Healthcare Predictive Analytics Market Size, Share & Trends Analysis Report By Application (Clinical, Financial, Operations Management), By End-use (Payers, Providers), By Region, And Segment Forecasts, 2024 - 2030
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Healthcare Predictive Analytics Market Growth & Trends
The global healthcare predictive analytics market size is expected treach USD 67.26 billion by 2030, registering a CAGR of 24.0% from 2024 t2030, according ta new report by Grand View Research, Inc. 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 tenormous 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 tthe 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 ta rise in the number of chronic diseases will alssupport 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 sduring the COVID-19 pandemic due tteleconsultations, EHRs, etc. have made it possible tanalyze 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 tdecide on the best treatment plans but alssignificantly reduce the risk of fraudulent claims made trecover 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 treducing costs significantly. The above-mentioned factors contribute significantly tthe growth of the market. The financial application of predictive analytics is the largest in the segment owing tthe 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 t$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 whassess risk related tfalse 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 tthe 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
Healthcare Predictive Analytics Market Growth & Trends
The global healthcare predictive analytics market size is expected treach USD 67.26 billion by 2030, registering a CAGR of 24.0% from 2024 t2030, according ta new report by Grand View Research, Inc. 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 tenormous 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 tthe 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 ta rise in the number of chronic diseases will alssupport 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 sduring the COVID-19 pandemic due tteleconsultations, EHRs, etc. have made it possible tanalyze 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 tdecide on the best treatment plans but alssignificantly reduce the risk of fraudulent claims made trecover 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 treducing costs significantly. The above-mentioned factors contribute significantly tthe growth of the market. The financial application of predictive analytics is the largest in the segment owing tthe 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 t$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 whassess risk related tfalse 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 tthe 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 tgrow at the fastest CAGR of 24.4% from 2024 t2030.
- 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 tgrow significantly over the forecast period. Rising medical costs have heightened the pressure on health plans tmanage 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 tgrow at the fastest CAGR of 26.9% from 2024 t2030 due tincreasing disposable income, rising healthcare expenditure, and technological advancements such as the integration of artificial intelligence in healthcare.
CHAPTER 1. METHODOLOGY AND SCOPE
1.1. Market Segmentation & Scope
1.2. Market Definitions
1.2.1. Application Segment
1.2.2. End Use Segment
1.3. Information analysis
1.3.1. Market formulation & data visualization
1.4. Data validation & publishing
1.5. Information Procurement
1.5.1. Primary Research
1.6. Information or Data Analysis
1.7. Market Formulation & Validation
1.8. Market Model
1.9. Total Market: CAGR Calculation
1.10. Objectives
1.10.1. Objective
1.10.2. Objective
CHAPTER 2. EXECUTIVE SUMMARY
2.1. Market Outlook
2.2. Segment Snapshot
2.3. Competitive Insights Landscape
CHAPTER 3. HEALTHCARE PREDICTIVE ANALYTICS MARKET VARIABLES, TRENDS & SCOPE
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook.
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.1.1. Rising Adoption of Electronic Health Records (EHRs) and Big Data
3.2.1.2. Advancements in artificial intelligence (AI) and machine learning technologies
3.2.1.3. Rising prevalence of chronic diseases and growing focus on personalized medicine
3.2.2. Market restraint analysis
3.2.2.1. Ethical concerns related to data privacy
3.3. Healthcare Predictive Analytics Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Supplier power
3.3.1.2. Buyer power
3.3.1.3. Substitution threat
3.3.1.4. Threat of new entrant
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political landscape
3.3.2.2. Technological landscape
3.3.2.3. Economic landscape
3.3.2.4. Environmental Landscape
3.3.2.5. Legal Landscape
3.3.2.6. Social Landscape
3.3.3. Regulatory Framework
3.3.4. Emerging Technologies Trends
3.3.5. Case Study & Insights
3.3.5.1. Use Cases
3.3.5.2. Related Survey
3.3.6. COVID-19 Impact Analysis
CHAPTER 4. HEALTHCARE PREDICTIVE ANALYTICS MARKET: APPLICATION ESTIMATES & TREND ANALYSIS
4.1. Segment Dashboard
4.2. Global Healthcare Predictive Analytics Market Application Movement Analysis
4.3. Global Healthcare Predictive Analytics Market Size & Trend Analysis, by Application, 2018 to 2030 (USD Million)
4.4. Operations Management
4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.2. Demand Forecasting
4.4.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.3. Workforce Planning and Scheduling
4.4.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.4. Inpatient Scheduling
4.4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.5. Outpatient Scheduling
4.4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5. Financial
4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5.2. Revenue Cycle Management
4.5.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5.3. Fraud Detection
