The report includes:
- Impact analysis of artificial intelligence (AI) on the global electronic health records (EHR) market
- Case studies for successful integration of AI and machine learning in data extraction, clinical decision support, workflow automation and patient data management
- Highlights of AI adoption trends across major geographical regions, as well as disruptions caused by AI across key healthcare IT, hospitals and digital health industry verticals
- AI’s role in interoperability, predictive analytics, population health management and operational efficiency
- Review of AI impact on the various stages of the global electronic health records value chain and supply chain analysis
- Competitive landscape featuring key strategic initiatives, market spendings and an investment outlook
Table of Contents
Chapter 1 Key Use Cases for AI Implementation- Overview
- Key Use Cases/Case Studies
- Use Case 1: AI-Based Automation of Clinical Documentation and Medical Coding
- Use Case 2: AI-Enabled Predictive Analytics for Population Health Management
- Use Case 3: AI for EHR Data Interoperability and Integration
- Overview
- Adoption Trends by Region
- Adoption Trends in North America
- Adoption Trends in Europe
- Adoption Trends in Asia-Pacific
- Adoption Trends in the Rest of the World
- Overview
- Impact of AI on Key Industry Verticals
- Key Areas of AI Application
- Impact of AI on Various Stages of the Value Chain
- Overview
- Market Spending and Forecasting Analysis
- Key Spending/VC Funding in Electronic Health Records Systems
- Abbreviations Used in the Report
Table 1: Major Companies Operating in the Electronic Health Records Market in North America
Table 2: VC Investment in Electronic Health Records
Table 3: Abbreviations Used in This Report
List of Figures
Figure 1: Value Chain for the Electronic Health Records Market

