CHICAGO, May 25, 2023 /PRNewswire/ — According to Arizton’s latest research report, the healthcare predictive analytics market will grow at a CAGR of 22.23% from 2022-2028.
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Browse In-Depth TOC on Healthcare Predictive Analytics Market
137 – Tables
123 – Charts
309 – Pages
Healthcare costs have surged, and the COVID-19 pandemic has accelerated the inflation of healthcare expenses worldwide. Limited access to quality healthcare due to financial constraints is prevalent in low- and middle-income countries (LMICs). COVID-19 has expedited various existing and emerging healthcare trends, particularly regarding health equity and environmental sustainability. Furthermore, healthcare executives globally are focused on shifting consumer preferences and behavior, integrating life sciences with the healthcare sector, rapidly advancing digital health technologies, introducing new talent and care delivery models, and implementing clinical innovation. Emerging technological applications like big data and advanced analytics are empowering health systems. Predictive analytics significantly improves patient management and ensures that treatments or surgical interventions are performed optimally. Likewise, the Internet of Things (IoT) and cloud computing can aid doctors in continuously monitoring a patient’s vital signs.
Predictive analytics has provided its value in hospital settings and at home by preventing patients from backsliding into a need for acute care. After a hospital stay, many patients are discharged without long-term health monitoring, leaving them at risk of adverse events and hospital readmissions that could have been avoided with appropriate preventative measures. Among the frail and elderly, falls at home are particularly common and a leading cause of fatal and nonfatal injuries. It presents another opportunity for predictive analytics to transform a reactive healthcare approach into a proactive one.
Healthcare Predictive Analytics Market Report Scope
|
Report Attributes |
Details |
|
Market Size (2028) |
USD 30.71 Billion |
|
Market Size (2022) |
USD 9.21 Billion |
|
CAGR (2022-2028) |
22.23 % |
|
Base Year |
2022 |
|
Forecast Year |
2023-2028 |
|
Market Segmentation |
Delivery Mode, Application, End-user, and Geography |
|
Geographic Analysis |
North America, Europe, APAC, Latin America, and Middle East & Africa |
|
Countries Covered |
US, Canada, Germany, UK, Italy, France, Spain, China, Japan, India, South Korea, Australia, Brazil, Mexico, Argentina, Turkey, Saudi Arabia, and South Africa |
|
Market Dynamics |
· Increasing Importance of Predictive Analytics in Healthcare · Digital Transformation in Healthcare · Growing Need to Reduce Healthcare Costs Predictive Analytics · Availability of Abundant Patient Data Encouraging Usage of Predictive Analytics |
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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.
Predictive AI Enhancing Patient Care and Health Outcomes
Predictive AI in healthcare is an emerging field that utilizes artificial intelligence to assist healthcare providers in making informed decisions regarding patient care. By analyzing extensive data from various sources, predictive AI offers valuable insights into a patient’s condition, treatment history, and other relevant information, enabling healthcare professionals to anticipate health issues and create targeted treatment plans. Integrating AI into patient care enhances diagnostic accuracy, treatment efficacy, patient outcomes, and cost reduction. Moreover, predictive AI can identify potential disease risk factors and provide early indications of health problems. AI can analyze patient records in healthcare predictive analytics to predict the probability of specific disorders and illnesses. Recent research has demonstrated AI’s capability to detect challenging-to-identify and diagnose conditions, including rare genetic disorders and neurodegenerative diseases.
Predictive Analytics in Home Health
Predictive analytics in home health utilizes data-driven models and algorithms to anticipate and forecast future health outcomes and risks. These analytical techniques are commonly employed by clinicians, administrators, providers, and health plans in the home healthcare setting to identify and mitigate potential risks. By leveraging predictive analytics, healthcare providers can make more informed decisions regarding patient care, leading to improved care quality and outcomes. Predictive analytics aids in identifying patients who are likely to require higher levels of care or additional services, pinpointing individuals who may benefit from personalized treatments, evaluating the impact of interventions on treatment outcomes, and enhancing communication between providers and patients. Furthermore, predictive analytics can assess outcomes such as mortality, readmission, and healthcare costs, providing valuable insights for optimizing care delivery.
