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市場調査レポート

医療用不正検出の世界市場 - 2022年までの予測:記述的アナリティクス、予測的アナリティクス、処方的アナリティクス

Healthcare Fraud Detection Market by Type (Descriptive, Prescriptive), Application (Insurance Claim, Prepay, Post payment), Component (Service, Software), Delivery (On-premise, Cloud), End user - Global Forecast to 2022

発行 MarketsandMarkets 商品コード 599540
出版日 ページ情報 英文 162 Pages
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医療用不正検出の世界市場 - 2022年までの予測:記述的アナリティクス、予測的アナリティクス、処方的アナリティクス Healthcare Fraud Detection Market by Type (Descriptive, Prescriptive), Application (Insurance Claim, Prepay, Post payment), Component (Service, Software), Delivery (On-premise, Cloud), End user - Global Forecast to 2022
出版日: 2018年01月08日 ページ情報: 英文 162 Pages
概要

医療用不正検出市場は、2017年の6億3100万米ドルから、2022年までに22億4270万米ドルまで拡大すると見られています。市場は、2017年〜2022年のCAGR (複合年間成長率) で、28.9%の成長が予測されています。

当レポートでは、世界の医療用不正検出市場について調査分析し、市場概要、産業動向、セグメント別の市場分析、競合情勢、主要企業などについて、体系的な情報を提供しています。

第1章 イントロダクション

第2章 調査手法

第3章 エグゼクティブサマリー

第4章 重要考察

  • 医療用不正検出:市場概要
  • 医療用不正検出:製品別、サービス別
  • 医療用不正検出:タイプ別
  • 医療用不正検出:配信モデル別

第5章 市場概要

  • イントロダクション
  • 市場力学
    • 促進要因
    • 抑制要因
    • 機会
    • 課題

第6章 医療用不正検出の世界市場:コンポーネント別

  • イントロダクション
  • サービス
  • ソフトウェア

第7章 医療用不正検出の世界市場:配信モデル別

  • イントロダクション
  • オンプレミス
  • オンデマンド

第8章 医療用不正検出の世界市場:タイプ別

  • イントロダクション
  • 記述的アナリティクス
  • 予測的アナリティクス
  • 処方的アナリティクス

第9章 医療用不正検出の世界市場:用途別

  • イントロダクション
  • 保険金請求
  • 支払整合性
  • その他

第10章 医療用不正検出の世界市場:エンドユーザー別

  • イントロダクション
  • 民間保険支払人
  • 公的/政府機関
  • 第三社サービス提供会社
  • 雇用主

第11章 医療用不正検出の世界市場:地域別

  • イントロダクション
  • 北米
  • 欧州
  • アジア
  • その他

第12章 競合情勢

  • 概要
  • 市場企業ランキング
  • 競合シナリオ

第13章 企業プロファイル

  • IBM
  • OPTUM (UNITEDHEALTH GROUPの一部)
  • VERSCEND TECHNOLOGIES
  • MCKESSON
  • FAIR ISAAC (FICO)
  • SAS INSTITUTE
  • SCIO HEALTH ANALYTICS
  • WIPRO
  • CONDUENT
  • HCL TECHNOLOGIES
  • CGI GROUP
  • DXC TECHNOLOGY
  • NORTHROP GRUMMAN
  • LEXINEXIS (RELX GROUPの一部)
  • PONDERA SOLUTIONS

第14章 付録

目次
Product Code: HIT 5868

"Global healthcare fraud detection market projected to grow at a CAGR of 28.9%"

The healthcare fraud detection market is expected to reach USD 2,242.7 million by 2022 from USD 631.0 million in 2017, at a CAGR of 28.9%. Factors such as the large number of fraudulent activities in healthcare; increasing number of patients seeking health insurance; the prepayment review model; growing pressure of fraud, waste, and abuse on healthcare spending; and high returns on investments are driving the growth of the healthcare fraud detection market. On the other hand, market growth is likely to be negatively affected by the dearth of skilled personnel and reluctance to adopt healthcare fraud analytics in emerging countries, are expected to limit the growth of this market to a certain extent.

"The prescriptive analytics segment is expected to grow at the highest CAGR during the forecast period"

By type, the healthcare fraud detection market is segmented into descriptive, predictive, and prescriptive analytics. The prescriptive analytics segment is expected grow at a highest CAGR during the forecast period. The high growth of this segment is attributed to the ability of prescriptive analytics to ensure the synergistic integration of predictions and prescriptions.