4.5.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5.4. Other Financial Applications
4.5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6. Population Health
4.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.2. Population Risk Management
4.6.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.3. Patient Engagement
4.6.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.4. Population Therapy Management
4.6.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.5. Other Applications
4.6.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7. Clinical
4.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7.2. Quality Benchmarking
4.7.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7.3. Patient Care Enhancement
4.7.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7.4. Clinical Outcome Analysis and Management
4.7.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
CHAPTER 5. HEALTHCARE PREDICTIVE ANALYTICS MARKET: END USE ESTIMATES & TREND ANALYSIS
5.1. Segment Dashboard
5.2. Global Healthcare Predictive Analytics Market End Use Movement Analysis
5.3. Global Healthcare Predictive Analytics Market Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
5.4. Payers
5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
5.5. Providers
5.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
5.6. Life Science Industry
5.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
CHAPTER 6. HEALTHCARE PREDICTIVE ANALYTICS MARKET: REGIONAL ESTIMATES & TREND ANALYSIS
6.1. Regional Market Share Analysis, 2023 & 2030
6.2. Regional Market Dashboard
6.3. Market Size, & Forecasts Trend Analysis, 2018 to 2030:
6.4. North America
6.4.1. U.S.
6.4.1.1. Key country dynamics
6.4.1.2. Regulatory framework/ reimbursement structure
6.4.1.3. Competitive scenario
6.4.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
6.4.2. Canada
6.4.2.1. Key country dynamics
6.4.2.2. Regulatory framework/ reimbursement structure
6.4.2.3. Competitive scenario
6.4.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
6.4.3. Mexico
6.4.3.1. Key country dynamics
6.4.3.2. Regulatory framework/ reimbursement structure
6.4.3.3. Competitive scenario
6.4.3.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
6.5. Europe
6.5.1. UK
6.5.1.1. Key country dynamics
6.5.1.2. Regulatory framework/ reimbursement structure
6.5.1.3. Competitive scenario
6.5.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
6.5.2. Germany
6.5.2.1. Key country dynamics
6.5.2.2. Regulatory framework/ reimbursement structure
6.5.2.3. Competitive scenario
6.5.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
6.5.3. France
6.5.3.1. Key country dynamics
6.5.3.2. Regulatory framework/ reimbursement structure
6.5.3.3. Competitive scenario
6.5.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
6.5.4. Italy
6.5.4.1. Key country dynamics
6.5.4.2. Regulatory framework/ reimbursement structure
6.5.4.3. Competitive scenario
6.5.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
6.5.5. Spain
6.5.5.1. Key country dynamics
6.5.5.2. Regulatory framework/ reimbursement structure
6.5.5.3. Competitive scenario
6.5.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
6.5.6. Norway
6.5.6.1. Key country dynamics
6.5.6.2. Regulatory framework/ reimbursement structure
6.5.6.3. Competitive scenario
6.5.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
6.5.7. Sweden
6.5.7.1. Key country dynamics
6.5.7.2. Regulatory framework/ reimbursement structure
6.5.7.3. Competitive scenario
6.5.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
6.5.8. Denmark
6.5.8.1. Key country dynamics
6.5.8.2. Regulatory framework/ reimbursement structure
6.5.8.3. Competitive scenario
6.5.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
6.6. Asia Pacific
6.6.1. Japan
6.6.1.1. Key country dynamics
6.6.1.2. Regulatory framework/ reimbursement structure
6.6.1.3. Competitive scenario
6.6.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
6.6.2. China
6.6.2.1. Key country dynamics
6.6.2.2. Regulatory framework/ reimbursement structure
6.6.2.3. Competitive scenario
6.6.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
6.6.3. India
6.6.3.1. Key country dynamics
6.6.3.2. Regulatory framework/ reimbursement structure
6.6.3.3. Competitive scenario
6.6.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
6.6.4. Australia
6.6.4.1. Key country dynamics
6.6.4.2. Regulatory framework/ reimbursement structure
6.6.4.3. Competitive scenario
6.6.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
6.6.5. South Korea
6.6.5.1. Key country dynamics
6.6.5.2. Regulatory framework/ reimbursement structure
6.6.5.3. Competitive scenario
6.6.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
6.6.6. Thailand
6.6.6.1. Key country dynamics
6.6.6.2. Regulatory framework/ reimbursement structure
6.6.6.3. Competitive scenario
6.6.6.4. Thailand market estimates and forecasts 2018 to 2030 (USD Million)
6.7. Latin America
6.7.1. Brazil
6.7.1.1. Key country dynamics
6.7.1.2. Regulatory framework/ reimbursement structure
6.7.1.3. Competitive scenario
6.7.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
6.7.2. Argentina
6.7.2.1. Key country dynamics
6.7.2.2. Regulatory framework/ reimbursement structure
6.7.2.3. Competitive scenario
6.7.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
6.8. MEA
6.8.1. South Africa
6.8.1.1. Key country dynamics
6.8.1.2. Regulatory framework/ reimbursement structure
6.8.1.3. Competitive scenario
6.8.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
6.8.2. Saudi Arabia
6.8.2.1. Key country dynamics
6.8.2.2. Regulatory framework/ reimbursement structure
6.8.2.3. Competitive scenario
6.8.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
6.8.3. UAE
6.8.3.1. Key country dynamics
6.8.3.2. Regulatory framework/ reimbursement structure
6.8.3.3. Competitive scenario
6.8.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
6.8.4. Kuwait
6.8.4.1. Key country dynamics
6.8.4.2. Regulatory framework/ reimbursement structure
6.8.4.3. Competitive scenario
6.8.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)