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.
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Key Company Profiles
- Health Catalyst
- IBM
- Koninklijke Philips
- Microsoft
- Oracle
- UNITEDHEALTH GROUP
- Allscripts Healthcare
- Apixio
- CGI
- Change Healthcare
- Conduent
- COTIVITI
- Epic Systems
- Flatiron
- Forian
- FraudLens
- FRISS
- Healthcare Fraud Shield
- LexisNexis Risk Solutions
- MedeAnalytics
- Net Health
- OSP
- PotentiaMetrics
- SAS Institute
- Verisk Analytics
- Wipro
Market Segmentation
Delivery Mode
Application
- Finance & Operations
- Clinical Care
- Population Health Management
- R&D
End-user
- Payers
- Healthcare Settings
- Others
Geography
- North America
- Europe
- Germany
- The U.K.
- France
- Italy
- Spain
- APAC
- China
- Japan
- India
- South Korea
- Australia
- Latin America
- Middle East & Africa
- Turkey
- Saudi Arabia
- South Africa
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Table of Contents
TABLE OF CONTENTS
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
13.1 MARKET SNAPSHOT & GROWTH ENGINE
13.2 MARKET OVERVIEW
13.3 ON-PREMISES
13.3.1 MARKET OVERVIEW
13.3.2 MARKET SIZE & FORECAST
13.3.3 ON-PREMISE BY GEOGRAPHY
13.4 CLOUD-BASED
13.4.1 MARKET OVERVIEW
13.4.2 MARKET SIZE & FORECAST
13.4.3 CLOUD-BASED BY GEOGRAPHY
14 APPLICATION
14.1 MARKET SNAPSHOT & GROWTH ENGINE
14.2 MARKET OVERVIEW
14.3 FINANCE & OPERATIONS
14.3.1 MARKET OVERVIEW
14.3.2 MARKET SIZE & FORECAST
14.3.3 FINANCE & OPERATIONS BY GEOGRAPHY
14.4 CLINICAL CARE
14.4.1 MARKET OVERVIEW
14.4.2 MARKET SIZE & FORECAST
14.4.3 CLINICAL CARE BY GEOGRAPHY
14.5 POPULATION HEALTH MANAGEMENT
14.5.1 MARKET OVERVIEW
14.5.2 MARKET SIZE & FORECAST
14.5.3 POPULATION HEALTH MANAGEMENT BY GEOGRAPHY
14.6 RESEARCH & DEVELOPMENT (R&D)
14.6.1 MARKET OVERVIEW
14.6.2 MARKET SIZE & FORECAST
14.6.3 R&D BY GEOGRAPHY
15 END-USERS
15.1 MARKET SNAPSHOT & GROWTH ENGINE
15.2 MARKET OVERVIEW
15.3 PAYERS
15.3.1 MARKET OVERVIEW
15.3.2 MARKET SIZE & FORECAST
15.3.3 PAYERS BY GEOGRAPHY
15.4 HEALTHCARE SETTINGS
15.4.1 MARKET OVERVIEW
15.4.2 MARKET SIZE & FORECAST
15.4.3 HEALTHCARE SETTINGS BY GEOGRAPHY
15.5 OTHERS
15.5.1 MARKET OVERVIEW
15.5.2 MARKET SIZE & FORECAST
15.5.3 OTHERS BY GEOGRAPHY
16 GEOGRAPHY
16.1 MARKET SNAPSHOT & GROWTH ENGINE
16.2 GEOGRAPHIC OVERVIEW
17 NORTH AMERICA
17.1 MARKET OVERVIEW
17.2 MARKET SIZE & FORECAST
17.2.1 NORTH AMERICA BY DELIVERY MODE
17.2.2 NORTH AMERICA BY APPLICATION
17.2.3 NORTH AMERICA BY END-USER
