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Global Healthcare Predictive Analytics Market to reach USD XX billion by the end of 2029.

Global Healthcare Predictive Analytics Market Size study & Forecast, by Application (Operations Management, Financial, Population Health, Clinical) by End-use (Payers, Providers, Other End-uses) and Regional Analysis, 2022-2029

Product Code: HLSHIT-46750412
Publish Date: 5-05-2023
Page: 200

Global Healthcare Predictive Analytics Market is valued at approximately USD XX billion in 2021 and is anticipated to grow with a healthy growth rate of more than XX% over the forecast period 2022-2029. Healthcare predictive analytics is a technique of analyzing historical healthcare data to spot patterns and trends that are likely to predictive of future events. It is generally used to identify medication regimens, optimal treatment plans, and engagement material, along with assessing the disease progression and expected comorbidities. The emergence of personalized and evidence-based medicine, the growing need to curtail healthcare costs by reducing unnecessary costs, and rising government initiatives to increase EHR adoption are the key factors that are fostering the market demand across the globe.

The increasing healthcare expenditure is further attributed to the market growth during the estimated period. The Canadian Institute of Health Information reported in 2021 that Canadian health spending increased to USD 308.1 billion in 2021 compared to USD 301.5 billion in 2020. Similarly, according to the Centers for Medicare and Medicaid Services (CMS) estimates, the United States spent nearly USD 4.3 trillion on health care in 2022, up about USD 173 billion from the year 2021. Thus, the rising healthcare spending is leveraging the market expansion at a considerable rate. Moreover, rising investment in the development of advanced technology, as well as the growing emphasis on increasing efficiency across the healthcare sector is presenting various lucrative opportunities over the forecasting years. However, the dearth of skilled IT professionals in healthcare and the lack of robust infrastructure is hindering the market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Healthcare Predictive Analytics Market study include Asia Pacific, North America, Europe, Latin America, and the Rest of the World. North America dominated the market in terms of revenue, owing to the increasing adoption of personalized medicine, along with the rising government initiatives in the region. Whereas, the Asia Pacific is expected to grow with the highest CAGR during the forecast period, owing to factors such as the development of the healthcare infrastructure, as well as the rising number of chronic disease cases in the regional market.

Major market players included in this report are:
IBM Corporation
Cerner Corp.
Verisk Analytics, Inc.
McKesson Corporation
SAS Institute Inc.
Oracle Corporation
Allscripts
Optum Health Inc.
MedeAnalytics, Inc.
MedAi Pvt. Ltd.

Recent Developments in the Market:
Ø In December 2020, Amazon Web Services (AWS) introduced Amazon HealthLake. This HIPAA-eligible service seeks to meet interoperability standards and advance the use of big data analytics in the healthcare industry.
Ø In June 2018, MedeAnalytics and HealthEdge unveiled the comp[any’s partnership with an objective to allow payers for reducing costs, lessens gaps in care, improves broker & employer plan engagement, enhance the quality outcomes, and boost member satisfaction by leveraging each company’s complementary capabilities.

Global Healthcare Predictive Analytics Market Report Scope:
Historical Data 2019-2020-2021
Base Year for Estimation 2021
Forecast period 2022-2029
Report Coverage Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
Segments Covered Application, End-use, Region
Regional Scope North America; Europe; Asia Pacific; Latin America; Rest of the World
Customization Scope Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Application:
Operations Management
Financial
Population Health
Clinical
By End-use:
Payers
Providers
Other End-uses
By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE
Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
RoLA
Rest of the World

