医療向けビッグデータ分析の世界市場の評価：分析別、用途別、エンドユーザー別、地域別、機会、予測（2016年～2030年）

世界の医療向けビッグデータ分析の市場規模は、2022年の306億米ドルから2030年に1,177億米ドルに達し、2023年～2030年の予測期間にCAGRで18.34%の成長が予測されています。近年、効果的な分析ツールを提供するソリューションに対する需要が増え続けています。公立病院と私立病院の両方で、意思決定の強化、競争優位性、企業業績の向上に向けてビッグデータの能力を活用する方法を模索しています。

当レポートでは、世界の医療向けビッグデータ分析市場について調査分析し、市場規模と予測、市場力学、主要企業の情勢と見通しなどを提供しています。

目次

第1章 調査手法

第2章 プロジェクトの範囲と定義

第3章 世界の医療向けビッグデータ分析市場に対するCOVID-19の影響

第4章 エグゼクティブサマリー

第5章 世界の医療向けビッグデータ分析の見通し（2016年～2030年）

• 市場規模と予測
  • 金額
• 分析別
  • 処方的
  • 予測的
  • 診断的
  • 記述的
• 用途別
  • 臨床分析
  • 財務分析
  • 運用分析
  • その他
• エンドユーザー別
  • 研究機関
  • 病院・診療所
  • 金融・保険代理店
  • その他
• 地域別
  • 北米
  • 欧州
  • 南米
  • アジア太平洋
  • 中東・アフリカ
• 市場シェア：企業別（2022年）

第6章 世界の医療向けビッグデータ分析の見通し：地域別（2016年～2030年）

• 北米
  • 分析別
  • 用途別
  • エンドユーザー別
  • 米国
  • エンドユーザー別
  • カナダ
  • メキシコ
• 欧州
  • ドイツ
  • フランス
  • イタリア
  • 英国
  • ロシア
  • オランダ
  • スペイン
  • トルコ
  • ポーランド
• 南米
  • ブラジル
  • アルゼンチン
• アジア太平洋
  • インド
  • 中国
  • 日本
  • オーストラリア
  • ベトナム
  • 韓国
  • インドネシア
  • フィリピン
• 中東・アフリカ
  • サウジアラビア
  • アラブ首長国連邦
  • 南アフリカ

第7章 市場マッピング（2022年）

• 製品別
• 用途別
• エンドユーザー別
• 地域別

第8章 マクロ環境と業界構造

• 需給の分析
• 輸出入の分析
• バリューチェーン分析
• PESTEL分析
• ポーターのファイブフォース分析

第9章 市場力学

• 成長促進要因
• 成長抑制要因（課題と抑制要因）

第10章 規制の枠組みとイノベーション

• 臨床試験
• 特許の情勢
• 政府の規制
• イノベーション/新興技術

第11章 主要企業情勢

• マーケットリーダー上位5社の競合マトリックス
• マーケットリーダー上位5社の市場の収益分析（2022年）
• 合併と買収/合弁事業（該当する場合）
• SWOT分析（市場参入企業5社向け）
• 特許分析（該当する場合）

第12章 価格分析

第13章 ケーススタディ

第14章 主要企業の見通し

• Veradigm Inc.
• GE Healthcare Technologies Inc.
• Microsoft Corporation
• Dell EMC
• Hewlett Packard Enterprise (HPE)
• Koninklijke Philips N.V.
• Cognizant
• International Business Machines Corporation (IBM)
• Cerner Corporation
• Cisco Systems Inc.
• McKesson Corporation
• Optum, Inc.

第15章 戦略的推奨事項

第16章 当社について・免責事項

List of Tables

• Table 1. Pricing Analysis of Products from Key Players
• Table 2. Competition Matrix of Top 5 Market Leaders
• Table 3. Mergers & Acquisitions/ Joint Ventures (If Applicable)
• Table 4. About Us - Regions and Countries Where We Have Executed Client Projects