17.3 KEY COUNTRIES
17.3.1 US: MARKET SIZE & FORECAST
17.3.2 CANADA: MARKET SIZE & FORECAST
18 EUROPE
18.1 MARKET OVERVIEW
18.2 MARKET SIZE & FORECAST
18.2.1 EUROPE BY DELIVERY MODE
18.2.2 EUROPE BY APPLICATION
18.2.3 EUROPE BY END-USER
18.3 KEY COUNTRIES
18.3.1 GERMANY: MARKET SIZE & FORECAST
18.3.2 UK: MARKET SIZE & FORECAST
18.3.3 FRANCE: MARKET SIZE & FORECAST
18.3.4 ITALY: MARKET SIZE & FORECAST
18.3.5 SPAIN: MARKET SIZE & FORECAST
19 APAC
19.1 MARKET OVERVIEW
19.2 MARKET SIZE & FORECAST
19.2.1 APAC BY DELIVERY MODE
19.2.2 APAC BY APPLICATION
19.2.3 APAC BY END-USER
19.3 KEY COUNTRIES
19.3.1 CHINA: MARKET SIZE & FORECAST
19.3.2 JAPAN: MARKET SIZE & FORECAST
19.3.3 INDIA: MARKET SIZE & FORECAST
19.3.4 SOUTH KOREA: MARKET SIZE & FORECAST
19.3.5 AUSTRALIA: MARKET SIZE & FORECAST
20 LATIN AMERICA
20.1 MARKET OVERVIEW
20.2 MARKET SIZE & FORECAST
20.2.1 LATIN AMERICA BY DELIVERY MODE
20.2.2 LATIN AMERICA BY APPLICATION
20.2.3 LATIN AMERICA BY END-USER
20.3 KEY COUNTRIES
20.3.1 BRAZIL: MARKET SIZE & FORECAST
20.3.2 MEXICO: MARKET SIZE & FORECAST
20.3.3 ARGENTINA: MARKET SIZE & FORECAST
21 MIDDLE EAST & AFRICA
21.1 MARKET OVERVIEW
21.2 MARKET SIZE & FORECAST
21.2.1 MIDDLE EAST & AFRICA BY DELIVERY MODE
21.2.2 MIDDLE EAST & AFRICA BY APPLICATION
21.2.3 MIDDLE EAST & AFRICA BY END-USER
21.3 KEY COUNTRIES
21.3.1 TURKEY: MARKET SIZE & FORECAST
21.3.2 SAUDI ARABIA: MARKET SIZE & FORECAST
21.3.3 SOUTH AFRICA: MARKET SIZE & FORECAST
22 COMPETITIVE LANDSCAPE
22.1 COMPETITION OVERVIEW
22.2 MARKET SHARE ANALYSIS
22.2.1 HEALTH CATALYST
22.2.2 IBM
22.2.3 KONINKLIJKE PHILIPS
22.2.4 MICROSOFT
22.2.5 ORACLE
22.2.6 UNITEDHEALTH GROUP
23 KEY COMPANY PROFILES
23.1 HEALTH CATALYST
23.1.1 BUSINESS OVERVIEW
23.1.2 PRODUCT OFFERINGS
23.1.3 KEY STRATEGIES
23.1.4 KEY STRENGTHS
23.1.5 KEY OPPORTUNITIES
23.2 IBM
23.3 KONINKLIJKE PHILIPS
23.4 MICROSOFT
23.5 ORACLE
23.6 UNITEDHEALTH GROUP
24 OTHER PROMINENT VENDORS
24.1 ALLSCRIPTS HEALTHCARE
24.1.1 BUSINESS OVERVIEW
24.1.2 PRODUCT OFFERINGS
24.2 APIXIO
24.3 CGI
24.4 CHANGE HEALTHCARE
24.5 CONDUENT
24.6 COTIVITI
24.7 EPIC SYSTEMS
24.8 FLATIRON
24.9 FORIAN
24.10 FRAUDLENS
24.11 FRISS
24.12 HEALTHCARE FRAUD SHIELD
24.13 LEXISNEXIS RISK SOLUTIONS
24.14 MEDEANALYTICS
24.15 NET HEALTH
24.16 OSP
24.17 POTENTIAMETRICS
24.18 SAS INSTITUTE
24.19 VERISK ANALYTICS
24.20 WIPRO
25 REPORT SUMMARY
25.1 KEY TAKEAWAYS
25.2 STRATEGIC RECOMMENDATIONS
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