"The services segment is expected to dominate the market during the forecast period"

Based on component, the healthcare fraud detection market is segmented into services, software, and hardware. The services segment accounted for the largest share of the healthcare fraud detection market in 2016. With the increasing need for business analytics services and the introduction of technologically advanced healthcare fraud detection software, which requires extensive training to use as well as regular upgrades, the services segment is expected to grow at the highest CAGR during the forecast period.

"North America to witness high growth during the forecast period"

In 2017, North America is expected to account for the largest share of the market followed by Europe. This regional segment is expected to register the highest CAGR during the forecast period. Factors such as increase in the number of people seeking health insurance, increasing cases of healthcare fraud, favorable government initiatives to combat healthcare fraud, rising pressure to reduce healthcare costs, technological advancements, and greater product and service availability in this region are expected to drive market growth in North America.

The primary interviews conducted for this report can be categorized as follows:

  • By Company Type: Tier 1 - 33%; Tier 2 - 45%; Tier 3 - 22%.
  • By Designation (Supply Side): C-level- 22%; D-level- 27%; others- 51%.
  • By Region: North America-62%; Europe-13%; Asia-21%; South America- 3%, and Middle East & Africa- 1%.

List of companies profiled in the report:

  • IBM (US)
  • Optum (US)
  • SAS (US)
  • McKesson (US)
  • SCIO (US)
  • Verscend (US)
  • Wipro (India)
  • Conduent (US)
  • HCL (India)
  • CGI (Canada)
  • DXC (US)
  • Northrop Grumman (US)
  • LexisNexis (US)
  • Pondera (US)

Research Coverage:

The report provides an overview of the healthcare fraud detection market. It aims at estimating the market size and future growth potential of this market across different segments such as type, application, component, delivery model, end user, and region. Furthermore, the report also includes an in-depth competitive analysis of the key players in the market along with their company profiles, recent developments, and key market strategies.

Key Benefits of Buying the Report:

The report will help the market leaders/new entrants in this market by providing them with the closest approximations of revenues for the overall healthcare fraud detection market and its subsegments. This report will help stakeholders to understand the competitive landscape better and gain insights to position their businesses and help companies make suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provide them with information regarding key market drivers and opportunities.

TABLE OF CONTENTS

1. INTRODUCTION

  • 1.1. OBJECTIVES OF THE STUDY
  • 1.2. MARKET DEFINITION
  • 1.3. MARKET SCOPE
    • 1.3.1. MARKETS COVERED
    • 1.3.2. YEARS CONSIDERED FOR THE STUDY
  • 1.4. CURRENCY
  • 1.5. LIMITATIONS
  • 1.6. STAKEHOLDERS

2. RESEARCH METHODOLOGY

  • 2.1. RESEARCH DATA
    • 2.1.1. SECONDARY DATA
      • 2.1.1.1. Secondary sources
    • 2.1.2. PRIMARY DATA
      • 2.1.2.1. Primary sources
      • 2.1.2.2. Key industry insights
  • 2.2. MARKET SIZE ESTIMATION
    • 2.2.1. BOTTOM-UP APPROACH
    • 2.2.2. TOP-DOWN APPROACH
  • 2.3. MARKET BREAKDOWN AND DATA TRIANGULATION
  • 2.4. ASSUMPTIONS FOR THE STUDY

3. EXECUTIVE SUMMARY

4. PREMIUM INSIGHTS

  • 4.1. HEALTHCARE FRAUD DETECTION: MARKET OVERVIEW
  • 4.2. HEALTHCARE FRAUD DETECTION, BY PRODUCT AND SERVICE
  • 4.3. HEALTHCARE FRAUD DETECTION, BY TYPE
  • 4.4. HEALTHCARE FRAUD DETECTION, BY DELIVERY MODEL

5. MARKET OVERVIEW

  • 5.1. INTRODUCTION
  • 5.2. MARKET DYNAMICS
    • 5.2.1. DRIVERS
      • 5.2.1.1. Large number of fraudulent activities in healthcare
      • 5.2.1.2. Increasing number of patients seeking health insurance
      • 5.2.1.3. Prepayment review model
      • 5.2.1.4. Growing pressure of fraud, waste, and abuse on healthcare spending
      • 5.2.1.5. High returns on investment
    • 5.2.2. RESTRAINT
      • 5.2.2.1. Reluctance to adopt healthcare fraud analytics in emerging countries
    • 5.2.3. OPPORTUNITIES
      • 5.2.3.1. Cloud-based analytics
      • 5.2.3.2. Emergence of social media and its impact on the healthcare industry
      • 5.2.3.3. AI in healthcare fraud detection
    • 5.2.4. CHALLENGES
      • 5.2.4.1. Dearth of skilled personnel
      • 5.2.4.2. Time-consuming deployment and need for frequent upgrades

6. HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT

  • 6.1. INTRODUCTION
  • 6.2. SERVICES
  • 6.3. SOFTWARE

7. FRAUD DETECTION MARKET, BY DELIVERY MODEL

  • 7.1. INTRODUCTION
  • 7.2. ON-PREMISE DELIVERY MODELS
  • 7.3. ON-DEMAND DELIVERY MODELS

8. HEALTHCARE FRAUD DETECTION MARKET, BY TYPE

  • 8.1. INTRODUCTION
  • 8.2. DESCRIPTIVE ANALYTICS
  • 8.3. PREDICTIVE ANALYTICS
  • 8.4. PRESCRIPTIVE ANALYTICS

9. HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION

  • 9.1. INTRODUCTION
  • 9.2. INSURANCE CLAIMS REVIEW
    • 9.2.1. POSTPAYMENT REVIEW
    • 9.2.2. PREPAYMENT REVIEW
  • 9.3. PAYMENT INTEGRITY
  • 9.4. OTHER APPLICATIONS

10. HEALTHCARE FRAUD DETECTION MARKET, BY END USER

  • 10.1. INTRODUCTION
  • 10.2. PRIVATE INSURANCE PAYERS
  • 10.3. PUBLIC/GOVERNMENT AGENCIES
  • 10.4. THIRD-PARTY SERVICE PROVIDERS
  • 10.5. EMPLOYERS

11. HEALTHCARE FRAUD DETECTION MARKET, BY REGION

  • 11.1. INTRODUCTION
  • 11.2. NORTH AMERICA
    • 11.2.1. US
    • 11.2.2. CANADA
  • 11.3. EUROPE
    • 11.3.1. GERMANY
    • 11.3.2. UK
    • 11.3.3. FRANCE
    • 11.3.4. REST OF EUROPE
  • 11.4. ASIA
  • 11.5. REST OF THE WORLD (ROW)

12. COMPETITIVE LANDSCAPE

  • 12.1. OVERVIEW
  • 12.2. MARKET PLAYER RANKING, 2016
  • 12.3. COMPETITIVE SCENARIO
    • 12.3.1. AGREEMENTS, PARTNERSHIPS, COLLABORATIONS, AND CONTRACTS
    • 12.3.2. EXPANSIONS
    • 12.3.3. ACQUISITIONS
    • 12.3.4. PRODUCT LAUNCHES

13. COMPANY PROFILES (Overview, Products Offered, Product Offering Scorecard, Business Strategy Scorecard, Recent Developments)*

  • 13.1. IBM
  • 13.2. OPTUM (A PART OF UNITEDHEALTH GROUP)
  • 13.3. VERSCEND TECHNOLOGIES
  • 13.4. MCKESSON
  • 13.5. FAIR ISAAC (FICO)
  • 13.6. SAS INSTITUTE
  • 13.7. SCIO HEALTH ANALYTICS
  • 13.8. WIPRO
  • 13.9. CONDUENT
  • 13.10. HCL TECHNOLOGIES
  • 13.11. CGI GROUP
  • 13.12. DXC TECHNOLOGY
  • 13.13. NORTHROP GRUMMAN
  • 13.14. LEXINEXIS (A PART OF RELX GROUP)
  • 13.15. PONDERA SOLUTIONS

*Details on MarketsandMarkets view, Overview, Products Offered, Product Offering Scorecard, Business Strategy Scorecard, and Recent Developments might not be captured in case of unlisted companies.

14. APPENDIX

  • 14.1. INSIGHTS FROM INDUSTRY EXPERTS
  • 14.2. DISCUSSION GUIDE
  • 14.3. KNOWLEDGE STORE: MARKETSANDMARKETS' SUBSCRIPTION PORTAL
  • 14.4. INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE
  • 14.5. AVAILABLE CUSTOMIZATIONS
  • 14.6. RELATED REPORTS
  • 14.7. AUTHOR DETAILS