CHAPTER 7. COMPETITIVE LANDSCAPE
7.1. Company/Competition Categorization
7.2. Strategy Mapping
7.3. Company Market Position Analysis, 2023
7.4. Company Profiles/Listing
7.4.1. IBM
7.4.1.1. Company overview
7.4.1.2. Financial performance
7.4.1.3. Product benchmarking
7.4.1.4. Strategic initiatives
7.4.2. Verisk Analytics, Inc.
7.4.2.1. Company overview
7.4.2.2. Financial performance
7.4.2.3. Product benchmarking
7.4.2.4. Strategic initiatives
7.4.3. McKesson Corp.
7.4.3.1. Company overview
7.4.3.2. Financial performance
7.4.3.3. Product benchmarking
7.4.3.4. Strategic initiatives
7.4.4. SAS
7.4.4.1. Company overview
7.4.4.2. Financial performance
7.4.4.3. Product benchmarking
7.4.4.4. Strategic initiatives
7.4.5. Oracle
7.4.5.1. Company overview
7.4.5.2. Financial performance
7.4.5.3. Product benchmarking
7.4.5.4. Strategic initiatives
7.4.6. Allscripts (now Veradigm)
7.4.6.1. Company overview
7.4.6.2. Financial performance
7.4.6.3. Product benchmarking
7.4.6.4. Strategic initiatives
7.4.7. Optum, Inc.
7.4.7.1. Company overview
7.4.7.2. Financial performance
7.4.7.3. Product benchmarking
7.4.7.4. Strategic initiatives
7.4.8. MedeAnalytics, Inc.
7.4.8.1. Company overview
7.4.8.2. Financial performance
7.4.8.3. Product benchmarking
7.4.8.4. Strategic initiatives
7.4.9. INFRAGISTICS
7.4.9.1. Company overview
7.4.9.2. Financial performance
7.4.9.3. Product benchmarking
7.4.9.4. Strategic initiatives
7.4.10. Cloudera
7.4.10.1. Company overview
7.4.10.2. Financial performance
7.4.10.3. Product benchmarking
7.4.10.4. Strategic initiatives
7.4.11. Health Catalyst
7.4.11.1. Company overview
7.4.11.2. Financial performance
7.4.11.3. Product benchmarking
7.4.11.4. Strategic initiatives
7.4.12. IQVIA Inc
7.4.12.1. Company overview
7.4.12.2. Financial performance
7.4.12.3. Product benchmarking
7.4.12.4. Strategic initiatives
7.4.13. Inovalon
7.4.13.1. Company overview
7.4.13.2. Financial performance
7.4.13.3. Product benchmarking
7.4.13.4. Strategic initiatives
7.4.14. OSP
7.4.14.1. Company overview
7.4.14.2. Financial performance
7.4.14.3. Product benchmarking
7.4.14.4. Strategic initiatives
1.1. Market Segmentation & Scope
1.2. Market Definitions
1.2.1. Application Segment
1.2.2. End Use Segment
1.3. Information analysis
1.3.1. Market formulation & data visualization
1.4. Data validation & publishing
1.5. Information Procurement
1.5.1. Primary Research
1.6. Information or Data Analysis
1.7. Market Formulation & Validation
1.8. Market Model
1.9. Total Market: CAGR Calculation
1.10. Objectives
1.10.1. Objective
1.10.2. Objective
CHAPTER 2. EXECUTIVE SUMMARY
2.1. Market Outlook
2.2. Segment Snapshot
2.3. Competitive Insights Landscape
CHAPTER 3. HEALTHCARE PREDICTIVE ANALYTICS MARKET VARIABLES, TRENDS & SCOPE