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2029 (USD Billion)
1.2.1. Healthcare Predictive Analytics Market, by Region, 2019-2029 (USD Billion)
1.2.2. Healthcare Predictive Analytics Market, by Application, 2019-2029 (USD Billion)
1.2.3. Healthcare Predictive Analytics Market, by End-use, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Healthcare Predictive Analytics Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Healthcare Predictive Analytics Market Dynamics
3.1. Healthcare Predictive Analytics Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Emergence of personalized and evidence-based medicine
3.1.1.2. Increasing healthcare expenditure
3.1.2. Market Challenges
3.1.2.1. Dearth of skilled IT professionals in healthcare
3.1.2.2. Lack of robust infrastructure
3.1.3. Market Opportunities
3.1.3.1. Rising investment in the development of advanced technology
3.1.3.2. Growing emphasis on increasing efficiency across the healthcare sector
Chapter 4. Global Healthcare Predictive Analytics Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Futuristic Approach to Porter’s 5 Force Model (2019-2029)
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. Industry Experts Prospective
4.7. Analyst Recommendation & Conclusion
Chapter 5. Risk Assessment: COVID-19 Impact
5.1. Assessment of the overall impact of COVID-19 on the industry
5.2. Pre COVID-19 and post COVID-19 Market scenario
Chapter 6. Global Healthcare Predictive Analytics Market, by Application
6.1. Market Snapshot
6.2. Global Healthcare Predictive Analytics Market by Application, Performance – Potential Analysis
6.3. Global Healthcare Predictive Analytics Market Estimates & Forecasts by Application 2019-2029 (USD Billion)
6.4. Healthcare Predictive Analytics Market, Sub Segment Analysis
6.4.1. Operations Management
6.4.2. Financial
6.4.3. Population Health
6.4.4. Clinical
Chapter 7. Global Healthcare Predictive Analytics Market, by End-use
7.1. Market Snapshot
7.2. Global Healthcare Predictive Analytics Market by End-use, Performance – Potential Analysis
7.3. Global Healthcare Predictive Analytics Market Estimates & Forecasts by End-use 2019-2029 (USD Billion)
7.4. Healthcare Predictive Analytics Market, Sub Segment Analysis
7.4.1. Payers
7.4.2. Providers
7.4.3. Other End-uses
Chapter 8. Global Healthcare Predictive Analytics Market, Regional Analysis
8.1. Healthcare Predictive Analytics Market, Regional Market Snapshot
8.2. North America Healthcare Predictive Analytics Market
8.2.1. U.S. Healthcare Predictive Analytics Market
8.2.1.1. Application breakdown estimates & forecasts, 2019-2029
8.2.1.2. End-use breakdown estimates & forecasts, 2019-2029
8.2.2. Canada Healthcare Predictive Analytics Market
8.3. Europe Healthcare Predictive Analytics Market Snapshot
8.3.1. U.K. Healthcare Predictive Analytics Market
8.3.2. Germany Healthcare Predictive Analytics Market
8.3.3. France Healthcare Predictive Analytics Market
8.3.4. Spain Healthcare Predictive Analytics Market
8.3.5. Italy Healthcare Predictive Analytics Market
8.3.6. Rest of Europe Healthcare Predictive Analytics Market
8.4. Asia-Pacific Healthcare Predictive Analytics Market Snapshot
8.4.1. China Healthcare Predictive Analytics Market
8.4.2. India Healthcare Predictive Analytics Market
8.4.3. Japan Healthcare Predictive Analytics Market
8.4.4. Australia Healthcare Predictive Analytics Market
8.4.5. South Korea Healthcare Predictive Analytics Market
8.4.6. Rest of Asia Pacific Healthcare Predictive Analytics Market
8.5. Latin America Healthcare Predictive Analytics Market Snapshot
8.5.1. Brazil Healthcare Predictive Analytics Market
8.5.2. Mexico Healthcare Predictive Analytics Market
8.5.3. Rest of Latin America Healthcare Predictive Analytics Market
8.6. Rest of The World Healthcare Predictive Analytics Market

Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. IBM Corporation
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. Cerner Corp.
9.2.3. Verisk Analytics, Inc.
9.2.4. McKesson Corporation
9.2.5. SAS Institute Inc.
9.2.6. Oracle Corporation
9.2.7. Allscripts
9.2.8. Optum Health Inc.
9.2.9. MedeAnalytics, Inc.
9.2.10. MedAi Pvt. Ltd.
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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