How AI is Shaping Real-World Data in Healthcare
Objective
To evaluate how Artificial Intelligence is transforming the use of real-world data (RWD) in healthcare, including data collection, diagnostics, patient care, and decision-making.
Respondent Profile (n = 50)
Healthcare Professionals (Doctors/Nurses): 40%
Healthcare Data Analysts/Researchers: 30%
Students (Medical/Data Science): 20%
Others (Admin/Tech roles): 10%
Q1: Are you aware of AI applications in healthcare data?
- Yes: 88% (44)
- No: 12% (6)
Insight: Strong awareness of AI in healthcare.
Q2: Do you currently use AI tools in healthcare data analysis?
- Regularly: 46% (23)
- Occasionally: 34% (17)
- Never: 20% (10)
Insight: 80% have exposure, but regular usage is still growing.
Q3: Which AI applications are most used?
- Clinical decision support systems: 32%
- Predictive analytics (disease risk, outcomes): 28%
- Medical imaging analysis: 22%
- Chatbots/virtual assistants: 18%
Insight: AI is widely used in diagnosis and prediction.
Q4: How has AI impacted data processing and analysis speed?
- Significant improvement: 64%
- Moderate improvement: 28%
- No impact: 8%
Insight: Faster insights are a major advantage.
Q5: Has AI improved diagnostic accuracy?
- Yes: 60%
- Somewhat: 32%
- No: 8%
Insight: AI is increasingly trusted in clinical support.
Q6: What are the biggest challenges of using AI in healthcare data?
- Data privacy & security: 38%
- Bias in algorithms: 26%
- Lack of skilled professionals: 20%
- Regulatory issues: 16%
Insight: Ethical and compliance issues dominate.
Q7: Do you trust AI-driven healthcare insights?
- Fully: 26%
- Partially: 58%
- Not at all: 16%
Insight: AI is seen as assistive, not authoritative.
Q8: Which area benefits most from AI-driven healthcare data?
- Early disease detection: 34%
- Personalized treatment: 26%
- Hospital operations: 18%
- Drug discovery: 22%
Insight: Preventive care leads the impact.
Q9: Has AI improved patient outcomes in your experience?
- Yes: 62%
- Somewhat: 28%
- No: 10%
Insight: Positive but still evolving impact.
Q10: What is the future of AI in healthcare data?
- Highly transformative: 74%
- Moderately impactful: 20%
- Minimal impact: 6%
Insight: Strong optimism for AI-driven healthcare.
Key Outcomes / Conclusion
- AI is significantly improving speed, diagnostics, and predictive care
- Adoption is growing but still not fully mature
- Trust gap and ethical concerns remain key barriers
- AI will play a critical role in preventive and personalized healthcare