3.1. Market Lineage Outlook
3.1.1. Parent market outlook
3.1.2. Related/ancillary market outlook.
3.2. Market Dynamics
3.2.1. Market driver analysis
3.2.1.1. Rising Adoption of Electronic Health Records (EHRs) and Big Data
3.2.1.2. Advancements in artificial intelligence (AI) and machine learning technologies
3.2.1.3. Rising prevalence of chronic diseases and growing focus on personalized medicine
3.2.2. Market restraint analysis
3.2.2.1. Ethical concerns related to data privacy
3.3. Healthcare Predictive Analytics Market Analysis Tools
3.3.1. Industry Analysis - Porter’s
3.3.1.1. Supplier power
3.3.1.2. Buyer power
3.3.1.3. Substitution threat
3.3.1.4. Threat of new entrant
3.3.1.5. Competitive rivalry
3.3.2. PESTEL Analysis
3.3.2.1. Political landscape
3.3.2.2. Technological landscape
3.3.2.3. Economic landscape
3.3.2.4. Environmental Landscape
3.3.2.5. Legal Landscape
3.3.2.6. Social Landscape
3.3.3. Regulatory Framework
3.3.4. Emerging Technologies Trends
3.3.5. Case Study & Insights
3.3.5.1. Use Cases
3.3.5.2. Related Survey
3.3.6. COVID-19 Impact Analysis
CHAPTER 4. HEALTHCARE PREDICTIVE ANALYTICS MARKET: APPLICATION ESTIMATES & TREND ANALYSIS
4.1. Segment Dashboard
4.2. Global Healthcare Predictive Analytics Market Application Movement Analysis
4.3. Global Healthcare Predictive Analytics Market Size & Trend Analysis, by Application, 2018 to 2030 (USD Million)
4.4. Operations Management
4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.2. Demand Forecasting
4.4.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.3. Workforce Planning and Scheduling
4.4.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.4. Inpatient Scheduling
4.4.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.4.5. Outpatient Scheduling
4.4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5. Financial
4.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5.2. Revenue Cycle Management
4.5.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5.3. Fraud Detection
4.5.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.5.4. Other Financial Applications
4.5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6. Population Health
4.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.2. Population Risk Management
4.6.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.3. Patient Engagement
4.6.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.4. Population Therapy Management
4.6.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.6.5. Other Applications
4.6.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7. Clinical
4.7.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7.2. Quality Benchmarking
4.7.2.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7.3. Patient Care Enhancement