List of Figures

• Figure 1. Global Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 2. Global Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 3. Global Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 4. Global Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 5. Global Big Data Analytics in Healthcare Market Share, By Region, in USD Billion, 2016-2030F
• Figure 6. North America Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 7. North America Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 8. North America Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 9. North America Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 10. North America Big Data Analytics in Healthcare Market Share, By Country, in USD Billion, 2016-2030F
• Figure 11. United States Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 12. United States Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 13. United States Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 14. United States Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 15. Canada Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 16. Canada Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 17. Canada Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 18. Canada Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 19. Mexico Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 20. Mexico Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 21. Mexico Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 22. Mexico Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 23. Europe Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 24. Europe Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 25. Europe Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 26. Europe Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 27. Europe Big Data Analytics in Healthcare Market Share, By Country, in USD Billion, 2016-2030F
• Figure 28. Germany Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 29. Germany Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 30. Germany Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 31. Germany Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 32. France Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 33. France Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 34. France Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 35. France Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 36. Italy Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 37. Italy Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 38. Italy Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 39. Italy Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 40. United Kingdom Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 41. United Kingdom Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 42. United Kingdom Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 43. United Kingdom Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 44. Russia Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 45. Russia Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 46. Russia Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 47. Russia Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 48. Netherlands Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 49. Netherlands Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 50. Netherlands Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 51. Netherlands Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 52. Spain Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 53. Spain Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 54. Spain Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 55. Spain Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 56. Turkey Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 57. Turkey Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 58. Turkey Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 59. Turkey Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 60. Poland Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 61. Poland Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 62. Poland Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 63. Poland Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 64. South America Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 65. South America Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 66. South America Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 67. South America Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 68. South America Big Data Analytics in Healthcare Market Share, By Country, in USD Billion, 2016-2030F
• Figure 69. Brazil Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 70. Brazil Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 71. Brazil Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 72. Brazil Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 73. Argentina Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 74. Argentina Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 75. Argentina Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 76. Argentina Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 77. Asia-Pacific Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 78. Asia-Pacific Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 79. Asia-Pacific Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 80. Asia-Pacific Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 81. Asia-Pacific Big Data Analytics in Healthcare Market Share, By Country, in USD Billion, 2016-2030F
• Figure 82. India Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 83. India Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 84. India Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 85. India Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 86. China Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 87. China Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 88. China Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 89. China Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 90. Japan Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 91. Japan Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 92. Japan Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 93. Japan Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 94. Australia Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 95. Australia Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 96. Australia Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 97. Australia Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 98. Vietnam Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 99. Vietnam Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 100. Vietnam Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 101. Vietnam Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 102. South Korea Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 103. South Korea Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 104. South Korea Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 105. South Korea Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 106. Indonesia Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 107. Indonesia Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 108. Indonesia Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 109. Philippines Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 110. Philippines Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 111. Philippines Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 112. Philippines Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 113. Middle East & Africa Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 114. Middle East & Africa Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 115. Middle East & Africa Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 116. Middle East & Africa Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 117. Middle East & Africa Big Data Analytics in Healthcare Market Share, By Country, in USD Billion, 2016-2030F
• Figure 118. Saudi Arabia Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 119. Saudi Arabia Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 120. Saudi Arabia Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 121. Saudi Arabia Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 122. UAE Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 123. UAE Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 124. UAE Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 125. UAE Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 126. South Africa Big Data Analytics in Healthcare Market, By Value, in USD Billion, 2016-2030F
• Figure 127. South Africa Big Data Analytics in Healthcare Market Share, By Analytics, in USD Billion, 2016-2030F
• Figure 128. South Africa Big Data Analytics in Healthcare Market Share, By Application, in USD Billion, 2016-2030F
• Figure 129. South Africa Big Data Analytics in Healthcare Market Share, By End-user, in USD Billion, 2016-2030F
• Figure 130. By Analytics Map-Market Size (USD Billion) & Growth Rate (%), 2022
• Figure 131. By Application Map-Market Size (USD Billion) & Growth Rate (%), 2022
• Figure 132. By End-user Map-Market Size (USD Billion) & Growth Rate (%), 2022
• Figure 133. By Region Map-Market Size (USD Billion) & Growth Rate (%), 2022

The Big Data Analytics in Healthcare Market was valued at 30.6 billion in 2022 and will reach USD 117.70 billion in 2030 growing at a CAGR of 18.34% for the forecast period between 2023 and 2030. In recent years, there has been a continuous increase in the demand for solutions offering effective analytical tools. Both public and private hospitals are seeking ways to leverage big data's capabilities for enhanced decision making, competitive advantage, and improving company performance.

Big data analytics and prediction models are being used by providers, lawmakers, and researchers to better allocate resources, predict surges, improve patient care and outcomes, and implement preventive measures. Roughly, 30% of the global data volume is created by the healthcare sector. Globally, there are around 350,000 health applications available, with over 90,000 of those being released in the same year. Hence, presence of enormous data enables the scope of utilizing big data analytics to improve healthcare decision making. Furthermore, Electronic Health Records (EHR) is the major application of big data in healthcare, where doc tors and nurses can access real-time, precise patient/resident data. Several other factors in the healthcare sector, such as increase in the use of data in healthcare, use of predictive analytics, increasing use of ML algorithms drive the demand for big data technology to improve overall efficiency and quality of care delivery.

