Healthcare Predictive Analytics Market

Healthcare Predictive Analytics Market by Application (Clinical [Clinical Outcome Analysis & Management, Patient Care Enhancement, and Quality Benchmarking], Population Health [Population Therapy Management, Patient Engagement, Population Therapy Management, and Others], Financial [Fraud Detection, Revenue Cycle Management, and Others], and Operations Management [Outpatient Scheduling, Inpatient Scheduling, Workforce Planning & Scheduling, and Demand Forecasting]), End-user (Healthcare Payers, Healthcare Providers, and Others), and Regions (Asia Pacific, North America, Latin America, Europe, and Middle East & Africa) - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast 2022 – 2030

  • Report ID: HC-4741
  • Author: Growth Market Reports
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  • No. Of Pages: 199
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The healthcare predictive analytics market size was around USD 10 billion in 2021 and is expected to reach USD 67 billion by 2030, expanding at a Compound Annual Growth Rate (CAGR) of 24% during the forecast period, 2022 – 2030. The growth of the market is attributed to the increasing demand for technologically advanced analytics systems to enhance patient outcomes and reduce costs.

Healthcare Predictive Analytics Market by Key Takeaways

In the field of data analytics, predictive analytics is a discipline that significantly utilizes modeling, data mining, artificial intelligence (AI), and machine learning. It is used to assess data from the past and present to generate future predictions. Healthcare practitioners can use predictive analytics to identify possibilities to make operational and clinical decisions that are effective and efficient, forecast trends, and even control the spread of diseases. This is done by analyzing both historical and current healthcare data. Medical and administrative records, health surveys, patient and disease registries, claims-based datasets, and electronic health records (EHRs) are all sources of healthcare data, which is any information about the health problems of an individual or a group of individuals. Healthcare organizations, hospitals, doctors, physicians, pharmacists, psychologists, pharmaceutical companies, and even healthcare stakeholders are estimated to use and benefit from healthcare analytics as a tool to provide high-quality care. Analytics has a huge impact on the healthcare sector as a result of technology innovation.

Spending on healthcare has significantly increased in every country. The increase in spending is intended to strengthen the US health systems, which is projected to boost the sector's effectiveness. Predictive analytics implementation can help cut the cost of medical procedures by a considerable amount. Predictive analytics and customized medicine can not only reduce excessive medical expenses but also improve patient results and outcomes. Rising prevalence of chronic diseases is one of the major factors driving the market.

COVID-19 Impact

The COVID-19 pandemic caused the sector to incur enormous expenses. Predictive analytics has been essential in addressing resource management during the crisis, reducing the number of patients with poor outcomes, and tackling COVID-19-related problems. The massive volume of patient data generated during the pandemic not only gave analytics organizations and the healthcare sector information to accurately analyze the spread of disease but also assisted in the efficient use of resources. Hospitals and other institutions employed predictive analytics to access the patient's infection/disease trajectory, the chance of developing serious symptoms, and a number of other parameters. For instance, in 2020, researchers in Cleveland Clinic, USA, worked on a predictive analytics model that calculated a person's probability of testing positive for COVID-19 as well as the results from it. 

Market Dynamics

The market research report on the global healthcare predictive analytics market provides a detailed analysis by focusing on revenue growth, facts, figures, and historical data to determine major drivers, existing restraints, key opportunities, and competitive analysis. The report includes recent developments that can shape the overall performance of the market during the assessment period, 2022 to 2030.

Healthcare Predictive Analytics Market-DROs

Major Drivers:

Growing Use of Electronic Health Records to Improve the Management of Patient Outcomes

Predictive analytics in healthcare offers many benefits for using electronic health services. The demand for healthcare predictive analytics is increased by these services' use in managing patient records and producing correct results. These analytics are essential for providing effective clinical treatments at various biotech and pharmaceutical organizations. A number of healthcare organizations, such as Flatiron Health, NextGen Healthcare, GNS Healthcare, and Komodo Health, offer advanced technology that produces precise and speedy diagnoses at the time of treatment. These analytics are employed to lower the frequency of expensive hospitalization. These factors are estimated to drive the market.

Existing Restraints:

Lack of infrastructure is projected to hinder the market growth

Lack of infrastructure is the major problem faced by the healthcare sector. Healthcare IT infrastructure is still a burden for many healthcare organizations. In order to deploy new technologies in this sector, these firms need the appropriate labor. As a result, the healthcare predictive analytics market's expansion is hindered by the absence of a strong infrastructure for the healthcare industry and the scarcity of competent IT workers in the healthcare sector.

