埃森哲：2018年数字医疗科技的5大趋势_32页_6mb

报告摘要

Digital Health Tech Vision 2018 Summary

Core Content

The Accenture Digital Health Technology Vision 2018 outlines key trends shaping the future of healthcare through the integration of intelligent technologies. These trends highlight the growing role of AI, Extended Reality (XR), and data integrity in transforming how care is delivered and experienced. The report emphasizes the importance of trust, transparency, and responsibility in leveraging these technologies to enhance patient outcomes and organizational efficiency.

Main Trends

1. Citizen AI

Definition: AI is becoming a core part of the healthcare workforce, influencing decisions and enhancing care delivery.
Impact: AI is used in diagnosing wounds, monitoring the elderly, and verifying insurance information.
Challenges:
- AI systems must be explainable and responsible to gain trust.
- There is a risk of bias in AI models if the training data is not diverse or representative.
Consumer Trust: 85% of health executives believe AI will directly impact every person’s daily life within three years.
Action Required: Organizations need to develop ethical standards and ensure AI systems are transparent and accountable.

2. Extended Reality (XR)

Definition: XR includes Virtual Reality (VR) and Augmented Reality (AR), creating immersive experiences that bridge the gap between the physical and digital worlds.
Benefits:
- XR helps close the distance between patients, providers, and information.
- It enables remote consultations, training, and surgical planning.
Use Cases:
- Patients can visualize their conditions using VR.
- Surgeons can use 3D mapping for precision during procedures.
- VR therapy is used to treat mental health conditions like PTSD.
Adoption: 79% of health executives believe it's important for their organizations to be a pioneer in XR solutions.

3. Data Veracity

Definition: Ensuring data is accurate, reliable, and trustworthy is crucial for AI and digital healthcare systems.
Risks:
- Adversarial AI (e.g., bot fraud, falsified data) is a growing threat.
- 24% of health executives say their organizations have been targeted by adversarial AI.
Data Integrity:
- 84% of providers and 68% of health plans agree that data-driven decisions introduce new risks.
- Only 14% of providers and 6% of health plans validate data sources extensively.
Solutions:
- Implement blockchain for data provenance and integrity.
- Use behavior-based authentication and risk engines to ensure data quality.

4. Frictionless Business

Definition: The use of microservices and blockchain to support seamless, scalable partnerships.
Microservices:
- Break applications into simple, modular services.
- Enable rapid integration with third-party systems.
Blockchain:
- Provides secure, transparent, and tamper-proof data sharing.
- Supports trustless collaboration among stakeholders.
Example: Walgreens uses microservices to share APIs with third-party developers, expanding its partnerships rapidly.

Key Insights

Trust is essential: 81% of health executives agree that organizations are not prepared to explain AI decisions if issues arise.
Consumer perception: 69% of consumers believe health plan sources are biased when researching treatments.
Adoption challenges: Many organizations are not keeping up with the pace of AI advancement.
XR's potential: 82% of health executives believe XR helps close the distance gap in delivering care.
Data security: 83% of physicians have experienced cyber attacks, highlighting the urgent need for data protection.

Consequences of Technology Integration

AI's role: AI is becoming a trusted advisor and collaborator in healthcare.
XR's impact: It enhances clinical precision, patient engagement, and workforce training.
Data integrity: Without reliable data, AI decisions and health outcomes can be compromised.