Additionally, healthcare technology integrating use of sensors to collect data across numerous applications in upcoming years provides ample growth opportunity for the market. From earphones that can measure a person's core temperature, socks that can monitor a baby's heart rate, or a sports bra that can identify cancer. The development of comfortable, patient-friendly wearables will boost customer compliance and enhance data collection due to the convergence of consumer wearables with medical technology. The newest developments will do more than just collect data; they will also offer advice and administer care. Technolog y is rapidly personalising healthcare on a global scale, from a small ring that encourages deeper sleep to insoles that aids in walking.

Increasing Demand for Population Health Analytics

On a population-wide scale, employing big data analytics to improve healthcare can significantly save costs by identifying the people who are at higher risk for disease and arranging early treatments before the situation worsens. Big data is used in healthcare by aggregating data on a variety of parameters such as medical history, lab values, medications, comorbidities, and socioeconomic profile. Policymakers have started to use data for decision-making as more data becomes available. Data related to hospital readmission rates is used to establish policies targeted at reducing needless readmissions. Patient satisfaction data is now being utilised to impact policies ranging from provider reimbursement to hospital transparency. For instance, in April 2023, Amitech Solutions, a healthcare data, analytics and automation consulting company, released Healthcare Pricing Analytics Solution, a first-of-its-kind, on Snowflake's Marketplace. It is based on publicly available hospital and payer pricing data, but they go beyond the raw data to provide insights that support collaboration among all healthcare stakeholders to reduce costs of treatment.

Extensive Implementation in Cancer Research

According to World Health Organization, approximately 14 million people suffer from cancer every year. In the next 20 years, the number is predicted to increase by almost 70%. Oncologists are using data to deliver individualised treatments based on biopsy specimens, patient histories, and other relevant data. Numerous types of cancer-related data from patient case histories, international research, and surveys are being compiled by institutions all over the world. Researchers are utilising Natural Language Processing (NLP) systems to analyse through millions of health records in a population to determine patterns, trends, and patient similarity metrics. For instance, in October 2022, Tem pus, a pioneer in AI and precision medicine, has introduced Tempus+, a proprietary platform that uses real-world data to drive collaborative precision oncology research.

Government Initiative

Several local governments have introduced various initiatives for the upliftment of big data in healthcare industry. For instance, the Data Integration Partnership for Australia (DIPA) is a three-year, USD130.8 million project, aimed to maximize the use and value of the government's data assets. DIPA used data integration and analysis to provide fresh insights into crucial and challenging policy issues. Over 20 Commonwealth agencies worked together as a whole-of-government initiative to advance technical data infrastructure and data integration capabilities throughout the Australian Public Service. Important data assets, such as those in the social welfare, health, and education sectors, were upgraded, enabling policymakers to get insights that were previously not possible. Because DIPA only allowed access to regulated, de-identified, and confidential data for policy analysis and research purposes, individual privacy and the security of sensitive data is preserved. Likewise, governments across the globe are encouraging use of big data analytics to enhance healthcare infrastructure and promote well-structured healthcare landscape.

Predictive Analytics to Grow at a Faster Rate

With growing demand for population health analytics, further advancements in predictive analytics are expected to take place in the future. Healthcare organizations with the help of predictive analytics can identify potential health problems before they occur. Predictive analytics can anticipate future patient needs and identify population health patterns more quickly and precisely than ever before by utilizing data-driven insights. Additionally, predictive analytics allows healthcare practitioners to better forecast patient outcomes and allocate resources, accordingly, resulting in better treatment for people and cost savings for organizations. Personalizing therapies based on an individual's medical history or genetic profile, improving operational efficiency by forecasting resource requirements, and lowering hospital readmissions through early interventions are some of the other applications of predictive analytics in healthcare. For instance, in July 2022, Trilliant Health launched Site Selec tion, an analytics tool that provides dynamic comparisons at the service line level for M&A, and organic exp ansion plans for providers, payers, or life science firms.

Growing Application of Big Data Analytics in Pharmaceutical Research

The development of a new medicine is a highly costly endeavor as it requires extensive pharmaceutical research. As per Congressional Budget Office (CBO), the cost of medicine development can range from USD 1 billion to USD 2 billion, encompassing capital expenditures and investments in unsuccessful drug candidates. However, big data analytics offers a powerful solution by enabling intelligent searches across extensive databases comprising patents, academic articles, and clinical trial data. This technology empowers researchers to efficiently navigate these vast datasets, accelerating the process of generating new medications. In the pharmaceutical sector, big data analytics have already been leveraged to streamline online searches for immense datasets encompassing existing and pending patents, as well as publications from relevant academic journals. This capability enables researchers to access and analyze valuable information swiftly, enhancing their knowledge base and facilitating the discovery of novel therapeutic compounds.

