DUBLIN, July 4, 2023 /PRNewswire/ — The “Healthcare Predictive Analytics Market – Global Outlook & Forecast 2023-2028” report has been added to  ResearchAndMarkets.com’s offering.



The global healthcare predictive analytics market is expected to reach $30.71 billion by 2028 from $9.21 billion by 2022 grow at a CAGR of 22.23% from 2022-2028.

Market Trends and Drivers

Predictive AI Enhancing Patient Care and Health Outcomes

Predictive AI enhancing patient care and health outcomes is an emerging area of healthcare technology that uses artificial intelligence (AI) to help healthcare providers make informed decisions about a patient’s care.

Predictive AI can analyze vast amounts of data from multiple sources to provide insights about the patient’s condition, treatment history, and other data points that can help health professionals predict health problems and develop targeted treatment plans.

By integrating AI into patient care, healthcare providers can more accurately diagnose and treat conditions, improve patient outcomes, and reduce costs. In addition, predictive AI can identify potential risk factors for disease and provide early warning signs of health problems.

In the healthcare predictive analytics market, AI can examine patient records to predict the likelihood of certain diseases and disorders. Recent studies have shown that AI can detect previously difficult conditions to identify and diagnose, such as rare genetic and neurodegenerative diseases.

Predictive Analytics in Home Health

Predictive analytics in home health uses data-driven models and algorithms to help predict and anticipate future health outcomes or risks. These analytical methods are typically used by clinicians, administrators, providers, and health plans to identify and reduce risks in the home health care setting.

Through predictive analysis, healthcare providers can make better-informed decisions regarding patient care to improve the quality and outcomes of care.

Predictive analytics can help determine which patients are likely to require higher levels of care or may need additional services; identify patients who may benefit from personalized treatments; assess the impact of various interventions on treatment outcomes; and improve communication between providers and patients. Predictive analytics can also assess mortality, readmission rates, and healthcare costs.

Increasing Importance of Predictive Analytics in Healthcare

The increasing importance of the healthcare predictive analytics market is projected to support the healthcare analytics industry. Predictive analytics helps healthcare practitioners identify potential health issues and take preventive action before it is too late, thus providing cost and time efficiency to healthcare providers.

Data from medical sensors, clinical laboratories, pharmacy information systems, and other sources help healthcare providers deliver tailored and personalized patient care.

Predictive analytics helps organizations to identify patterns and trends in large amounts of data and utilize the insights to improve operational efficiency, reduce costs and improve patient outcomes. Predictive analytics enables the healthcare provider to predict future health trends, identify at-risk patients, and formulate relevant intervention programs. The increasing use of healthcare analytics is leading to enhanced accuracy in diagnosis, improved patient outcomes, and reduced cost.

Growing Need to Reduce Healthcare Costs Predictive Analytics

Predictive analytics has become a valuable tool in healthcare as it helps to reduce healthcare costs by enabling improved decision-making, operational improvements, and targeted interventions. Predictive analytics helps healthcare organizations anticipate costs, identify trends, and reduce costs to focus on high-value patient care. Predictive analytics helps to forecast the future with better precision and accuracy, which provides a more robust basis for decisions and actions.

Predictive analytics are also used to support decisions related to population health, such as allocating resources to patients, assessing the financial impact of different treatments, and predicting when changes should be made to maximize cost savings. The growing need to reduce healthcare costs is leading to an increased demand for predictive analytics and is driving the healthcare predictive analytics market.

Availability of Abundant Patient Data Encouraging Usage of Predictive Analytics

The availability of abundant patient data is encouraging the usage of predictive analytics in healthcare and boosts the growth of the healthcare predictive analytics market. Predictive analytics uses data mining, machine learning, and statistical techniques to identify patterns and trends that can help diagnose illnesses, identify risk factors, and predict health outcomes.

This data can also identify high-risk patients, suggest interventions, and provide insights for improving patient care. By leveraging this data, healthcare professionals can make more informed decisions, leading to better outcomes and improved patient safety.

Additionally, predictive analytics can help health organizations improve efficiency and decrease costs by reducing unnecessary testing and treatment. The availability of abundant patient data pushes healthcare organizations to adopt predictive analytics technology and use it to its fullest potential.

Vendor Landscape

The global healthcare predictive analytics market is highly competitive, with global, regional, and local players recommending a broad range of conventional and latest-generation AI technologies for end-users.

The key vendors in the market include Health Catalyst, IBM, Koninklijke Philips, Microsoft, Oracle, and UNITEDHEALTH GROUP, based on digital healthcare platforms, patient management, and clinical advancements. These companies have a wide geographic presence, diverse product portfolios, and a strong focus on product innovation, R&D, and business expansion activities.

Key Company Profiles

  • Health Catalyst

  • IBM

  • Koninklijke Philips

  • Microsoft

  • Oracle


Other Prominent Vendors

Key Questions Answered:
1. How big is the global healthcare predictive analytics market?
2. What is the growth rate of the healthcare predictive analytics market?
3. What are the growing trends in the healthcare predictive analytics industry?
4. Which region holds the most significant global healthcare predictive analytics market share?
5. Who are the key players in the global healthcare predictive analytics market?

Key Topics Covered:

1 Research Methodology

2 Research Objectives

3 Research Process

4 Scope & Coverage
4.1 Market Definition
4.1.1 Inclusions
4.1.2 Exclusions
4.1.3 Market Estimation Caveats
4.2 Base Year
4.3 Scope of the Study
4.3.1 Market Segmentation by Delivery Mode
4.3.2 Market Segmentation by Application
4.3.3 Market Segmentation by End-User
4.3.4 Market Segmentation by Geography

5 Report Assumptions & Caveats
5.1 Key Caveats
5.2 Currency Conversion
5.3 Market Derivation

6 Premium Insights
6.1 Overview
6.1.1 Geography Insights
6.1.2 Delivery Mode Segmentation Insights
6.1.3 Application Segmentation Insights
6.1.4 End-User Segmentation Insights

7 Market at a Glance

8 Introduction
8.1 Overview

9 Market Opportunities & Trends
9.1 Predictive AI Enhancing Patient Care and Health Outcomes
9.2 Predictive Analytics in Home Health
9.3 Emerging Use of Predictive Analytics in Disease Management

10 Market Growth Enablers
10.1 Increasing Importance of Predictive Analytics in Healthcare
10.2 Digital Transformation in Healthcare
10.3 Growing Need to Reduce Healthcare Costs Using Predictive Analytics
10.4 Availability of Abundant Patients Data Encouraging Use of Predictive Analytics

11 Market Restraints
11.1 Ethics and Moral Hazards in Healthcare Predictive Analytics
11.2 Serious Privacy Considerations
11.3 Impact of Technology on Care and Lack of Regulations

12 Market Landscape
12.1 Market Overview
12.2 Market Size & Forecast
12.3 Market Opportunities
12.3.1 Market by Geography
12.3.2 Market by Delivery Mode
12.3.3 Market by Application
12.3.4 Market by End-User
12.4 Five Forces Analysis
12.4.1 Threat of New Entrants
12.4.2 Bargaining Power of Suppliers
12.4.3 Bargaining Power of Buyers
12.4.4 Threat of Substitutes
12.4.5 Competitive Rivalry

13 Delivery Mode

14 Application

15 End-Users

16 Geography

17 North America

18 Europe


20 Latin America

21 Middle East & Africa

22 Competitive Landscape

23 Key Company Profiles

24 Other Prominent Vendors

25 Report Summary

26 Quantitative Summary

27 Appendix

For more information about this report visit https://www.researchandmarkets.com/r/17q5i6

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