Predictive Disease Analytics Market Size To Reach USD 19.2 Billion By 2034, At 24.7% CAGR: Insights By Dimension Market Research

(MENAFN- GlobeNewsWire - Nasdaq) Advancements and Projections in the Predictive Disease Analytics Market: Insights, Trends, Opportunities, and Recent Developments

New York, Sept. 10, 2024 (GLOBE NEWSWIRE) -- Overview

The Global Predictive Disease Analytics Market size is expected to reach USD 2.6 billion by 2024 and it is further anticipated to reach a market value of USD 19.2 billion in 2033 at a CAGR of 24.7% .

The global predictive disease analytics market encompasses a wide range of products and services that utilize advanced analytics and artificial intelligence to analyze and manage disease patterns in healthcare.

It includes applications like disease prediction, population health management, clinical decision support, and resource optimization, contributing to enhanced patient outcomes and healthcare efficiency globally.

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Important Insights99

• Market Value: Projections suggest a substantial surge, within the global predictive disease analytics market as it is expected to show noteworthy growth by reaching USD 19.2 billion by 2033. This represents a significant Compound Annual Growth Rate (CAGR) of 24.7% , commencing from its 2024 base value of USD 2.6 billion.
• Component Segment Insights: Software and services are projected to hold 71.1% market share in the 2024 global predictive disease analytics market. This dominance results from the software's central role, offering adaptability, especially in cloud-based solutions, ensuring scalability and cost-effective disease analysis.
• Deployment Segment Insights: In case of deployment, on-premise solutions are expected to maintain a significant 66.0% share in the global healthcare predictive disease analytics market in 2024. Their dominance is fueled by healthcare data sensitivity and regulatory requirements where on-premise solutions offer flexibility in addressing performance concerns.
• End User Segment Insight: In the predictive disease analytics market, healthcare payers are anticipated to hold a 44.9% share in 2024, leading due to their focus on cost management, risk mitigation, and population health.
• Regional Insights: North America is projected to lead the predictive disease analytics market with a 46.7% share in 2024, anticipated to grow due to advanced healthcare infrastructure and technology.

Latest Trends

• Ongoing advancements in AI, machine learning, and data analytics fuel the predictive disease analytics market. These innovations elevate predictive models, enhancing accuracy and effectiveness in disease prediction and analysis.
• The growing accessibility of varied healthcare data, such as electronic health records, genomics, and real-time patient monitoring, drives market growth while integrating diverse data sources enhances comprehensive disease predictions.
• The shift to value-based care and population health management propels the use of predictive analytics. Organizations seek tools for identifying high-risk populations, optimizing resource allocation, and enhancing health outcomes, fostering market growth.
• Increasing awareness and concern for data privacy and security impact the market. Secure data-sharing mechanisms and adherence to regulations become drivers, ensuring responsible and ethical use of healthcare data.
• The increased emphasis on public health, especially during global challenges like pandemics, drives the need for predictive disease analytics. Forecasting disease trends and implementing preventive measures becomes crucial.

Predictive Disease Analytics Market: Competitive Landscape

• The competitive landscape of the global predictive disease analytics market is shaped by industry leaders like IBM, SAS, and Microsoft leverage advanced analytics to drive innovation in predictive disease analytics. Start-ups such as Health Catalyst and Tempus introduce specialized platforms, fostering market dynamism.
• These companies form collaborations between technology giants and healthcare entities, including pharmaceutical companies like Roche and Novartis, which signify a convergence of expertise and cutting-edge technology. This diversification enhances the competitive landscape of the global predictive disease analytics market.

Some of the prominent market players:

• IBM Corporation
• SAS Institute Inc.
• Optum, Inc. (a subsidiary of UnitedHealth Group)
• Cerner Corporation
• McKesson Corporation
• Allscripts Healthcare Solutions, Inc.
• Oracle Corporation
• Microsoft Corporation
• Health Catalyst, LLC
• Epic Systems Corporation
• Inovalon Holdings, Inc.
• MedeAnalytics, Inc.
• IBM Watson Health
• Other Key Players

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Predictive Disease Analytics Market Scope

Report Highlights	Details
Market Size (2024)	USD 2.6 Bn
Forecast Value (2033)	USD 19.2 Bn
CAGR (2024-2033)	24.7%
Leading Region in terms of Revenue Share	North America
Percentage of Revenue Share by Leading Region	46.7%
Historical Data	2018 - 2023
Forecast Data	2024 - 2033
Base Year	2023
Estimate Year	2024
Segments Covered	By Component, By Deployment, By End User
Regional Coverage	North America, Europe, Asia Pacific, Latin America, Middle East & Africa (MEA)

Market Analysis

In terms of components, software and services are projected to command a dominant 71.1% market share in the global predictive disease analytics market in 2024. This dominance stems from the intricate nature of predictive disease analytics, where software serves as the central enabler due to its adaptability and customization capabilities.