4.7.3.1. Market estimates and forecasts 2018 to 2030 (USD Million)
4.7.4. Clinical Outcome Analysis and Management
4.7.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
CHAPTER 5. HEALTHCARE PREDICTIVE ANALYTICS MARKET: END USE ESTIMATES & TREND ANALYSIS
5.1. Segment Dashboard
5.2. Global Healthcare Predictive Analytics Market End Use Movement Analysis
5.3. Global Healthcare Predictive Analytics Market Size & Trend Analysis, by End Use, 2018 to 2030 (USD Million)
5.4. Payers
5.4.1. Market estimates and forecasts 2018 to 2030 (USD Million)
5.5. Providers
5.5.1. Market estimates and forecasts 2018 to 2030 (USD Million)
5.6. Life Science Industry
5.6.1. Market estimates and forecasts 2018 to 2030 (USD Million)
CHAPTER 6. HEALTHCARE PREDICTIVE ANALYTICS MARKET: REGIONAL ESTIMATES & TREND ANALYSIS
6.1. Regional Market Share Analysis, 2023 & 2030
6.2. Regional Market Dashboard
6.3. Market Size, & Forecasts Trend Analysis, 2018 to 2030:
6.4. North America
6.4.1. U.S.
6.4.1.1. Key country dynamics
6.4.1.2. Regulatory framework/ reimbursement structure
6.4.1.3. Competitive scenario
6.4.1.4. U.S. market estimates and forecasts 2018 to 2030 (USD Million)
6.4.2. Canada
6.4.2.1. Key country dynamics
6.4.2.2. Regulatory framework/ reimbursement structure
6.4.2.3. Competitive scenario
6.4.2.4. Canada market estimates and forecasts 2018 to 2030 (USD Million)
6.4.3. Mexico
6.4.3.1. Key country dynamics
6.4.3.2. Regulatory framework/ reimbursement structure
6.4.3.3. Competitive scenario
6.4.3.4. Mexico market estimates and forecasts 2018 to 2030 (USD Million)
6.5. Europe
6.5.1. UK
6.5.1.1. Key country dynamics
6.5.1.2. Regulatory framework/ reimbursement structure
6.5.1.3. Competitive scenario
6.5.1.4. UK market estimates and forecasts 2018 to 2030 (USD Million)
6.5.2. Germany
6.5.2.1. Key country dynamics
6.5.2.2. Regulatory framework/ reimbursement structure
6.5.2.3. Competitive scenario
6.5.2.4. Germany market estimates and forecasts 2018 to 2030 (USD Million)
6.5.3. France
6.5.3.1. Key country dynamics
6.5.3.2. Regulatory framework/ reimbursement structure
6.5.3.3. Competitive scenario
6.5.3.4. France market estimates and forecasts 2018 to 2030 (USD Million)
6.5.4. Italy
6.5.4.1. Key country dynamics
6.5.4.2. Regulatory framework/ reimbursement structure
6.5.4.3. Competitive scenario
6.5.4.4. Italy market estimates and forecasts 2018 to 2030 (USD Million)
6.5.5. Spain
6.5.5.1. Key country dynamics
6.5.5.2. Regulatory framework/ reimbursement structure
6.5.5.3. Competitive scenario
6.5.5.4. Spain market estimates and forecasts 2018 to 2030 (USD Million)
6.5.6. Norway
6.5.6.1. Key country dynamics
6.5.6.2. Regulatory framework/ reimbursement structure
6.5.6.3. Competitive scenario
6.5.6.4. Norway market estimates and forecasts 2018 to 2030 (USD Million)
6.5.7. Sweden
6.5.7.1. Key country dynamics
6.5.7.2. Regulatory framework/ reimbursement structure
6.5.7.3. Competitive scenario
6.5.7.4. Sweden market estimates and forecasts 2018 to 2030 (USD Million)
6.5.8. Denmark
6.5.8.1. Key country dynamics
6.5.8.2. Regulatory framework/ reimbursement structure
6.5.8.3. Competitive scenario
6.5.8.4. Denmark market estimates and forecasts 2018 to 2030 (USD Million)
6.6. Asia Pacific
6.6.1. Japan
6.6.1.1. Key country dynamics
6.6.1.2. Regulatory framework/ reimbursement structure
6.6.1.3. Competitive scenario
6.6.1.4. Japan market estimates and forecasts 2018 to 2030 (USD Million)
6.6.2. China
6.6.2.1. Key country dynamics
6.6.2.2. Regulatory framework/ reimbursement structure
6.6.2.3. Competitive scenario
6.6.2.4. China market estimates and forecasts 2018 to 2030 (USD Million)
6.6.3. India
6.6.3.1. Key country dynamics
6.6.3.2. Regulatory framework/ reimbursement structure
6.6.3.3. Competitive scenario
6.6.3.4. India market estimates and forecasts 2018 to 2030 (USD Million)
6.6.4. Australia
6.6.4.1. Key country dynamics
6.6.4.2. Regulatory framework/ reimbursement structure
