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Asia Pacific Predictive Disease Analytics Market Size, Share & Trends Analysis Report By Deployment (On-premise, Cloud-based), By End-use (Healthcare Providers, Healthcare Payers), By Component, And Segment Forecasts, 2023-2030

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    Report

  • 90 Pages
  • June 2023
  • Region: Asia Pacific
  • Grand View Research
  • ID: 5846828
The Asia Pacific predictive disease analytics market size is expected to reach USD 2448.46 million by 2030, registering a CAGR of 24.0% from 2023 to 2030, according to this report. The growth is attributed to the rising pressure of increasing healthcare costs and reduced patient engagement and retention. Moreover, rising investment for technological development in this space by prominent players is driving the market growth. Furthermore, major players, such as IBM Corp., Verisk Analytics, Inc., McKesson Corp., SAS Institute, Inc., Cotiviti, Inc., Optum, Inc., MedeAnalytics, Inc., and Oracle Corp., are undertaking various strategies, such as partnerships, acquisitions, collaborations, product launches, and expansions.

For instance, in April 2022, SAS Institute, Inc. and Microsoft collaborated to build deep technology integrations to make advanced healthcare analytics accessible. This collaboration would enable the use of Fast Healthcare Interoperability Resources by integrating Azure Health Data Services into SAS Health. In December 2020, McKesson Corp. launched an oncology technology and insights business, Ontada. This helped the company advance cancer research and care. Moreover, government support in the form of funding and initiatives will drive the market over the forecast period. According to a study conducted by the Asian Development Bank in August 2022, the adoption of remote patient monitoring and predictive analytics can contribute an estimated USD 9.4 billion and USD 15.5 billion, respectively to the gross domestic product across Southeast Asia by 2030.

Asia Pacific Predictive Disease Analytics Market Report Highlights

  • The software & services segment accounted for the largest share of 70.8% in 2022 and is anticipated to register the fastest CAGR of 24.4% over the forecast period. The growing patient load on healthcare facilities and the rising prevalence of diseases are encouraging healthcare systems to adopt predictive analytics tools
  • The on-premise deployment segment dominated the market in 2022 with a revenue share of 65.2% owing to the benefits associated with the adoption of on-premise solutions, such as reduced costs, low power consumption, and low maintenance
  • The healthcare payersend-use segment dominated the market with a share of 40.8% in 2022 owing to the high adoption of predictive disease analytics tools to evaluate claims for insurance
  • India dominated the overall market in 2022 with a share of 23.6% owing to the presence of developing healthcare infrastructure and favorable government policies

