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Predictive Disease Analytics Market

Predictive Disease Analytics Market Size, Share & Trends Analysis Report By Component (Hardware, Software & Services), By Deployment (On-premise and Cloud-based), By End-user (Healthcare Providers, Healthcare Payers), By Region, And Segment Forecasts, 2024-2031

Report ID : 1720 | Published : 2024-06-13 | Pages: 180 | Format: PDF/EXCEL

The Global Predictive Disease Analytics Market Size is valued at 2.78 billion in 2023 and is predicted to reach 12.93 billion by the year 2031 at a 21.19% CAGR during the forecast period for 2024-2031.

Predictive analytics, a subset of advanced analytics, makes better decisions using modeling, data mining, statistics, and artificial intelligence (AI) techniques. The market is expanding primarily due to factors such as increased the need for healthcare spending to be decreased by removing wasteful expenditures, the emergence of tailored and evidence-based treatments, and enhanced healthcare sector efficiency. Furthermore, due to growing government initiatives and growing financial investments in the field, predictive analytical techniques are being employed more frequently in the healthcare industry. 

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Additionally, two major factors driving the increased usage of predictive analytical tools in the healthcare sector are government efforts and the rising amount of money invested in the field.

In addition to hospitals, policymakers are using these platforms to analyze data and models to improve decisions and policies about healthcare institutions and the provision of patient care. The essential firms also develop cutting-edge technical instruments to increase their market domination. However, challenges like privacy concerns, a lack of rules, and algorithm bias are anticipated to impede market expansion. 

Recent Developments:

  • In January 2023, SwitchPoint Ventures and Ardent Health Service collaborated to open an innovation studio. The studio's main priorities will be creating and implementing data-driven solutions. Polaris, SwitchPoint's ground-breaking technology for precisely forecasting patient volume in any healthcare context, has also been adopted by Ardent. 

Competitive Landscape:

Some of the predictive disease analytics market players are:

  • Oracle
  • IBM
  • SAS
  • Allscripts Healthcare Solutions Inc.
  • MedeAnalytics, Inc.
  • Health Catalyst
  • Apixio Inc 

Market Segmentation:

The predictive disease analytics market is segmented on the basis of component, deployment and application. Based on components, the market is segmented as Software & Services and Hardware. By deployment, the market is segmented into On-premise and Cloud-based. Based on end-user, the market is segmented as Healthcare Providers, Healthcare Payers,  and Other End Users.

Based On Component, The Software & Services Segment Is Accounted As A Major Contributor In The Predictive Disease Analytics Market

The software & services category is expected to hold a significant share of the global predictive disease analytics market in 2024. Significant investments from the healthcare sector have been made in the IT sector due to the creation of platforms and the digitalization of data for analytics. Most firms outsource the data analytics aspect of their IT because they lack a data analytics division. As a result, more companies are offering a wide range of services to organizations through data analytics. The industry's growth is further boosted by expanding data analytics services.

Healthcare Payers Segment Witnessed Growth At A Rapid Rate

The healthcare payers segment is projected to grow at a rapid rate in the global predictive disease analytics market. Insurance firms, businesses and unions that sponsor health plans, governmental organizations, and third-party payers are examples of healthcare payers. Healthcare payers use predictive disease analytics technologies to review insurance claims before paying out, to determine the risk of diseases, and to stop and identify fraudulent claims. Healthcare payers forecast the future using past and current data. 

The North America, Predictive Disease Analytics Market Holds A Significant Regional Revenue Share

The North America predictive disease analytics market is expected to register the highest market share in revenue in the near future. The region has the most advanced medical facilities, which hastens platform adoption. The need for hospitals and other organizations to adopt analytics tools has grown due to the burden of chronic diseases and the proportion of the growing older population. The existence of significant corporations has also had an impact on the market's sizable amount of income. For instance, a U.S.-based company, Microsoft, will introduce Microsoft Cloud for Healthcare in September 2020. This alliance between patients and providers will help provide better patient care insights. In addition, Asia Pacific is projected to grow rapidly in the global predictive disease analytics market. Expanding favorable government programs are to blame for the market expansion.

