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Global Predictive Disease Analytics Market to reach USD 8.37 billion by the end of 2029.

Global Predictive Disease Analytics Market Size study & Forecast, by Component (Software & Services, Hardware) by Deployment( On-premises, Cloud based), by End User(Healthcare Payers, Healthcare Providers and Other End Users) and Regional Analysis, 2022-2029

Product Code: HLSHIT-16851512
Publish Date: 2-05-2023
Page: 200

Global Predictive Disease Analytics Market is valued approximately USD 1.63 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 22.70% over the forecast period 2022-2029. Predictive analytics uses a variety of techniques to analyze the most recent data and make future predictions, including data mining, statistics, modelling, artificial intelligence, and machine learning. The healthcare sector has made improvements in several areas by using predictive analytics. These include administering a hospital, simplifying the supply chain, and treating chronic diseases. The Predictive Disease Analytics market is expanding because of factors such as rising emergence of personalized medicine, rising adoption of digital technologies in healthcare industry.

Predictive analytical tools are being more widely used in the healthcare sector due to a combination of rising government initiatives and rising financial investments in the area. For instance, in February 2023, the European Commission allocated USD 7.2 million for a new project that aims to create an AI-based platform for gathering and evaluating clinical data on novel oncology drugs to help regulators’ and HTA agencies’ evaluations of those drugs. Similar to this, the American government has launched a number of initiatives in this area, such as the HealthData.gov portal, which compiles data from a number of federal databases on subjects like clinical data, community health performance, and medical and scientific knowledge. In addition, the healthcare sector is rapidly becoming digitalized due to the quick development of technology and significant investment made by the sector. These analytical tools are being used all around the world to control patients’ retention. The use of healthcare analytics also boosts employee productivity, enhances patient care, and lessens the stress on carers. To bring innovation in research and care, Databricks developed the Lakehouse paradigm for the healthcare and life science industries in March 2022. Analytics, data management, and cutting-edge AI for disease prediction, medical picture classification, and biomarker identification can all be done on one platform. Thus rising product development activities and government funding in healthcare sector is catering the market growth. However, the high cost of Predictive Disease Analytics stifles market growth throughout the forecast period of 2022-2029.

The key regions considered for the Global Predictive Disease Analytics Market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America dominated the market in terms of revenue, owing to rising adoption of digital technologies in healthcare industry, rising research and development of personalized medicine and rising government support to the industry. Whereas Asia Pacific is expected to grow with a highest CAGR during the forecast period, owing to factors such as increasing government support and initiative, growing chronic disease in the region an increase in the number of collaborations for product development, geographic expansion of key players, and active participation of government and nonprofit organizations in the market space.

Major market player included in this report are:
Oracle Corporation
International Business Machines (IBM) Corporation
SAS Software
Allscripts Healthcare Solutions Inc.
MedeAnalytics, Inc.
Health Catalyst.
Apixio Inc.
Microsoft Corporation
UnitedHealth Group Incorporated (Optum Inc.),
Cerner Corporation

Recent Developments in the Market:
Ø In September 2020, Microsoft, a U.S.-based company, unveiled Microsoft Cloud for Healthcare, a partnership between patients and providers that will aid in providing improved patient care insights.
Ø In January 2023, SwitchPoint Ventures and Ardent Health Service partnered to launch an innovation lab. The studio will focus on developing and putting into practise data-driven solutions. Ardent has also implemented Polaris, a game-changing technology from SwitchPoint that accurately forecasts patient volume in any clinical setting.

Global Predictive Disease 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 Component, Deployment, End User, 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 component offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Component:
Software & Services
Hardware