Table of Contents

Chapter 1. Methodology and Scope
1.1. Market Segmentation & Scope
1.1.1. Component
1.1.2. Deployment
1.1.3. End-Use
1.1.4. Regional scope
1.1.5. Estimates and forecast timeline
1.2. Research Methodology
1.3. Information Procurement
1.3.1. Purchased database
1.3.2. GVR’s internal database
1.3.3. Secondary sources
1.3.4. Primary research
1.3.5. Details of primary research
1.3.5.1. Data for primary interviews in Asia Pacific
1.4. Information or Data Analysis
1.4.1. Data analysis models
1.5. Market Formulation & Validation
1.6. Model Details
1.6.1. Commodity flow analysis (Model 1)
1.6.1.1. Approach 1: Commodity flow approach
1.6.2. Volume price analysis (Model 2)
1.6.2.1. Approach 2: Volume price analysis
1.7. List of Secondary Sources
1.8. List of Primary Sources
1.9. Objectives
1.9.1. Objective 1
1.9.2. Objective 2
Chapter 2. Executive Summary
2.1. Market Outlook
2.2. Segment Outlook
2.2.1. Component outlook
2.2.2. Deployment outlook
2.2.3. End-Use outlook
2.2.4. Regional outlook
2.3. Competitive Insights
Chapter 3. Asia Pacific Predictive Disease 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. Penetration & Growth Prospect Mapping
3.3. Industry Value Chain Analysis
3.3.1. Reimbursement framework
3.4. Market Dynamics
3.4.1. Market driver analysis
3.4.1.1. Pressure to curb healthcare cost
3.4.1.2. Emergence of advacned analytics methods
3.4.1.3. Increase in number of initiatives and investments supporting predictive disease analytics services
3.4.1.4. Rising impact of internet and social media on healthcare
3.4.2. Market restraint analysis
3.4.2.1. Data privacy and theft issues
3.4.2.2. Lack of skilled prefessionals
3.4.3. Industry challenges
3.4.3.1. Preseance of large amount of healthcare data
3.4.3.2. Lack of healthcare infrastructure
3.5. Asia Pacific Predictive Disease Analytics Market Analysis Tools
3.5.1. Industry Analysis - Porter’s
3.5.1.1. Supplier power
3.5.1.2. Buyer power
3.5.1.3. Substitution threat
3.5.1.4. Threat of new entrant
3.5.1.5. Competitive rivalry
3.5.2. PESTEL Analysis
3.5.2.1. Political landscape
3.5.2.2. Technological landscape
3.5.2.3. Economic landscape
3.5.3. Major Deals & Strategic Alliances Analysis
3.5.4. Market Entry Strategies
Chapter 4. Asia Pacific Predictive Disease Analytics Market: Component Estimates & Trend Analysis
4.1. Definitions and Scope
4.1.1. Hardware
4.1.2. Software & Services
4.2. Type Market Share, 2018 & 2030
4.3. Segment Dashboard
4.4. Asia Pacific Predictive Disease Analytics Market by Component Outlook
4.5. Market Size & Forecasts and Trend Analyses, 2018 to 2030 for the following
4.5.1. Hardware
4.5.1.1. Hardware market estimates and forecast 2018 to 2030 (USD Million)
4.5.2. Software & Services
4.5.2.1. Software & services market estimates and forecast 2018 to 2030 (USD Million)
Chapter 5. Asia Pacific Predictive Disease Analytics Market: Deployment Estimates & Trend Analysis
5.1. Definitions and Scope
5.1.1. On-premise
5.1.2. Cloud-based
5.2. Application Market Share, 2018 & 2030
5.3. Segment Dashboard
5.4. Asia Pacific Predictive Disease Analytics Market by Deployment Outlook
5.5. Market Size & Forecasts and Trend Analyses, 2018 to 2030 for the following
5.5.1. On-premise
5.5.1.1. On-premise market estimates and forecast 2018 to 2030 (USD Million)
5.5.2. Cloud-based
5.5.2.1. Cloud-based market estimates and forecast 2018 to 2030 (USD Million)
Chapter 6. Asia Pacific Predictive Disease Analytics Market: End-Use Estimates & Trend Analysis
6.1. Definitions and Scope
6.1.1. Healthcare Payers
6.1.2. Healthcare Providers
6.1.3. Others End-Users
6.2. Sales Channel Market Share, 2018 & 2030
6.3. Segment Dashboard
6.4. Asia Pacific Predictive Disease Analytics Market by End-Use Outlook
6.5. Market Size & Forecasts and Trend Analyses, 2018 to 2030 for the following
6.5.1. Healthcare Payers
6.5.1.1. Hospitals & clinics market estimates and forecast 2018 to 2030 (USD Million)
6.5.2. Healthcare Providers
6.5.2.1. Outpatient facilities market estimates and forecast 2018 to 2030 (USD Million)
6.5.3. Others End-Users
6.5.3.1. Others end-users market estimates and forecast 2018 to 2030 (USD Million)
Chapter 7. Asia Pacific Predictive Disease Analytics Market: Regional Estimates & Trend Analysis
7.1. Regional Market Share Analysis, 2022 & 2030
7.2. Regional Market Dashboard
7.3. Regional Market Snapshot
7.4. Regional Market Share and Leading Players, 2022
7.5. SWOT Analysis, by Factor (Political & Legal, Economic and Technological)
7.6. Market Size, & Forecasts, Volume and Trend Analysis, 2018 to 2030
7.7. Asia Pacific
7.7.1. Japan
7.7.1.1. Market estimates and forecast, 2018 - 2030
7.7.2. China
7.7.2.1. Market estimates and forecast, 2018 - 2030
7.7.3. India
7.7.3.1. Market estimates and forecast, 2018 - 2030
7.7.4. Australia
7.7.4.1. Market estimates and forecast, 2018 - 2030
7.7.5. Singapore
7.7.5.1. Market estimates and forecast, 2018 - 2030
7.7.6. Malaysia
7.7.6.1. Market estimates and forecast, 2018 - 2030
7.7.7. Indonesia
7.7.7.1. Market estimates and forecast, 2018 - 2030
7.7.8. Vietnam
7.7.8.1. Market estimates and forecast, 2018 - 2030
Chapter 8. Competitive Landscape
8.1. Recent Developments & Impact Analysis, By Key Market Participants
8.2. Company/Competition Categorization
8.3. Vendor Landscape
8.3.1. List of key distributors and channel partners
8.3.2. Key customers
8.3.3. Key company market share analysis, 2022
8.3.4. IBM Corporation
8.3.4.1. Company overview
8.3.4.2. Financial performance
8.3.4.3. Product benchmarking
8.3.4.4. Strategic initiatives
8.3.5. Verisk Analytics, Inc.
8.3.5.1. Company overview
8.3.5.2. Financial performance
8.3.5.3. Product benchmarking
8.3.5.4. Strategic initiatives
8.3.6. McKesson Corporation
8.3.6.1. Company overview
8.3.6.2. Financial performance
8.3.6.3. Product benchmarking
8.3.6.4. Strategic initiatives
8.3.7. SAS Institute, Inc.
8.3.7.1. Company overview
8.3.7.2. Financial performance
8.3.7.3. Product benchmarking
8.3.7.4. Strategic initiatives
8.3.8. Cotiviti, Inc.
8.3.8.1. Company overview