LIST OF TABLES

  • TABLE 1: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 2: HEALTHCARE FRAUD DETECTION SERVICES MARKET, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 3: NORTH AMERICA: HEALTHCARE FRAUD DETECTION SERVICES MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 4: EUROPE: HEALTHCARE FRAUD DETECTION SERVICES MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 5: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 6: NORTH AMERICA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 7: EUROPE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 8: HEALTHCARE FRAUD DETECTION MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 9: HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 10: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 11: EUROPE: HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 12: HEALTHCARE FRAUD DETECTION MARKET FOR ON-DEMAND DELIVERY MODELS, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 13: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR ON-DEMAND DELIVERY MODELS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 14: EUROPE: HEALTHCARE FRAUD DETECTION MARKET FOR ON-DEMAND DELIVERY MODELS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 15: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 16: DESCRIPTIVE ANALYTICS MARKET, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 17: NORTH AMERICA: DESCRIPTIVE ANALYTICS MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 18: EUROPE: DESCRIPTIVE ANALYTICS MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 19: PREDICTIVE ANALYTICS MARKET, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 20: NORTH AMERICA: PREDICTIVE ANALYTICS MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 21: EUROPE: PREDICTIVE ANALYTICS MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 22: PRESCRIPTIVE ANALYTICS MARKET, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 23: NORTH AMERICA: PRESCRIPTIVE ANALYTICS MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 24: EUROPE: PRESCRIPTIVE ANALYTICS MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 25: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015-2022 (USD MILLION)
  • TABLE 26: HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 27: HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 28: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR INSURANCE CLAIMS REVIEW, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 29: HEALTHCARE FRAUD DETECTION MARKET FOR POSTPAYMENT REVIEW, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 30: HEALTHCARE FRAUD DETECTION MARKET FOR PREPAYMENT REVIEW, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 31: HEALTHCARE FRAUD DETECTION MARKET FOR PAYMENT INTEGRITY, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 32: HEALTHCARE FRAUD DETECTION MARKET FOR OTHER APPLICATIONS, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 33: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 34: HEALTHCARE FRAUD DETECTION MARKET FOR PRIVATE INSURANCE PAYERS, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 35: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR PRIVATE INSURANCE PAYERS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 36: HEALTHCARE FRAUD DETECTION MARKET FOR PUBLIC/GOVERNMENT AGENCIES, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 37: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR PUBLIC/GOVERNMENT AGENCIES, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 38: HEALTHCARE FRAUD DETECTION MARKET FOR THIRD-PARTY SERVICE PROVIDERS, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 39: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR THIRD-PARTY SERVICE PROVIDERS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 40: HEALTHCARE FRAUD DETECTION MARKET FOR EMPLOYERS, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 41: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET FOR EMPLOYERS, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 42: HEALTHCARE FRAUD DETECTION MARKET, BY REGION, 2015-2022 (USD MILLION)
  • TABLE 43: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 44: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 45: NORTH AMERICA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 46: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 47: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015-2022 (USD MILLION)
  • TABLE 48: NORTH AMERICA: INSURANCE CLAIMS REVIEW MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 49: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 50: US: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 51: US: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 52: US: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 53: US: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015-2022 (USD MILLION)
  • TABLE 54: US: INSURANCE CLAIMS REVIEW MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 55: US: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 56: CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 57: CANADA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 58: CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 59: CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015-2022 (USD MILLION)
  • TABLE 60: CANADA: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 61: EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY COUNTRY, 2015-2022 (USD MILLION)
  • TABLE 62: EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 63: EUROPE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 64: EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 65: EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015-2022 (USD MILLION)
  • TABLE 66: EUROPE: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 67: GERMANY: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 68: GERMANY: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 69: GERMANY: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 70: GERMANY: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 71: UK: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 72: UK: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 73: UK: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 74: UK: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 75: FRANCE: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 76: FRANCE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 77: FRANCE: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 78: FRANCE: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 79: ROE: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 80: ROE: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 81: ROE: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 82: ROE: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 83: ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 84: ASIA: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 85: ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 86: ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION, 2015-2022 (USD MILLION)
  • TABLE 87: ASIA: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 88: ROW: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT, 2015-2022 (USD MILLION)
  • TABLE 89: ROW: HEALTHCARE FRAUD DETECTION SOFTWARE MARKET, BY DELIVERY MODEL, 2015-2022 (USD MILLION)
  • TABLE 90: ROW: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE, 2015-2022 (USD MILLION)
  • TABLE 91: ROW: HEALTHCARE FRAUD DETECTION MARKET, BY END USER, 2015-2022 (USD MILLION)
  • TABLE 92: HEALTHCARE FRAUD DETECTION RANKING ANALYSIS, BY KEY PLAYER, 2016

