Prompt Engineering for Healthcare Training in Astana, Kazakhstan

The Prompt Engineering for Healthcare Training is a specialized program designed to teach healthcare professionals and health IT teams how to design safe, effective, and compliant prompts for using Generative AI in clinical, administrative, and operational healthcare settings.

The course focuses on accuracy, patient safety, privacy, and regulatory compliance, ensuring AI is used as a clinical support tool—not a clinical decision-maker.

Generative AI in Healthcare – Context & Risks

• Role of AI in healthcare settings
• Clinical vs administrative AI use cases
• Patient safety considerations
• Risks of hallucinations in healthcare

Healthcare Compliance & Privacy Basics

• PHI and sensitive health data
• HIPAA / GDPR / local healthcare regulations
• Consent and data handling rules
• Organizational AI usage policies

Prompt Engineering Fundamentals

• How LLMs interpret prompts
• Instruction clarity for clinical environments
• Role prompting for healthcare use
• Controlling tone and medical language

Designing Safe Clinical Support Prompts

• Prompts for summarization of clinical notes
• Discharge summary drafting
• Referral and handoff documentation
• Avoiding diagnosis and treatment recommendations

Structured Outputs for Healthcare Workflows

• Templates for clinical documentation
• JSON and form-based outputs
• Enforcing standardized formats
• Reducing transcription and formatting errors

Reducing Hallucinations & Medical Risk

• Grounding prompts with source text
• Asking for uncertainty flags
• Verification and cross-checking strategies
• Limiting scope of AI responses

Prompting for Administrative Healthcare Tasks

• Insurance and billing documentation support
• Scheduling and communication drafts
• Policy and procedure documentation
• Internal reporting and summaries

Prompting for Research & Evidence Summaries

• Literature summarization prompts
• Evidence table extraction
• Citation-aware prompting
• Avoiding fabricated references

Prompting for Patient Communication

• Drafting patient-friendly explanations
• Tone and readability control
• Multilingual support
• Avoiding medical advice and diagnosis

Prompt Testing & Validation in Healthcare

• Reviewing outputs for safety
• Clinical review workflows
• Prompt regression testing
• Continuous improvement

Governance & Approval Workflows

• Prompt approval processes
• Documentation of prompts
• Audit trails
• Change management

Security & Access Controls

• Role-based access to AI tools
• Limiting who can use clinical prompts
• Secure prompt libraries
• Preventing misuse

Ethical & Responsible AI in Healthcare

• Bias and fairness in healthcare AI
• Transparency to clinicians and patients
• Accountability and oversight
• Ethical decision support boundaries

Hands-on Exercises

Summary and Conclusion