8.3.8.2. Financial performance
8.3.8.3. Product benchmarking
8.3.8.4. Strategic initiatives
8.3.9. Optum, Inc.
8.3.9.1. Company overview
8.3.9.2. Financial performance
8.3.9.3. Product benchmarking
8.3.9.4. Strategic initiatives
8.3.10. MedeAnalytics, Inc.
8.3.10.1. Company overview
8.3.10.2. Financial performance
8.3.10.3. Product benchmarking
8.3.10.4. Strategic initiatives
8.3.11. Oracle Corporation
8.3.11.1. Company overview
8.3.11.2. Financial performance
8.3.11.3. Product benchmarking
8.3.11.4. Strategic initiatives
List of Tables
Table 1: List of Abbreviation
Table 2: Asia Pacific predictive disease analytics market, by Region, 2018-2030 (USD Million)
Table 3: Asia Pacific predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 4: Asia Pacific predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 5: Asia Pacific predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 6: Japan predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 7: Japan predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 8: Japan predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 9: China predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 10: China predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 11: China predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 12: India predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 13: India predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 14: India predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 15: Australia predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 16: Australia predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 17: Australia predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 18: Singapore predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 19: Singapore predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 20: Singapore predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 21: Malaysia predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 22: Malaysia predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 23: Malaysia predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 24: Indonesia predictive disease analytics market, by Region, 2018-2030 (USD Million)
Table 25: Indonesia predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 26: Indonesia predictive disease analytics market, by deployment, 2018-2030 (USD Million)
Table 27: Vietnam predictive disease analytics market, by end use, 2018-2030 (USD Million)
Table 28: Vietnam predictive disease analytics market, by component, 2018-2030 (USD Million)
Table 29: Vietnam predictive disease analytics market, by deployment, 2018-2030 (USD Million)
List of Figures
Fig. 1: Market research process
Fig. 2: Data triangulation techniques
Fig. 3: Primary research pattern
Fig. 4: Primary interviews in APAC
Fig. 5: Market research approaches
Fig. 6: Value-chain-based sizing & forecasting
Fig. 7: QFD modeling for market share assessment
Fig. 8: Market formulation & validation
Fig. 9: Asia Pacific predictive disease analytics market: market outlook
Fig. 10: Asia Pacific predictive disease analytics market competitive insights
Fig. 11: Parent market outlook
Fig. 12: Related/ancillary market outlook
Fig. 13: Penetration and growth prospect mapping
Fig. 14: Industry value chain analysis
Fig. 15: Asia Pacific predictive disease analytics market driver impact
Fig. 16: Asia Pacific predictive disease analytics market restraint impact
Fig. 17: Asia Pacific predictive disease analytics market strategic initiatives analysis
Fig. 18: Asia Pacific predictive disease analytics market: component movement analysis
Fig. 19: Asia Pacific predictive disease analytics market: component outlook and key takeaways
Fig. 20: Hardware market estimates and forecast, 2018-2030
Fig. 21: Software & services market estimates and forecast, 2018-2030
Fig. 22: Asia Pacific predictive disease analytics market: deployment movement analysis
Fig. 23: Asia Pacific predictive disease analytics market: deployment outlook and key takeaways
Fig. 24: On-premise market estimates and forecast, 2018-2030
Fig. 25: Cloud-based market estimates and forecast, 2018-2030
Fig. 26: Asia Pacific predictive disease analytics market: end use movement analysis
Fig. 27: Asia Pacific predictive disease analytics market: end use outlook and key takeaways
Fig. 28: Healthcare payers market estimates and forecast, 2018-2030
Fig. 29: Healthcare providers market estimates and forecast, 2018-2030
Fig. 30: Other end-users market estimates and forecast, 2018-2030
Fig. 31: Asia Pacific predictive disease analytics market: Regional movement analysis
Fig. 32: Asia Pacific predictive disease analytics market: Regional outlook and key takeaways
Fig. 33: Regional market shares and leading players
Fig. 34: Asia Pacific market share and leading players
Fig. 35: Asia Pacific SWOT
Fig. 36: Asia Pacific
Fig. 37: Asia Pacific market estimates and forecast, 2018-2030
Fig. 38: Japan
Fig. 39: Japan market estimates and forecast, 2018-2030
Fig. 40: China
Fig. 41: China market estimates and forecast, 2018-2030
Fig. 42: India
Fig. 43: India market estimates and forecast, 2018-2030
Fig. 44: Australia
Fig. 45: Australia market estimates and forecast, 2018-2030
Fig. 46: Singapore
Fig. 47: Singapore market estimates and forecast, 2018-2030
Fig. 48: Malaysia
Fig. 49: Malaysia market estimates and forecast, 2018-2030
Fig. 50: Indonesia
Fig. 51: Indonesia market estimates and forecast, 2018-2030
Fig. 52: Vietnam
Fig. 53: Vietnam market estimates and forecast, 2018-2030
Fig. 54: Participant categorization - Asia Pacific predictive disease analytics market
Fig. 55: Market share of key market players - Asia Pacific predictive disease analytics market

Companies Mentioned

  • IBM Corporation
  • Verisk Analytics, Inc.
  • McKesson Corporation
  • SAS Institute, Inc.
  • Cotiviti, Inc.
  • Optum, Inc.
  • MedeAnalytics, Inc.
  • Oracle Corporation

Methodology

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Table Information