毕马威-2020人工智能在医疗保健行业的成就与挑战_8页_895kb

报告摘要

Summary of the "Living in an AI World 2020 Report: Healthcare Insiders"

Core Content

The KPMG Living in an AI World 2020 report focuses on the adoption and challenges of artificial intelligence (AI) in the healthcare industry, based on a survey of 751 U.S. business decision-makers with moderate AI knowledge. The report highlights both the current achievements and ongoing challenges in implementing AI within healthcare organizations.

Main Findings

AI Adoption in Healthcare:
- Just over half (53%) of healthcare respondents believe the industry is ahead of most others in AI adoption.
- However, 37% of healthcare executives feel the implementation pace is too slow, citing factors such as training, cost, and privacy as barriers.
- AI is already creating efficiencies (89%) and increasing patient access to care (91%).
Impact of AI:
- Diagnostics is seen as a key area for AI impact, with 68% of respondents confident in its eventual effectiveness, and 47% expecting significant impact within two years.
- Process automation is anticipated, with 40% expecting robotic handling of x-rays and CT scans.
- AI is expected to enhance electronic health records (EHR) and biometric applications, with 41% and 48% of respondents respectively anticipating these benefits.
- Machine learning is considered a key enabler for AI in healthcare, with 47% of respondents recognizing its importance.
Challenges of AI Adoption:
- Talent Shortage: Only 47% of healthcare insiders report that their organizations offer AI training courses, which is lower than in other industries.
- Employee Support: Only 67% of healthcare insiders believe their employees support AI adoption, the lowest among all five industries surveyed.
- Cost Concerns: 54% of executives believe AI has increased healthcare costs rather than decreased them, due to the need for significant capital investment.
- Privacy and Security: 75% of respondents express concern that AI could threaten the security and privacy of patient data, although 86% say their organizations are taking steps to protect patient privacy.

Key Areas for AI Implementation

Clinical and Patient-Facing Applications:
- AI is increasingly being used in clinical settings to assist with diagnoses, treatment, and patient engagement.
- Unstructured data analysis is seen as a valuable tool for solving complex healthcare problems.
Operational Efficiency:
- AI is expected to enhance records management, process automation, and data-driven decision-making.

Recommendations for Healthcare Companies

Invest in Training:
- Healthcare organizations need to develop AI-ready workforces through comprehensive training programs and talent acquisition strategies.
Focus on ROI:
- Decision-makers should identify the most impactful areas for AI investment to maximize returns and improve patient outcomes.
Prioritize Data Security:
- Given the sensitivity of patient data, healthcare companies must ensure robust privacy and security measures are in place when deploying AI technologies.

Conclusion

The healthcare industry is at a pivotal stage in AI adoption, with a growing recognition of its potential to transform patient care and operational efficiencies. Despite the challenges of training, cost, and privacy, the majority of healthcare insiders remain optimistic about AI's future impact. The report emphasizes the need for a strategic approach to AI implementation, focusing on employee readiness, cost-effectiveness, and data protection to fully harness its benefits.

Additional Resources

For further insights on AI, KPMG provides additional thought leadership papers, including:

Contact Information

Traci Gusher
Principal, Innovation and Enterprise Solutions
U.S. Lead, Artificial Intelligence, KPMG
Email: tgusher@kpmg.com
Melissa Edwards
Managing Director, Digital Enablement
KPMG
Email: melissaedwards@kpmg.com
Website: kpmg.com/us