Key Opportunities:

Implementation of AI in healthcare predictive analytics system is projected to create immense growth opportunities

The adoption of evidence-based medicine as a means of providing the appropriate care to suitable patient is projected to boost the market in the coming years. Electronic health records (EHRs) are increasingly being used to store patient data. In the U.S., office-based physicians adopted EHRs at a rate of nearly 86% in 2019 from 42% in 2010. EHRs are used in healthcare predictive analytics to advise the optimal course of action for any operation or drug. In addition to significantly lowering patient expenses, this also generates better results. The use of electronic health systems, combined with analytics software and AI, is anticipated to create immense growth opportunities for the key players in the market. 

Scope of the Report

The report on the global healthcare predictive analytics market includes an assessment of the market trends, segments, and regional markets. Overview and dynamics have also been included in the report.

Attributes

Details

Report Title

Healthcare Predictive Analytics Market - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast

Base Year

2021

Historic Data

2019–2020

Forecast Period

2022 – 2030

Segmentation

Application (Clinical [Clinical Outcome Analysis & Management, Patient Care Enhancement, and Quality Benchmarking], Population Health [Population Therapy Management, Patient Engagement, Population Therapy Management, and Others], Financial [Fraud Detection, Revenue Cycle Management, and Others], and Operations Management [Outpatient Scheduling, Inpatient Scheduling, Workforce Planning & Scheduling, and Demand Forecasting]) and End-user (Healthcare Payers, Healthcare Providers, and Others)

Regional Scope

Asia Pacific, North America, Latin America, Europe, and Middle East & Africa

Report Coverage

Company Share, Market Analysis and Size, Competitive Landscape, Growth Factors, Market Trends, and Revenue Forecast

Key Players Covered in the Report

IBM; Cerner Corp.; Verisk Analytics, Inc.; McKesson Corp.; SAS; Oracle; Allscripts; Optum, Inc.; and MedeAnalytics, Inc.

Market Segment Insights

The financial segment held a key market share in 2021

Based on application, the global market is segregated into clinical, population health, financial, and operations management. The clinical segment is further segregated into clinical outcome analysis & management, patient care enhancement, and quality benchmarking. The population health segment is sub-fragmented into population therapy management, patient engagement, population therapy management, and others. The financial segment is further divided into fraud detection, revenue cycle management, and others. The operations management segment is categorized into outpatient scheduling, inpatient scheduling, workforce planning & scheduling, and demand forecasting. The financial segment accounted for a market share of around 36% in 2021. Revenue cycle management, determining the risk of fraud, and minimizing false claims—which cost the healthcare sector billions of dollars annually—are examples of financial applications. According to the National Healthcare Fraud Association, there is fraud worth close to USD 80 billion committed in the United States each year. This form of application is advantageous to both public and government-funded institutions in addition to private businesses. The market has expanded as a result of the increasing use of predictive analytics in finance.

The population health segment is projected to expand at a high CAGR during the forecast period. The identification of populations that require appropriate medical care can be done through population health management, which is made possible by the creation of massive volumes of patient data through telehealth, other internet platforms, and connected devices.

The clinical segment is estimated to grow at a rapid pace during the projected period. Clinical data analytics assist patients and caregivers with concerns related to healing from surgery, such as reaction to allergies and medicines, poor physical function, and surgical site infections because electronic health records have provided healthcare practitioners with past information about patients' medical conditions. Clinical data analytics also allow people to repeatedly describe their medical issues to multiple doctors. This can be accomplished by performing a thorough examination of their clinical data and giving further preventive treatment. The growth of the clinical data analytics segment is anticipated to result in low healthcare costs, accessibility to big data in the healthcare sector, and technological advances.

The payers segment accounted for a major market share in 2021

On the basis of end-user, the global market is fragmented into healthcare payers, healthcare providers, and others. The payers segment held around 37% of the total market share in 2021. Payers, such as health plan sponsors, insurance companies, and other third-party payers, are among the main beneficiaries of the application of predictive analytics in the healthcare sector. Fraudulent claims may be tracked down and billions can be saved from the payers perspective.

Healthcare Predictive Analytics Market by End Users

North America dominated the market in 2021

In terms of regions, the market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America held around 48% of the total market share in 2021. Growth of the market is attributed to the presence of major market players in the region. Availability of skilled labor along with developed healthcare infrastructure in the region is the key factor boosting the market.