LIST OF FIGURES

  • FIGURE 1: HEALTHCARE FRAUD DETECTION MARKET
  • FIGURE 2: RESEARCH DESIGN
  • FIGURE 3: BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY TYPE, DESIGNATION, AND REGION
  • FIGURE 4: DATA TRIANGULATION
  • FIGURE 5: DESCRIPTIVE ANALYTICS SEGMENT TO DOMINATE THE MARKET, BY TYPE, DURING THE FORECAST PERIOD
  • FIGURE 6: SERVICES SEGMENT TO DOMINATE THE MARKET IN 2017
  • FIGURE 7: ON-DEMAND DELIVERY MODELS TO GROW AT THE HIGHEST RATE DURING THE FORECAST PERIOD
  • FIGURE 8: PRIVATE INSURANCE PAYERS SEGMENT TO HOLD THE LARGEST MARKET SHARE IN 2017
  • FIGURE 9: NORTH AMERICA TO HOLD THE LARGEST SHARE OF THE GLOBAL MARKET DURING 2017 TO 2022
  • FIGURE 10: LARGE NUMBER OF FRAUDULENT ACTIVITIES IN HEALTHCARE TO DRIVE THE GROWTH OF THE MARKET
  • FIGURE 11: SERVICES SEGMENT TO GROW AT THE HIGHEST CAGR OVER THE FORECAST PERIOD (2017 -2022)
  • FIGURE 12: PRESCRIPTIVE ANALYTICS TO WITNESS HIGH GROWTH RATE FROM 2017 TO 2022
  • FIGURE 13: ON-PREMISE MODELS TO ACCOUNT FOR THE LARGEST SHARE OF THE HEALTHCARE FRAUD DETECTION IN 2017
  • FIGURE 14: HEALTHCARE FRAUD DETECTION MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES
  • FIGURE 15: HEALTHCARE SPENDING AS A PERCENTAGE OF THE GDP, BY COUNTRY, 2015
  • FIGURE 16: SERVICES SEGMENT TO DOMINATE THE HEALTHCARE FRAUD DETECTION MARKET IN 2017
  • FIGURE 17: ON-DEMAND SEGMENT TO REGISTER HIGHEST GROWTH RATE DURING THE FORECAST PERIOD (2017-2022)
  • FIGURE 18: NORTH AMERICA TO DOMINATE THE GLOBAL HEALTHCARE FRAUD DETECTION MARKET FOR ON-PREMISE DELIVERY MODELS (2017-2022)
  • FIGURE 19: PRESCRIPTIVE ANALYTICS TO WITNESS HIGHEST GROWTH DURING THE FORECAST PERIOD
  • FIGURE 20: NORTH AMERICA IS EXPECTED TO DOMINATE THE GLOBAL DESCRIPTIVE ANALYTICS MARKET (2017-2022)
  • FIGURE 21: INSURANCE CLAIMS REVIEW SEGMENT TO DOMINATE THE HEALTHCARE FRAUD DETECTION MARKET IN 2017
  • FIGURE 22: PAYERS TO DOMINATE THE HEALTHCARE FRAUD DETECTION MARKET DURING THE FORECAST PERIOD
  • FIGURE 23: NORTH AMERICA TO WITNESS THE HIGHEST GROWTH IN THE HEALTHCARE FRAUD DETECTION MARKET DURING THE FORECAST PERIOD
  • FIGURE 24: NORTH AMERICA: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT
  • FIGURE 25: EUROPE: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT
  • FIGURE 26: ASIA: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT
  • FIGURE 27: ROW: HEALTHCARE FRAUD DETECTION MARKET SNAPSHOT
  • FIGURE 28: MARKET EVOLUTION FRAMEWORK
  • FIGURE 29: IBM: COMPANY SNAPSHOT
  • FIGURE 30: MCKESSON: COMPANY SNAPSHOT
  • FIGURE 31: FICO: COMPANY SNAPSHOT
  • FIGURE 32: SAS INSTITUTE: COMPANY SNAPSHOT
  • FIGURE 33: WIPRO: COMPANY SNAPSHOT
  • FIGURE 34: CONDUENT: COMPANY SNAPSHOT
  • FIGURE 35: HCL: COMPANY SNAPSHOT
  • FIGURE 36: CGI GROUP: COMPANY SNAPSHOT
  • FIGURE 37: DXC TECHNOLOGY: COMPANY SNAPSHOT
  • FIGURE 38: NORTHROP GRUMMAN: COMPANY SNAPSHOT
  • FIGURE 39: RELX GROUP: COMPANY SNAPSHOT
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