Furthermore, rising healthcare spending encourages market growth and generates new business opportunities. A growing senior population and an increase in the prevalence of chronic diseases are the two main causes of regional spread. In 2020, 414 million people in Asia were 65 or older, and the U.S. Census Bureau estimates that number will increase to 1.2 billion by 2060. 

Predictive Disease Analytics Market Report Scope:

Report Attribute

Specifications

Market size value in 2023

USD 2.78 Bn

Revenue forecast in 2031

USD 12.93 Bn

Growth rate CAGR

CAGR of 21.19% from 2024 to 2031

Quantitative units

Representation of revenue in US$ Billion, and CAGR from 2024 to 2031

Historic Year

2019 to 2023

Forecast Year

2024-2031

Report coverage

The forecast of revenue, the position of the company, the competitive market statistics, growth prospects, and trends

Segments covered

Component, Deployment And Application

Regional scope

North America; Europe; Asia Pacific; Latin America; Middle East & Africa

Country scope

U.S.; Canada; U.K.; Germany; China; India; Japan; Brazil; Mexico; The UK; France; Italy; Spain; China; Japan; India; South Korea; Southeast Asia; South Korea; Southeast Asia

Competitive Landscape

Oracle; IBM; SAS; Allscripts Healthcare Solutions Inc.; MedeAnalytics, Inc.; Health Catalyst; and Apixio Inc.

Customization scope

Free customization report with the procurement of the report, Modifications to the regional and segment scope. Particular Geographic competitive landscape.

Pricing and available payment methods

Explore pricing alternatives that are customized to your particular study requirements.

Chapter 1. Methodology and Scope
1.1. Research Methodology
1.2. Research Scope & Assumptions

Chapter 2. Executive Summary

 

Chapter 3. Global Predictive Disease Analytics Market Snapshot

Chapter 4. Global Predictive Disease Analytics Market Variables, Trends & Scope
4.1. Market Segmentation & Scope
4.2. Drivers
4.3. Challenges
4.4. Trends
4.5. Investment and Funding Analysis
4.6. Industry Analysis – Porter’s Five Forces Analysis
4.7. Competitive Landscape & Market Share Analysis
4.8. Impact of Covid-19 Analysis

Chapter 5. Market Segmentation 1: by Component Estimates & Trend Analysis
5.1. by Component & Market Share, 2023 & 2031
5.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Component:

5.2.1. Software and Services
5.2.2. Hardware

Chapter 6. Market Segmentation 2: by Deployment Estimates & Trend Analysis
6.1. by Deployment & Market Share, 2023 & 2031
6.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by Deployment:

6.2.1. On-premise
6.2.2. Cloud-based

Chapter 7. Market Segmentation 3: by End-user Estimates & Trend Analysis
7.1. by End-user & Market Share, 2023 & 2031
7.2. Market Size (Value (US$ Mn)) & Forecasts and Trend Analyses, 2019 to 2031 for the following by End-user:

7.2.1. Healthcare Payers
7.2.2. Healthcare Providers
7.2.3. Other End-Users

Chapter 8. Predictive Disease Analytics Market Segmentation 4: Regional Estimates & Trend Analysis

8.1. North America

8.1.1. North America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2023-2031
8.1.2. North America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2023-2031
8.1.3. North America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2023-2031
8.1.4. North America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.2. Europe

8.2.1. Europe Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2023-2031
8.2.2. Europe Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2023-2031
8.2.3. Europe Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2023-2031
8.2.4. Europe Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.3. Asia Pacific

8.3.1. Asia Pacific Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2023-2031
8.3.2. Asia Pacific Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2023-2031
8.3.3. Asia-Pacific Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2023-2031
8.3.4. Asia Pacific Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.4. Latin America

8.4.1. Latin America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2023-2031
8.4.2. Latin America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2023-2031
8.4.3. Latin America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2023-2031
8.4.4. Latin America Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

8.5. Middle East & Africa

8.5.1. Middle East & Africa Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Component, 2023-2031
8.5.2. Middle East & Africa Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by Deployment, 2023-2031
8.5.3. Middle East & Africa Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by End-user, 2023-2031
8.5.4. Middle East & Africa Predictive Disease Analytics Market Revenue (US$ Million) Estimates and Forecasts by country, 2023-2031