By Deployment:
On-premises
Cloud based
By End User:
Healthcare Payers
Healthcare Providers
Other End Users
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. Predictive Disease Analytics Market, by Region, 2019-2029 (USD Billion)
1.2.2. Predictive Disease Analytics Market, by Component, 2019-2029 (USD Billion)
1.2.3. Predictive Disease Analytics Market, by Deployment, 2019-2029 (USD Billion)
1.2.4. Predictive Disease Analytics Market, by End User, 2019-2029 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Predictive Disease 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 Predictive Disease Analytics Market Dynamics
3.1. Predictive Disease Analytics Market Impact Analysis (2019-2029)
3.1.1. Market Drivers
3.1.1.1. Rising emergence of personalized medicine
3.1.1.2. Rising adoption of digital technologies in healthcare industry
3.1.2. Market Challenges
3.1.2.1. High Cost of Predictive Disease Analytics
3.1.3. Market Opportunities
3.1.3.1. Increase in government funding in healthcare industry.
3.1.3.2. The rapid advancement in technology
Chapter 4. Global Predictive Disease 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 Predictive Disease Analytics Market, by Component
6.1. Market Snapshot
6.2. Global Predictive Disease Analytics Market by Component, Performance – Potential Analysis
6.3. Global Predictive Disease Analytics Market Estimates & Forecasts by Component 2019-2029 (USD Billion)
6.4. Predictive Disease Analytics Market, Sub Segment Analysis
6.4.1. Software & Services
6.4.2. Hardware
Chapter 7. Global Predictive Disease Analytics Market, by Deployment
7.1. Market Snapshot
7.2. Global Predictive Disease Analytics Market by Deployment, Performance – Potential Analysis
7.3. Global Predictive Disease Analytics Market Estimates & Forecasts by Deployment 2019-2029 (USD Billion)
7.4. Predictive Disease Analytics Market, Sub Segment Analysis
7.4.1. On-premises
7.4.2. Cloud based
Chapter 8. Global Predictive Disease Analytics Market, by End User
8.1. Market Snapshot
8.2. Global Predictive Disease Analytics Market by End User, Performance – Potential Analysis
8.3. Global Predictive Disease Analytics Market Estimates & Forecasts by End User 2019-2029 (USD Billion)
8.4. Predictive Disease Analytics Market, Sub Segment Analysis
8.4.1. Healthcare Payers
8.4.2. Healthcare Providers
8.4.3. Other End Users
Chapter 9. Global Predictive Disease Analytics Market, Regional Analysis
9.1. Predictive Disease Analytics Market, Regional Market Snapshot
9.2. North America Predictive Disease Analytics Market
9.2.1. U.S. Predictive Disease Analytics Market
9.2.1.1. Component breakdown estimates & forecasts, 2019-2029
9.2.1.2. Deployment breakdown estimates & forecasts, 2019-2029
9.2.1.3. End User breakdown estimates & forecasts, 2019-2029
9.2.2. Canada Predictive Disease Analytics Market
9.3. Europe Predictive Disease Analytics Market Snapshot
9.3.1. U.K. Predictive Disease Analytics Market
9.3.2. Germany Predictive Disease Analytics Market
9.3.3. France Predictive Disease Analytics Market
9.3.4. Spain Predictive Disease Analytics Market
9.3.5. Italy Predictive Disease Analytics Market
9.3.6. Rest of Europe Predictive Disease Analytics Market
9.4. Asia-Pacific Predictive Disease Analytics Market Snapshot
9.4.1. China Predictive Disease Analytics Market
9.4.2. India Predictive Disease Analytics Market
9.4.3. Japan Predictive Disease Analytics Market
9.4.4. Australia Predictive Disease Analytics Market
9.4.5. South Korea Predictive Disease Analytics Market
9.4.6. Rest of Asia Pacific Predictive Disease Analytics Market
9.5. Latin America Predictive Disease Analytics Market Snapshot
9.5.1. Brazil Predictive Disease Analytics Market
9.5.2. Mexico Predictive Disease Analytics Market
9.5.3. Rest of Latin America Predictive Disease Analytics Market
9.6. Rest of The World Predictive Disease Analytics Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Oracle Corporation
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. International Business Machines (IBM) Corporation
10.2.3. SAS Software
10.2.4. Allscripts Healthcare Solutions Inc.
10.2.5. MedeAnalytics, Inc.
10.2.6. Health Catalyst.
10.2.7. Apixio Inc.
10.2.8. Microsoft Corporation
10.2.9. UnitedHealth Group Incorporated (Optum Inc.),
10.2.10. Cerner Corporation
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

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Data Collection:
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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.
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