| name | KSB-D06-K0100 |
| description | AI Error Prediction Modeling: Understanding of AI models for medication error prediction including near-miss pattern recognition, ... |
| version | 1.0.0 |
| domain | D06 |
| domain_name | Medication Errors & Quality |
| type | Knowledge |
| proficiency_level | L4 |
| bloom_level | analyze |
| triggers | ["explain ai error prediction modeling","what is ai error prediction modeling","analyze ai error prediction modeling"] |
| epa_mapping | EPA-01, EPA-07, EPA-09 |
| cpa_mapping | CPA-01, CPA-03 |
| regulatory_refs | |
KSB-D06-K0100: AI Error Prediction Modeling
Overview
Domain: D06 - Medication Errors & Quality
Type: Knowledge
Proficiency Level: L4 (Proficient - Independent practice)
Bloom Level: Analyze
Description
Understanding of AI models for medication error prediction including near-miss pattern recognition, high-risk situation identification, temporal risk variation modeling, and machine learning approaches for prevention resource optimization.
Context
- Major Section: AI in Medication Error Prevention
- Section: Predictive Error Analytics
EPA Mapping
- EPA-01:3001-3003
- EPA-07:3016-3017
- EPA-09:3020-3022
CPA Pathway
Regulatory References
Instructions
When this skill is activated, Claude should:
- Demonstrate L4 proficiency in ai error prediction modeling
- Apply analyze level cognitive skills to analyze the topic
- Reference relevant regulatory guidance (general PV standards)
- Connect to related EPAs: EPA-01, EPA-07, EPA-09
Key Competencies
- Understanding of AI models for medication error prediction including near-miss pattern recognition, high-risk situation identification, temporal risk variation modeling, and machine learning approaches for prevention resource optimization.
Assessment Criteria
- Can analyze core concepts independently
- Demonstrates understanding of regulatory context
- Applies knowledge appropriately to PV scenarios
Related Skills
- Other D06 skills in Predictive Error Analytics
- Cross-domain integrations per DAG architecture
Generated from PV KSB Framework v1.0 | 2025-12-31
