current state focuses on the major players and restraints for the key players. Global Healthcare Predictive Analytics Industry report additionally gives granular analysis of the market size, share, segmentation, revenue forecasts and geographic regions of the market. This report categorizes the market based on market overview, regions, analysis by types and applications, market dynamics and manufacturers profiles.
Get a sample copy of the report at- https://www.marketreportsworld.com/enquiry/request-sample/12346221
Moreover, development policies and plans are discussed as well as manufacturing processes and cost structures. This report also states Healthcare Predictive Analytics market trend, import/export, supply and consumption figures as well as cost, price, revenue and gross margin by regions, and other regions can be added.Healthcare Predictive Analytics market forecast For the period of 2020-2023, this study provides the Healthcare Predictive Analytics sales, revenue and market share for each player covered in this report.
TopManufacturersListed inthe Healthcare Predictive Analytics Market Report are:
Allscripts Healthcare Solutions Inc.
Truven Healthanalytics Inc.
Information Builders Inc.
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.