Chapter 9. Competitive Landscape

9.1. Major Mergers and Acquisitions/Strategic Alliances

9.2. Company Profiles


9.2.1. Oracle
9.2.2. IBM
9.2.3. SAS
9.2.4. Allscripts Healthcare Solutions Inc.
9.2.5. MedeAnalytics, Inc.
9.2.6. Health Catalyst
9.2.7. Apixio Inc.
9.2.8. Other Prominent Players

Segmentation of Predictive Disease Analytics Market-

Predictive Disease Analytics Market By Component

  • Software & Services
  • Hardware 

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Predictive Disease Analytics Market By Deployment

  • On-premise
  • Cloud-based

Predictive Disease Analytics Market By End User

  • Healthcare Payers
  • Healthcare Providers
  • Other End Users

Predictive Disease Analytics Market By Region

North America-

  • The US
  • Canada
  • Mexico

Europe-

  • Germany
  • The UK
  • France
  • Italy
  • Spain
  • Rest of Europe

Asia-Pacific-

  • China
  • Japan
  • India
  • South Korea
  • South East Asia
  • Rest of Asia Pacific

Latin America-

  • Brazil
  • Argentina
  • Rest of Latin America

 Middle East & Africa-

  • GCC Countries
  • South Africa
  • Rest of Middle East and Africa

InsightAce Analytic follows a standard and comprehensive market research methodology focused on offering the most accurate and precise market insights. The methods followed for all our market research studies include three significant steps – primary research, secondary research, and data modeling and analysis - to derive the current market size and forecast it over the forecast period. In this study, these three steps were used iteratively to generate valid data points (minimum deviation), which were cross-validated through multiple approaches mentioned below in the data modeling section.

Through secondary research methods, information on the market under study, its peer, and the parent market was collected. This information was then entered into data models. The resulted data points and insights were then validated by primary participants.

Based on additional insights from these primary participants, more directional efforts were put into doing secondary research and optimize data models. This process was repeated till all data models used in the study produced similar results (with minimum deviation). This way, this iterative process was able to generate the most accurate market numbers and qualitative insights.

Secondary research

The secondary research sources that are typically mentioned to include, but are not limited to:

  • Company websites, financial reports, annual reports, investor presentations, broker reports, and SEC filings.
  • External and internal proprietary databases, regulatory databases, and relevant patent analysis
  • Statistical databases, National government documents, and market reports
  • Press releases, news articles, and webcasts specific to the companies operating in the market

The paid sources for secondary research like Factiva, OneSource, Hoovers, and Statista

Primary Research:

Primary research involves telephonic interviews, e-mail interactions, as well as face-to-face interviews for each market, category, segment, and subsegment across geographies

The contributors who typically take part in such a course include, but are not limited to: 

  • Industry participants: CEOs, CBO, CMO, VPs, marketing/ type managers, corporate strategy managers, and national sales managers, technical personnel, purchasing managers, resellers, and distributors.
  • Outside experts: Valuation experts, Investment bankers, research analysts specializing in specific markets
  • Key opinion leaders (KOLs) specializing in unique areas corresponding to various industry verticals
  • End-users: Vary mainly depending upon the market

Data Modeling and Analysis:

In the iterative process (mentioned above), data models received inputs from primary as well as secondary sources. But analysts working on these models were the key. They used their extensive knowledge and experience about industry and topic to make changes and fine-tuning these models as per the product/service under study.

The standard data models used while studying this market were the top-down and bottom-up approaches and the company shares analysis model. However, other methods were also used along with these – which were specific to the industry and product/service under study.

To know more about the research methodology used for this study, kindly contact us/click here.

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Frequently Asked Questions

How big is the Predictive Disease Analytics Market?

Predictive Disease Analytics Market expected to grow at a 21.19% CAGR during the forecast period for 2024-2031

Oracle; IBM; SAS; Allscripts Healthcare Solutions Inc.; MedeAnalytics, Inc.; Health Catalyst; and Apixio Inc

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