Moreover, big data analytics plays a crucial role in the pharmaceutical industry's pre-commercialization phase. By harnessing these analytics, companies can identify the optimal patient demographics for clinical trials, ensuring a diverse and representative participant pool. Remote monitoring and analysis of previous clinical trial data can also be facilitated, allowing for comprehensive evaluation of drug safety and efficacy. This technology aids in the early detection and reporting of potential side effects, enabling pharmaceutical companies to address any concerns proactively.

Hence, big data analytics in healthcare present significant opportunities for the pharmaceutical industry to streamline drug development processes, improve research efficiency, and enhance patient safety. By harnessing the power of vast datasets and advanced analytical techniques, the industry can drive innovation, optimize decision-making, and ultimately bring safer and more effective medications to the market.

Impact of COVID-19

The utilization of big data analytics has emerged as a pivotal factor in healthcare decision-making, particularly in the context of the COVID-19 pandemic. The ongoing global health crisis has witnessed an exponential surge in the volume and variety of health data being collected and modified, thereby facilitating more extensive and sophisticated analytics. This has, in turn, led to a deeper comprehension of effective response strategies and treatment modalities for patients. Significantly, the COVID-19 pandemic has underscored the existing challenges associated with health data exchange between organizations and the notable lack of standardization in data collection and analysis methodologies. These obstacles have further highlighted the criticality of implementing robust data governance frameworks and standardized protocols to enhance data sharing and promote interoperability within the healthcare ecosystem. In the aftermath of the pandemic, the healthcare industry has recognized the operational advantages of leveraging big data analytics to drive informed decision-making processes. Industry players are increasingly forging strategic partnerships aimed at developing advanced data analytics platforms tailored specifically for the healthcare sector.

Key Players Landscape and Outlook

Companies operating in the global Big Data Analytics in Healthcare market are increasingly collaborating with healthcare bodies and popular hospitals to accelerate digital transformation of healthcare systems. Healthcare bodies and hospitals possess vast amounts of valuable patient data, including medical records, clinical trials, genomic data, and real-time patient monitoring data. By collaborating with these entities, companies can gain access to diverse and comprehensive datasets necessary for developing and refining their big data analytics solutions. Access to such data enables companies to train and validate their algorithms, improve predictive models, and generate meaningful insights for healthcare decision-making.

For instance, in 2022, Hartford HealthCare has entered into a strategic and enduring collaboration with Google Cloud to propel the health system's digital evolution, enhance data analysis capabilities, and elevate the delivery and accessibility of healthcare services. The health system will use Google Cloud's Healthcare Data Engine (HDE) and HDE accelerators, leveraging artificial intelligence (AI) and machine learning (ML), to make its healthcare data more accessible and actionable.

Table of Contents

1. Research Methodology

2. Project Scope & Definitions

3. Impact of Covid-19 on Global Big Data Analytics in Healthcare Market

4. Executive Summary

5. Global Big Data Analytics in Healthcare Outlook, 2016-2030F

• 5.1. Market Size & Forecast
  • 5.1.1. By Value
• 5.2. By Analytics
  • 5.2.1. Prescriptive
  • 5.2.2. Predictive
  • 5.2.3. Diagnostic
  • 5.2.4. Descriptive
• 5.3. By Application
  • 5.3.1. Clinical Analytics
  • 5.3.2. Financial Analytics
  • 5.3.3. Operational Analytics
  • 5.3.4. Others
• 5.4. By End-User
  • 5.4.1. Research Organisations
  • 5.4.2. Hospitals and Clinics
  • 5.4.3. Finance and Insurance Agencies
  • 5.4.4. Others
• 5.5. By Region
  • 5.5.1. North America
  • 5.5.2. Europe
  • 5.5.3. South America
  • 5.5.4. Asia-Pacific
  • 5.5.5. Middle East and Africa
• 5.6. By Company Market Share (%), 2022

