The global healthcare predictive analytics market size is expected to reach USD 67.26 billion by 2030, registering a CAGR of 24.0% from 2024 to 2030. The rising burden of chronic diseases on a global level coupled with the increasing cost of healthcare are the key factors driving the market for healthcare predictive analytics and is resulting in wider adoption rates of the same across the globe. With the increasing adoption of telehealth and other consultation methods, the adoption of EHRs has led to enormous patient data in the past few years. This can be leveraged by the healthcare IT companies for predictive analytics for risk management, disease management, understanding of disease spread & trajectory as well as in delivering proper medical care to the patient for the best outcomes.
All of these factors have been driving the global market growth. An increase in healthcare expenditure in developed and developing countries due to a rise in the number of chronic diseases will also support market growth. In the Europe region, the healthcare expenditure as a percentage of GDP in 2019 was 9.92%. Technological advancements as well as rapid generation of patient data, more so during the COVID-19 pandemic due to teleconsultations, EHRs, etc. have made it possible to analyze data and derive meaningful results, which are oriented towards better patient outcomes. The healthcare predictive analytics tools not only help reduce costs & assist the care providers to decide on the best treatment plans but also significantly reduce the risk of fraudulent claims made to recover money from insurance companies.
Annually, trillions of U.S. dollars’ worth of false insurance claims are made. For providers, predictive analytics has been a key to reducing costs significantly. The above-mentioned factors contribute significantly to the growth of the market. The financial application of predictive analytics is the largest in the segment owing to the massive amounts of money that can be saved by deploying these predictive tools in day-to-day work. The frauds alone when detected can be averted and result in trillions of dollars saved, moreover unnecessary tests and medication can be avoided with the help of predictive analytics, which can help determine the best treatment plans and evidence-based medicine or personalized medicines for the treatment of the disease.
A trial conducted studied the financial implications of continuous monitoring in patients with opioid-induced respiratory depression, the study found that a median hospital could save up to $535,531 annually, and can shorten the cumulative stay by 103 days. The payers had the majority share of the end-use segment, comprising insurance companies who assess risk related to false claims as well as the high cost of treatments that are a concern for the providers. Adoption of predictive analytics tools for cost reduction as well as for saving money by detecting frauds in insurance claims is a major factor driving the growth of the segment. The providers are the fastest-growing category owing to the reduction in the cost of treatments and wider adoption rates among both private as well as government-affiliated providers.
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All of these factors have been driving the global market growth. An increase in healthcare expenditure in developed and developing countries due to a rise in the number of chronic diseases will also support market growth. In the Europe region, the healthcare expenditure as a percentage of GDP in 2019 was 9.92%. Technological advancements as well as rapid generation of patient data, more so during the COVID-19 pandemic due to teleconsultations, EHRs, etc. have made it possible to analyze data and derive meaningful results, which are oriented towards better patient outcomes. The healthcare predictive analytics tools not only help reduce costs & assist the care providers to decide on the best treatment plans but also significantly reduce the risk of fraudulent claims made to recover money from insurance companies.
Annually, trillions of U.S. dollars’ worth of false insurance claims are made. For providers, predictive analytics has been a key to reducing costs significantly. The above-mentioned factors contribute significantly to the growth of the market. The financial application of predictive analytics is the largest in the segment owing to the massive amounts of money that can be saved by deploying these predictive tools in day-to-day work. The frauds alone when detected can be averted and result in trillions of dollars saved, moreover unnecessary tests and medication can be avoided with the help of predictive analytics, which can help determine the best treatment plans and evidence-based medicine or personalized medicines for the treatment of the disease.
A trial conducted studied the financial implications of continuous monitoring in patients with opioid-induced respiratory depression, the study found that a median hospital could save up to $535,531 annually, and can shorten the cumulative stay by 103 days. The payers had the majority share of the end-use segment, comprising insurance companies who assess risk related to false claims as well as the high cost of treatments that are a concern for the providers. Adoption of predictive analytics tools for cost reduction as well as for saving money by detecting frauds in insurance claims is a major factor driving the growth of the segment. The providers are the fastest-growing category owing to the reduction in the cost of treatments and wider adoption rates among both private as well as government-affiliated providers.
Healthcare Predictive Analytics Market Report Highlights
- Financial application segment dominated the market in 2023 and accounted for the largest revenue share of 35.5%.
- Population health management segment is expected to grow at the fastest CAGR of 24.4% from 2024 to 2030.
- The healthcare providers segment held the largest market share in 2023. Predictive analytics can automate hospital administrative processes, predict staffing needs, and control hospital drug and supply costs, leveraging the performance of hospitals and other healthcare providers.
- Payers segment is expected to grow significantly over the forecast period. Rising medical costs have heightened the pressure on health plans to manage financial risk while maintaining quality care.
- North America healthcare predictive analytics market dominated with the largest revenue share of 48.4% in 2023. Increasing demand for personalized medicine, rising focus on improving patient care, and robust healthcare infrastructure are some of the factors driving market growth.
- Healthcare predictive analytics market in Asia Pacific is anticipated to grow at the fastest CAGR of 26.9% from 2024 to 2030 due to increasing disposable income, rising healthcare expenditure, and technological advancements such as the integration of artificial intelligence in healthcare.
Why should you buy this report?
- Comprehensive Market Analysis: Gain detailed insights into the global market across major regions and segments
- Competitive Landscape: Explore the market presence of key players worldwide
- Future Trends: Discover the pivotal trends and drivers shaping the future of the global market
- Actionable Recommendations: Utilize insights to uncover new revenue streams and guide strategic business decisions
This report addresses:
- Market intelligence to enable effective decision-making
- Market estimates and forecasts from 2018 to 2030
- Growth opportunities and trend analyses
- Segment and regional revenue forecasts for market assessment
- Competition strategy and market share analysis
- Product innovation listing for you to stay ahead of the curve
- COVID-19's impact and how to sustain in these fast-evolving markets
The leading players in the Healthcare Predictive Analytics market include:
- IBM
- Verisk Analytics, Inc.
- McKesson Corp.
- SAS
- Oracle
- Allscripts (now Veradigm)
- Optum, Inc.
- MedeAnalytics, Inc.
- INFRAGISTICS
- Cloudera
- Health Catalyst
- IQVIA Inc
- Inovalon
- OSP
- ClosedLoop
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Table of Contents
Chapter 1. Methodology and Scope
Chapter 2. Executive Summary
Chapter 3. Healthcare Predictive Analytics Market Variables, Trends & Scope
Chapter 4. Healthcare Predictive Analytics Market: Application Estimates & Trend Analysis
Chapter 5. Healthcare Predictive Analytics Market: End Use Estimates & Trend Analysis
Chapter 6. Healthcare Predictive Analytics Market: Regional Estimates & Trend Analysis
Chapter 7. Competitive Landscape
List of Tables
List of Figures
Companies Mentioned
- IBM
- Verisk Analytics, Inc.
- McKesson Corp.
- SAS
- Oracle
- Allscripts (now Veradigm)
- Optum, Inc.
- MedeAnalytics, Inc.
- INFRAGISTICS
- Cloudera
- Health Catalyst
- IQVIA Inc
- Inovalon
- OSP
- ClosedLoop
Methodology
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Table Information
Report Attribute | Details |
---|---|
No. of Pages | 120 |
Published | October 2024 |
Forecast Period | 2023 - 2030 |
Estimated Market Value ( USD | $ 14.58 Billion |
Forecasted Market Value ( USD | $ 67.26 Billion |
Compound Annual Growth Rate | 24.0% |
Regions Covered | Global |
No. of Companies Mentioned | 15 |