6.6.4.3. Competitive scenario
6.6.4.4. Australia market estimates and forecasts 2018 to 2030 (USD Million)
6.6.5. South Korea
6.6.5.1. Key country dynamics
6.6.5.2. Regulatory framework/ reimbursement structure
6.6.5.3. Competitive scenario
6.6.5.4. South Korea market estimates and forecasts 2018 to 2030 (USD Million)
6.6.6. Thailand
6.6.6.1. Key country dynamics
6.6.6.2. Regulatory framework/ reimbursement structure
6.6.6.3. Competitive scenario
6.6.6.4. Thailand market estimates and forecasts 2018 to 2030 (USD Million)
6.7. Latin America
6.7.1. Brazil
6.7.1.1. Key country dynamics
6.7.1.2. Regulatory framework/ reimbursement structure
6.7.1.3. Competitive scenario
6.7.1.4. Brazil market estimates and forecasts 2018 to 2030 (USD Million)
6.7.2. Argentina
6.7.2.1. Key country dynamics
6.7.2.2. Regulatory framework/ reimbursement structure
6.7.2.3. Competitive scenario
6.7.2.4. Argentina market estimates and forecasts 2018 to 2030 (USD Million)
6.8. MEA
6.8.1. South Africa
6.8.1.1. Key country dynamics
6.8.1.2. Regulatory framework/ reimbursement structure
6.8.1.3. Competitive scenario
6.8.1.4. South Africa market estimates and forecasts 2018 to 2030 (USD Million)
6.8.2. Saudi Arabia
6.8.2.1. Key country dynamics
6.8.2.2. Regulatory framework/ reimbursement structure
6.8.2.3. Competitive scenario
6.8.2.4. Saudi Arabia market estimates and forecasts 2018 to 2030 (USD Million)
6.8.3. UAE
6.8.3.1. Key country dynamics
6.8.3.2. Regulatory framework/ reimbursement structure
6.8.3.3. Competitive scenario
6.8.3.4. UAE market estimates and forecasts 2018 to 2030 (USD Million)
6.8.4. Kuwait
6.8.4.1. Key country dynamics
6.8.4.2. Regulatory framework/ reimbursement structure
6.8.4.3. Competitive scenario
6.8.4.4. Kuwait market estimates and forecasts 2018 to 2030 (USD Million)
CHAPTER 7. COMPETITIVE LANDSCAPE
7.1. Company/Competition Categorization
7.2. Strategy Mapping
7.3. Company Market Position Analysis, 2023
7.4. Company Profiles/Listing
7.4.1. IBM
7.4.1.1. Company overview
7.4.1.2. Financial performance
7.4.1.3. Product benchmarking
7.4.1.4. Strategic initiatives
7.4.2. Verisk Analytics, Inc.
7.4.2.1. Company overview
7.4.2.2. Financial performance
7.4.2.3. Product benchmarking
7.4.2.4. Strategic initiatives
7.4.3. McKesson Corp.
7.4.3.1. Company overview
7.4.3.2. Financial performance
7.4.3.3. Product benchmarking
7.4.3.4. Strategic initiatives
7.4.4. SAS
7.4.4.1. Company overview
7.4.4.2. Financial performance
7.4.4.3. Product benchmarking
7.4.4.4. Strategic initiatives
7.4.5. Oracle
7.4.5.1. Company overview
7.4.5.2. Financial performance
7.4.5.3. Product benchmarking
7.4.5.4. Strategic initiatives
7.4.6. Allscripts (now Veradigm)
7.4.6.1. Company overview
7.4.6.2. Financial performance
7.4.6.3. Product benchmarking
7.4.6.4. Strategic initiatives
7.4.7. Optum, Inc.
7.4.7.1. Company overview
7.4.7.2. Financial performance
7.4.7.3. Product benchmarking
7.4.7.4. Strategic initiatives
7.4.8. MedeAnalytics, Inc.
7.4.8.1. Company overview
7.4.8.2. Financial performance
7.4.8.3. Product benchmarking
7.4.8.4. Strategic initiatives
7.4.9. INFRAGISTICS
7.4.9.1. Company overview
7.4.9.2. Financial performance
7.4.9.3. Product benchmarking
7.4.9.4. Strategic initiatives
7.4.10. Cloudera
7.4.10.1. Company overview
7.4.10.2. Financial performance
7.4.10.3. Product benchmarking
7.4.10.4. Strategic initiatives
7.4.11. Health Catalyst
7.4.11.1. Company overview
7.4.11.2. Financial performance
7.4.11.3. Product benchmarking
7.4.11.4. Strategic initiatives
7.4.12. IQVIA Inc
7.4.12.1. Company overview
7.4.12.2. Financial performance
7.4.12.3. Product benchmarking
7.4.12.4. Strategic initiatives
7.4.13. Inovalon
7.4.13.1. Company overview
7.4.13.2. Financial performance
7.4.13.3. Product benchmarking
7.4.13.4. Strategic initiatives
7.4.14. OSP
7.4.14.1. Company overview
7.4.14.2. Financial performance
7.4.14.3. Product benchmarking
7.4.14.4. Strategic initiatives