The market in Asia Pacific is anticipated to expand at a high CAGR during the forecast period. Healthcare predictive analytics have been rapidly adopted to lower the rising health-related expenditures and to improve the results of treatments given to patients as a result of a growth in the number of chronic illness cases and improved healthcare infrastructure. These factors are estimated to fuel the market in the region. 

Healthcare Predictive Analytics Market by Regions

Segments

The global healthcare predictive analytics market has been segmented on the basis of

Application

  • Clinical 
    • Clinical Outcome Analysis & Management
    • Patient Care Enhancement
    • Quality Benchmarking
  • Population Health 
    • Population Therapy Management
    • Patient Engagement
    • Population Therapy Management
    • Others
  • Financial 
    • Fraud Detection
    • Revenue Cycle Management
    • Others
  • Operations Management 
    • Outpatient Scheduling
    • Inpatient Scheduling
    • Workforce Planning & Scheduling
    • Demand Forecasting

End-user

  • Healthcare Payers
  • Healthcare Providers
  • Others

Regions

  • Asia Pacific
  • North America
  • Latin America
  • Europe
  • Middle East & Africa

Major Players

  • IBM
  • Cerner Corp.
  • Verisk Analytics, Inc.
  • McKesson Corp.
  • SAS
  • Oracle
  • Allscripts
  • Optum, Inc.
  • MedeAnalytics, Inc.

Competitive Landscape

Key players competing in the healthcare predictive analytics market include IBM; Cerner Corp.; Verisk Analytics, Inc.; McKesson Corp.; SAS; Oracle; Allscripts; Optum, Inc.; and MedeAnalytics, Inc. Some of these players are using several market strategies such as acquisitions, mergers, collaborations, partnerships, capacity expansion, and product launches to enhance their market shares, generate revenue, and raise their production line of the business in the coming years. For instance,

  • In July 2021, Enlitic signed a collaboration arrangement With NMC Healthcare. Enlitic's solutions will be implemented across GCC nations through this extensive relationship with private healthcare organizations.
  • In June 2021, Flatiron and Foundation Medicine, Inc. signed a collaboration agreement in order to combine its products with OncoEMR and provide customers with integrated genomic profiling.

