Evidence-Based Health Decision Making with AI

Overview

Use AI to thoroughly analyze health decisions by examining benefits, risks, probabilities, and personalized factors. Get objective assessments that help you make informed choices about medical treatments, preventive care, or health interventions. 

Key Benefits: 

• Comprehensive analysis: Get detailed benefit-risk assessments with specific metrics and probability distributions
• Personalized insights: Factor in your personal health history and circumstances
• Objective perspective: Reduce confirmation bias with quantitative analysis and uncertainty estimates
• Multiple scenarios: Explore different timeframes, assumptions, and what-if scenarios
• Clear certainty levels: Understand how confident you can be in recommendations based on available evidence

Starter Prompt:

Here is a generalized template. The key is to be as specific as possible within the brackets to get the best results.

I need help making an evidence-based decision about [specific health intervention/treatment]. Here are the key details about my situation: [your age, health status, relevant history].

Could you help me analyze:

1. The benefits and risks with specific metrics
2. How these apply to someone with my profile
3. The quality of evidence and any uncertainties
4. A recommendation with a confidence level

Please be objective and include both sides of the decision, with actual numbers where possible.

 Usage Tips:

1. Start broad, then narrow: Begin with general analysis, then dive deeper into specific concerns or scenarios that matter to you
2. Ask for probability distributions: Request things like "What's the probability of different benefit levels?" to get a fuller picture
3. Challenge the analysis: Ask the AI to consider alternative perspectives or create prompts for other AI systems to check for bias
4. Include personal factors: Share relevant details about your health history, risk tolerance, and values to get personalized insights
5. Request multiple timeframes: Ask how the analysis changes when considering different time horizons (short-term vs. lifetime)
6. Ask for uncertainty quantification: Request confidence levels and explanations of what factors create uncertainty in the recommendations
7. Verify with sources: Ask the AI to explain the basis for its analysis and what evidence it's drawing from

Model used: Claude Sonnet 4 (via Claude.ai interface)

Note: This approach works best for decisions where scientific evidence exists. Always discuss significant health decisions with qualified healthcare providers, and use AI analysis as one input among many in your decision-making process.

A quick reminder: AI is a powerful tool. Learn how to use it safely and effectively by reading our Guide to Responsible AI Use.