AI in Healthcare 2020 Leadership Survey Report: Survey at a Glance
Gaining insight and knowledge from data is the objective of adopting AI and machine learning to medicine. Think predicting risk, speeding clinical decisionmaking, making devices less user dependent and diagnosing and detecting disease earlier and better. Here is an overview of top priorities, barriers to adoption and the mindset of leadership. Healthcare organizations are focused, creating plans and paths to make AI happen.
Top 5 Priorities of AI
- Using EHR data to reliably predict risk
- Revolutionizing clinical decision making at the bedside
- Developing the next generation of radiology tools
- Bringing intelligence to medical devices and machines
- Utilizing AI to more effectively manage population health
Top 5 Barriers to AI Adoption
- Lack of financial resources
- Lack of clear strategy for AI within your organization
- Limited understanding of insights from AI
- Lack of leaders’ ownership of and commitment to AI
- Uncertain or low expectations for return on AI investments
AI in Healthcare 2020 Leadership Survey Report
- About the Survey
- Table of Contents
- Leveraging Intelligence to Enhance Care and Processes
- 7 Key Findings
- 01 C-level healthcare leaders are leading the charge to AI
- 02 AI has moved into the mainstream
- 03 Health systems are committed to investing in AI
- 04 Fortifying infrastructure is top of mind
- 05 Improving care is AI’s greatest benefit
- 06 Health systems are both buying and developing AI apps
- 07 Radiology is blazing the AI trail
- Drill Down by Facility Type
- The Doctor Says
- The Early Adopters
- Through the Eyes of the CIO
- From the C-Suite
- Meet the Survey Respondents