DUBLIN: The "Artificial Intelligence in Private Healthcare Report" has been added to ResearchAndMarkets.com's offering.

This report offers the most comprehensive view yet on how AI can be integrated across every element of a healthcare business to realise commercial gains, deliver operational efficiencies, and drive excellence in clinical care.

Rather than theoretical benefits, we have spoken to leading experts already integrating AI into their businesses. Curzon Consulting have identified real-life use cases across the entire value chain of hospital operations from more than 60 hospitals and healthcare institutions, providing a true global view of the potential for AI - spanning 25 countries and every major continent. Going into greater detail, the report highlights AI use cases relevant to every function within a hospital organisation, including operations, commercial, and clinical areas.

As a trusted partner of the independent sector for almost four decades, we believe that this report will provide the insights needed to inform business case development, investment decisions and strategic prioritisation.

What's inside?

• An unparalleled international study on the use of AI within healthcare organisations
• More than 60 real-life examples from hospitals and healthcare providers
• Case studies taken from more than 25 countries, including the US, UK, China and India
• Clearly defined use-cases for AI across primary and support functions
• Detailed strategic recommendations that provide a road map for AI adoption
• Levers that drive success in strategic growth ambitions
• Identification of potential barriers and challenges of AI adoption
• Global AI Adoption Index
• Market Sizing for 2024 and 2034 forecast

Key Topics Covered:

1. Executive Summary

2. Introduction

2.1 Background and Objectives

2.2 Scope of Report

2.3 AI Definitions, Stages and Perceptions

2.3.1 Definitions of AI

2.3.2 Proposed Five Stages of Artificial Intelligence

2.3.3 Primary Insights: Understanding of AI from Healthcare Executives

3. AI in Healthcare: Current Landscape

3.1 Global Overview of AI Adoption in Healthcare

3.1.1 North America

3.1.2 Europe

3.1.3 Asia & Pacific

3.1.4 Middle East & Africa

3.1.5 South America

3.1.6 Stakeholders Perspectives on Global AI Adoption

3.1.7 Reflections on Global AI Adoption

3.2 Key Themes and Trends in AI Adoption from Leaders in the Private Acute Sector

3.2.1 Key Trends on AI Implementation

3.2.2 AI Adoption in Private Hospital Functions

4. AI Applications in Primary Activities

4.1 Marketing and Patient-Acquisition

4.1.1 AI-Driven Marketing Strategies in UK Private Hospitals

4.1.2 Global Case Studies of AI-Driven Marketing Strategies

4.2 Consultation

4.2.1 AI-Driven Consultation in UK Private Hospitals

4.2.2 Global Case Studies of AI-Driven Consultation Technologies

4.3 Diagnostics

4.3.1 AI-Driven Diagnostic Use Cases in the UK and Europe

4.3.2 Global Case Studies of AI in Diagnostics

4.3.3 Key Technology Companies in AI-Driven Diagnostics

4.3.4 Impact of AI on Accuracy and Efficiency in Diagnostics

4.4 Treatment

4.4.1 AI-Driven Treatment in UK Private Hospitals

4.4.2 Global Case Studies of AI-Driven Treatments

4.5 Discharge

4.6 Outcomes

4.7 Follow-up

4.7.1 AI-Driven Follow-Up Support in Europe and UK Private Hospitals

4.7.2 Current AI Technologies in Post-Operative Care

5. AI Applications in Support Activities

5.1 Infrastructure

5.1.1 AI-Driven Infrastructure Management in UK Private Hospitals

5.1.2 Global Case Studies of AI-Driven Infrastructure Management

5.2 Workforce Management

5.2.1 AI-Driven Workforce Management in UK Private Hospitals

5.2.2 Global Case Studies of AI-Driven Infrastructure Management

5.3 Information Technology

5.3.1 AI-Driven IT Management in UK Private Hospitals

5.4 Operations

5.4.1 AI-Driven Operations in Europe and UK Private Hospitals

5.4.2 Global Case Studies of AI-Driven Operations

5.5 Procurement

5.5.1 AI-Driven Procurement in UK Private Hospitals

5.5.2 Global Case Studies of AI-Driven Operations

6. AI Across the Value Chain: A Case Study in Orthopaedic Hip Replacements

7. Value Generation and Return on Investment

7.1 Measuring AI's Impact

7.2 Revenue Generation

7.3 Cost Savings and Efficiency Gains

8. Challenges and Barriers

8.1 Technical Challenges

8.1.1 Data Integration and Quality

8.1.2 System Integration and Interoperability

8.1.3 Relying on Third-Party Expertise

8.1.4 Scaling AI with Adequate Infrastructure

8.2 Ethical and Legal Considerations

8.2.1 Ensuring Accuracy and Reliability

8.2.2 Transparency and Patient Consent

8.2.3 Bias, Fairness, and Accountability

8.2.4 Regulatory Compliance and Data Privacy

8.2.5 Cybersecurity Risks

8.3 Integration and Adoption Barriers

8.3.1 Cultural Resistance and Workforce Integration

8.3.2 Workforce Impact and Job Evolution

8.4 Regulatory Landscape

8.4.1 Compliance with UK and EU Regulations

9. Future Outlook and Opportunities

9.1 Emerging Innovations and Applications

9.1.1. Service Redesign and Patient-Centred Care

9.1.2 Shift from Hospital-Based to Home-Based and Self-Managed Care

9.1.3 Precision Medicine and Personalised Care

9.1.4 Patient Acquisition and Management

9.1.5 Potential Transformation to Platform-Based Organisations

9.2 Strategic Growth: Levers for Achieving Success

9.2.1 Core Requirements for AI Success

9.2.2 Understanding the Value-Chain Wide Adoption Potential of any individual AI application

9.2.3 Collaboration for Innovation

9.2.4 Governance and Leadership

9.2.5 Workforce Champions

10. Recommendations and Conclusions

10.1 Strategic Recommendations

10.2 Curzon's Role in Business Case Development

10.3 Conclusion: Turning Vision into Action

Appendices

Appendix 1 Methodology & Assumptions

Appendix 2 Active AI Regulations by Country

Appendix 3 List of Hospital Groups and Academic Institutions

Appendix 4 References

For more information about this report visit https://www.researchandmarkets.com/r/2d3v6a

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Fonte: Business Wire