6. Global Big Data Analytics in Healthcare Outlook, By Region, 2016-2030F

• 6.1. North America*
  • 6.1.1. By Analytics
    • 6.1.1.1. Prescriptive
    • 6.1.1.2. Predictive
    • 6.1.1.3. Diagnostic
    • 6.1.1.4. Descriptive
  • 6.1.2. By Application
    • 6.1.2.1. Clinical Analytics
    • 6.1.2.2. Financial Analytics
    • 6.1.2.3. Operational Analytics
    • 6.1.2.4. Others
  • 6.1.3. By End-User
    • 6.1.3.1. Research Organisations
    • 6.1.3.2. Hospitals and Clinics
    • 6.1.3.3. Finance and Insurance Agencies
    • 6.1.3.4. Others
  • 6.1.4. United States*
    • 6.1.4.1. By Analytics
    • 6.1.4.1.1. Prescriptive
    • 6.1.4.1.2. Predictive
    • 6.1.4.1.3. Diagnostic
    • 6.1.4.1.4. Descriptive
    • 6.1.4.2. By Application
    • 6.1.4.1.1. Clinical Analytics
    • 6.1.4.1.2. Financial Analytics
    • 6.1.4.1.3. Operational Analytics
    • 6.1.4.1.4. Others
  • 6.1.5. By End-User
    • 6.1.5.1. Research Organisations
    • 6.1.5.2. Hospitals and Clinics
    • 6.1.5.3. Finance and Insurance Agencies
    • 6.1.5.4. Others
  • 6.1.6. Canada
  • 6.1.7. Mexico

All segments will be provided for all regions and countries covered

• 6.2. Europe
  • 6.2.1 Germany
  • 6.2.2 France
  • 6.2.3 Italy
  • 6.2.4 United Kingdom
  • 6.2.5 Russia
  • 6.2.6 Netherlands
  • 6.2.7 Spain
  • 6.2.8 Turkey
  • 6.2.9 Poland
• 6.3. South America
  • 6.3.1. Brazil
  • 6.3.2. Argentina
• 6.4. Asia Pacific
  • 6.4.1. India
  • 6.4.2. China
  • 6.4.3. Japan
  • 6.4.4. Australia
  • 6.4.5. Vietnam
  • 6.4.6. South Korea
  • 6.4.7. Indonesia
  • 6.4.8. Philippines
• 6.5. Middle East & Africa
  • 6.5.1. Saudi Arabia
  • 6.5.2. UAE
  • 6.5.3. South Africa

7. Market Mapping, 2022

• 7.1. By Product
• 7.2. By Application
• 7.3. By End-user
• 7.4. By Region

8. Macro Environment and Industry Structure

• 8.1. Supply Demand Analysis
• 8.2. Import Export Analysis
• 8.3. Value Chain Analysis
• 8.4. PESTEL Analysis
  • 8.4.1. Political Factors
  • 8.4.2. Economic System
  • 8.4.3. Social Implications
  • 8.4.4. Technological Advancements
  • 8.4.5. Environmental Impacts
  • 8.4.6. Legal Compliances and Regulatory Policies (Statutory Bodies Included)
• 8.5. Porter's Five Forces Analysis
  • 8.5.1. Supplier Power
  • 8.5.2. Buyer Power
  • 8.5.3. Substitution Threat
  • 8.5.4. Threat from New Entrant
  • 8.5.5. Competitive Rivalry

9. Market Dynamics

• 9.1. Growth Drivers
• 9.2. Growth Inhibitors (Challenges and Restraints)

10. Regulatory Framework and Innovation

• 10.1. Clinical Trials
• 10.2. Patent Landscape
• 10.3. Government Regulations
• 10.4. Innovations/Emerging Technologies

11. Key Players Landscape

• 11.1. Competition Matrix of Top Five Market Leaders
• 11.2. Market Revenue Analysis of Top Five Market Leaders (in %, 2022)
• 11.3. Mergers and Acquisitions/Joint Ventures (If Applicable)
• 11.4. SWOT Analysis (For Five Market Players)
• 11.5. Patent Analysis (If Applicable)

12. Pricing Analysis

13. Case Studies

14. Key Players Outlook

• 14.1. Veradigm Inc.
  • 14.1.1. Company Details
  • 14.1.2. Key Management Personnel
  • 14.1.3. Products & Services
  • 14.1.4. Financials (As reported)
  • 14.1.5. Key Market Focus & Geographical Presence
  • 14.1.6. Recent Developments
• 14.2. GE Healthcare Technologies Inc.
• 14.3. Microsoft Corporation
• 14.4. Dell EMC
• 14.5. Hewlett Packard Enterprise (HPE)
• 14.6. Koninklijke Philips N.V.
• 14.7. Cognizant
• 14.8. International Business Machines Corporation (IBM)
• 14.9. Cerner Corporation
• 14.10. Cisco Systems Inc.
• 14.11. McKesson Corporation
• 14.12. Optum, Inc.

Companies mentioned above DO NOT hold any order as per market share and can be changed as per information available during research work

15. Strategic Recommendations

16. About Us & Disclaimer