Healthcare Predictive Analytics Market By Key Players

1. Executive Summary
2. Assumptions and Acronyms Used
3. Research Methodology
4. Healthcare Predictive Analytics Market Overview
  4.1. Introduction
     4.1.1. Market Taxonomy
     4.1.2. Market Definition
  4.2. Macro-Economic Factors
     4.2.1. Industry Outlook
  4.3. Healthcare Predictive Analytics Market Dynamics
     4.3.1. Market Drivers
     4.3.2. Market Restraints
     4.3.3. Opportunity
     4.3.4. Market Trends
  4.4. Healthcare Predictive Analytics Market - Supply Chain
  4.5. Global Healthcare Predictive Analytics Market Forecast
     4.5.1. Healthcare Predictive Analytics Market Size (US$ Mn) and Y-o-Y Growth
     4.5.2. Healthcare Predictive Analytics Market Size (000’ Units) and Y-o-Y Growth
     4.5.3. Healthcare Predictive Analytics Market Absolute $ Opportunity
5. Global Healthcare Predictive Analytics Market Analysis and Forecast by End Users
  5.1. Market Trends
  5.2. Introduction
     5.2.1. Basis Point Share (BPS) Analysis by End Users
     5.2.2. Y-o-Y Growth Projections by End Users
  5.3. Healthcare Predictive Analytics Market Size and Volume Forecast by End Users
     5.3.1. Healthcare Payers
     5.3.2. Healthcare Providers
     5.3.3. Others
  5.4. Absolute $ Opportunity Assessment by End Users
  5.5. Market Attractiveness/Growth Potential Analysis by End Users
6. Global Healthcare Predictive Analytics Market Analysis and Forecast by Region
  6.1. Market Trends
  6.2. Introduction
     6.2.1. Basis Point Share (BPS) Analysis by Region
     6.2.2. Y-o-Y Growth Projections by Region
  6.3. Healthcare Predictive Analytics Market Size and Volume Forecast by Region
     6.3.1. North America
     6.3.2. Latin America
     6.3.3. Europe
     6.3.4. Asia Pacific
     6.3.5. Middle East and Africa (MEA)
  6.4. Absolute $ Opportunity Assessment by Region
  6.5. Market Attractiveness/Growth Potential Analysis by Region
  6.6. Global Healthcare Predictive Analytics Demand Share Forecast, 2019-2026
7. North America Healthcare Predictive Analytics Market Analysis and Forecast
  7.1. Introduction
     7.1.1. Basis Point Share (BPS) Analysis by Country
     7.1.2. Y-o-Y Growth Projections by Country
  7.2. North America Healthcare Predictive Analytics Market Size and Volume Forecast by Country
     7.2.1. U.S.
     7.2.2. Canada
  7.3. Absolute $ Opportunity Assessment by Country
  7.4. North America Healthcare Predictive Analytics Market Size and Volume Forecast by End Users
     7.4.1. Healthcare Payers
     7.4.2. Healthcare Providers
     7.4.3. Others
  7.5. Basis Point Share (BPS) Analysis by End Users
  7.6. Y-o-Y Growth Projections by End Users
  7.7. Market Attractiveness/Growth Potential Analysis
     7.7.1. By Country
     7.7.2. By Product Type
     7.7.3. By Application
  7.8. North America Healthcare Predictive Analytics Demand Share Forecast, 2019-2026
8. Latin America Healthcare Predictive Analytics Market Analysis and Forecast
  8.1. Introduction
     8.1.1. Basis Point Share (BPS) Analysis by Country
     8.1.2. Y-o-Y Growth Projections by Country
     8.1.3. Latin America Average Pricing Analysis
  8.2. Latin America Healthcare Predictive Analytics Market Size and Volume Forecast by Country
      8.2.1. Brazil
      8.2.2. Mexico
      8.2.3. Rest of Latin America
   8.3. Absolute $ Opportunity Assessment by Country
  8.4. Latin America Healthcare Predictive Analytics Market Size and Volume Forecast by End Users
     8.4.1. Healthcare Payers
     8.4.2. Healthcare Providers
     8.4.3. Others
  8.5. Basis Point Share (BPS) Analysis by End Users
  8.6. Y-o-Y Growth Projections by End Users
  8.7. Market Attractiveness/Growth Potential Analysis
     8.7.1. By Country
     8.7.2. By Product Type
     8.7.3. By Application
  8.8. Latin America Healthcare Predictive Analytics Demand Share Forecast, 2019-2026
9. Europe Healthcare Predictive Analytics Market Analysis and Forecast
  9.1. Introduction
     9.1.1. Basis Point Share (BPS) Analysis by Country
     9.1.2. Y-o-Y Growth Projections by Country
     9.1.3. Europe Average Pricing Analysis
  9.2. Europe Healthcare Predictive Analytics Market Size and Volume Forecast by Country
     9.2.1. Germany
     9.2.2. France
     9.2.3. Italy
     9.2.4. U.K.
     9.2.5. Spain
     9.2.6. Russia
     9.2.7. Rest of Europe
  9.3. Absolute $ Opportunity Assessment by Country
  9.4. Europe Healthcare Predictive Analytics Market Size and Volume Forecast by End Users
     9.4.1. Healthcare Payers
     9.4.2. Healthcare Providers
     9.4.3. Others
  9.5. Basis Point Share (BPS) Analysis by End Users
  9.6. Y-o-Y Growth Projections by End Users
  9.7. Market Attractiveness/Growth Potential Analysis
     9.7.1. By Country
     9.7.2. By Product Type
     9.7.3. By Application
  9.8. Europe Healthcare Predictive Analytics Demand Share Forecast, 2019-2026
10. Asia Pacific Healthcare Predictive Analytics Market Analysis and Forecast
  10.1. Introduction
     10.1.1. Basis Point Share (BPS) Analysis by Country
     10.1.2. Y-o-Y Growth Projections by Country
     10.1.3. Asia Pacific Average Pricing Analysis
  10.2. Asia Pacific Healthcare Predictive Analytics Market Size and Volume Forecast by Country
     10.2.1. China
     10.2.2. Japan
     10.2.3. South Korea
     10.2.4. India
     10.2.5. Australia
     10.2.6. Rest of Asia Pacific (APAC)
  10.3. Absolute $ Opportunity Assessment by Country
  10.4. Asia Pacific Healthcare Predictive Analytics Market Size and Volume Forecast by End Users
     10.4.1. Healthcare Payers
     10.4.2. Healthcare Providers
     10.4.3. Others
  10.5. Basis Point Share (BPS) Analysis by End Users
  10.6. Y-o-Y Growth Projections by End Users
  10.7. Market Attractiveness/Growth Potential Analysis
     10.7.1. By Country
     10.7.2. By Product Type
     10.7.3. By Application
  10.8. Asia Pacific Healthcare Predictive Analytics Demand Share Forecast, 2019-2026
11. Middle East & Africa Healthcare Predictive Analytics Market Analysis and Forecast
  11.1. Introduction
     11.1.1. Basis Point Share (BPS) Analysis by Country
     11.1.2. Y-o-Y Growth Projections by Country
     11.1.3. Middle East & Africa Average Pricing Analysis
  11.2. Middle East & Africa Healthcare Predictive Analytics Market Size and Volume Forecast by Country
     11.2.1. Saudi Arabia
     11.2.2. South Africa
     11.2.3. UAE
     11.2.4. Rest of Middle East & Africa (MEA)
  11.3. Absolute $ Opportunity Assessment by Country
  11.4. Middle East & Africa Healthcare Predictive Analytics Market Size and Volume Forecast by End Users
     11.4.1. Healthcare Payers
     11.4.2. Healthcare Providers
     11.4.3. Others
  11.5. Basis Point Share (BPS) Analysis by End Users
  11.6. Y-o-Y Growth Projections by End Users
  11.7. Market Attractiveness/Growth Potential Analysis
     11.7.1. By Country
     11.7.2. By Product Type
     11.7.3. By Application
  11.8. Middle East & Africa Healthcare Predictive Analytics Demand Share Forecast, 2019-2026
12. Competition Landscape
  12.1. Global Healthcare Predictive Analytics Market: Market Share Analysis
  12.2. Healthcare Predictive Analytics Distributors and Customers
  12.3. Healthcare Predictive Analytics Market: Competitive Dashboard
  12.4. Company Profiles (Details: Overview, Financials, Developments, Strategy)
     12.4.1. IBM
     12.4.2. Cerner Corp.
     12.4.3. Verisk Analytics, Inc.
     12.4.4. McKesson Corp.
     12.4.5. SAS
     12.4.6. Oracle
     12.4.7. Allscripts
     12.4.8. Optum, Inc.
     12.4.9. MedeAnalytics, Inc.