Continuous updates and innovations, particularly in cloud-based solutions, further solidify software's prominence, providing scalability, accessibility, and cost-effectiveness for comprehensive disease analysis.

Growth Drivers

• Integration of AI and Machine Learning: These technologies also help in creating more precise statistics by predicting diseases and making their control better in this case, they also support the individualized approach in medicine. These models are self-learning and thus become more efficient and accurate more often.
• Rising Adoption of Cloud-Based Solutions: Business intelligence and cloud solutions like Microsoft Azure Cloud for Healthcare provide an opportunity to store and quickly access large amounts of data at a low cost. These solutions facilitate distant care and more importantly, telemedicine hence improving health care.

Restraints

• Privacy and Security Issues with Data: In this case, it is important to note that patient information is sensitive and one has to have a strong Computer/Network Security System. Rules and legislations like HIPAA as well as GDPR make compliance an extra layer of challenge, hence data privacy and security become very crucial.
• High Implementation Costs: The initial investment in the specialized equipment, software and human resources to effectively run the system is expensive and thus scares off the small healthcare organizations. Upgrades, training as well as support consumed a lot of money, and when as a constant recurrent expense it overstretched resources.

Growth Opportunities

• Expansion in Emerging Markets: Asia-Pacific and Latin America, in particular, present opportunities for growth because of the rising healthcare costs and the use of technology from these regions.
• Collaborations and Partnerships: The advancement of predictive disease analytics tools involves joint efforts between professionals from the healthcare field, information technology industry, and scientific research centers on an international level.

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Predictive Disease Analytics Market Segmentation

By Component

• Software
  • Disease Prediction Models
  • Risk Stratification Tools
  • Diagnostic Software
  • Population Health Management Software
• Services
  • Consulting Services
  • Implementation Services
  • Training & Support
  • Maintenance Services
  • Data Integration Services
• Hardware
  • Servers
  • Storage Devices
  • Network Equipment
  • Data Centers
  • Wearable Devices
  • IoT Devices

By Deployment

• On-premise
• Cloud-based

By End User

• Healthcare Payers
• Healthcare Providers
• Others

Regional Analysis

North America is projected to hold 46.7% of the predictive disease analytics market in 2024 and is expected to further grow in the upcoming period. The region's dominance is fueled by advanced healthcare infrastructure, robust technology, and heightened awareness.

The United States, a key player in this region, propels the growth of this market with significant investments, supported by government initiatives and mature regulations. North America's early adoption of predictive analytics in healthcare, driven by the rising prevalence of chronic diseases and tech acceptance, solidifies its leadership globally.

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By Region

North America

• The U.S.
• Canada

Europe

• Germany
• The U.K.
• France
• Italy
• Russia
• Spain
• Benelux
• Nordic
• Rest of Europe

Asia-Pacific

• China
• Japan
• South Korea
• India
• ANZ
• ASEAN
• Rest of Asia-Pacific

Latin America

• Brazil
• Mexico
• Argentina
• Colombia
• Rest of Latin America

Middle East & Africa

• Saudi Arabia
• UAE
• South Africa
• Israel
• Egypt
• Rest of MEA

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Recent Developments in the Predictive Disease Analytics Market

• June 2024: IBM launched an advanced version of Watson Health, incorporating enhanced AI capabilities for predictive disease analytics.
• March 2024: Microsoft announced new features for Microsoft Cloud for Healthcare, focusing on improving data integration and predictive analytics capabilities.

• December 2023: At the ONC Annual Meeting, over 25 health systems and payers pledged to uphold and focus on ethical AI, aligning with fair principles for health equity, access, and patient outcomes, emphasizing trust, risk management, and responsible research.
• November 2023: Medial EarlySign and Geisinger have introduced LungFlagTM AlgoMarker, an AI risk model for lung cancer screening. It analyzes electronic health records to identify high-risk patients for early interventions.
• November 2023: GE Healthcare revealed validated AI models predicting immunotherapy responses with 70-80% accuracy, enhancing personalized treatment selection. Presented at SITC, these models leverage EHR data for scalability, benefiting patients and drug development.
• October 2022: Zeiss collaborated with Boehringer for predictive analytics in eye diseases, employing cloud-connected devices and AI to identify early retinal disease markers for breakthrough treatments and improved quality of life.
• April 2023: Under Former WPC Healthcare/Intermedix executive guidance, IQuity introduced a data analytics platform for predicting chronic diseases. The shift to comprehensive data science emphasizes early detection, drawing interest from diverse healthcare organizations.

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