The global healthcare predictive analytics market has been segmented on the basis of

Application

  • Clinical 
    • Clinical Outcome Analysis & Management
    • Patient Care Enhancement
    • Quality Benchmarking
  • Population Health 
    • Population Therapy Management
    • Patient Engagement
    • Population Therapy Management
    • Others
  • Financial 
    • Fraud Detection
    • Revenue Cycle Management
    • Others
  • Operations Management 
    • Outpatient Scheduling
    • Inpatient Scheduling
    • Workforce Planning & Scheduling
    • Demand Forecasting

End-user

  • Healthcare Payers
  • Healthcare Providers
  • Others

Regions

  • Asia Pacific
  • North America
  • Latin America
  • Europe
  • Middle East & Africa

Major Players

  • IBM
  • Cerner Corp.
  • Verisk Analytics, Inc.
  • McKesson Corp.
  • SAS
  • Oracle
  • Allscripts
  • Optum, Inc.
  • MedeAnalytics, Inc.

Key players competing in the healthcare predictive analytics market include IBM; Cerner Corp.; Verisk Analytics, Inc.; McKesson Corp.; SAS; Oracle; Allscripts; Optum, Inc.; and MedeAnalytics, Inc. Some of these players are using several market strategies such as acquisitions, mergers, collaborations, partnerships, capacity expansion, and product launches to enhance their market shares, generate revenue, and raise their production line of the business in the coming years. For instance,

  • In July 2021, Enlitic signed a collaboration arrangement With NMC Healthcare. Enlitic's solutions will be implemented across GCC nations through this extensive relationship with private healthcare organizations.
  • In June 2021, Flatiron and Foundation Medicine, Inc. signed a collaboration agreement in order to combine its products with OncoEMR and provide customers with integrated genomic profiling.

Healthcare Predictive Analytics Market By Key Players

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FAQ Section

Some frequently asked quetions about this report!

Application and end-user are the segments provided in the healthcare predictive analytics market report.

The healthcare predictive analytics market is anticipated to expand at a Compound Annual Growth Rate (CAGR) of 24% during the forecast period, 2022 – 2030.

The healthcare predictive analytics market is expected to reach USD 67 billion by 2030

The healthcare predictive analytics market size was around USD 10 billion in 2021.

Healthcare Payers, healthcare providers, and others are the end-users in the healthcare predictive analytics market.

IBM; Cerner Corp.; Verisk Analytics, Inc.; McKesson Corp.; SAS; Oracle; Allscripts; Optum, Inc.; and MedeAnalytics, Inc. are some of the leading players in the healthcare predictive analytics market.