Overview:

 

This AI-powered assistant helps healthcare support agents navigate the complex steps of processing prior authorizations (PAs) for specialty medications. It simulates real-world job support inside a fictional healthcare tech company—CareAccess Health.

 

Try the GPT Here

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The Problem

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Processing prior authorizations requires detailed, step-based workflows involving insurance requirements, documentation, and provider communication. New support agents are often overwhelmed and risk making mistakes that delay patient treatment.

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The Solution

 

The CareAccess Health GPT Assistant functions as a digital mentor, walking users through real-time PA scenarios using clear, job-aligned guidance. It:

• Provides step-by-step support based on medication and payer requirements

• Helps agents escalate appropriately (e.g., involving case managers)

• Simulates just-in-time job aid behavior without replacing formal training

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This solution showcases the power of AI-driven learning and support tools in real-world healthcare operations.

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Design Process

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I used OpenAI's CustomGPT builder to create a structured, rules-based assistant:

• Wrote detailed GPT logic using role, rules, and workflow prompts

• Simulated realistic job scenarios using fictional data and tone

• Tested scenarios using user-like questions such as:

  • “What documents are required for a Humira prior auth?”

  • “What do I do if the provider forgot to submit labs?”

• Tuned language to be clear, supportive, and accurate

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Impact

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This project demonstrates how CustomGPTs can accelerate onboarding and support for complex roles in healthcare. It shows how AI can be:

• A safe practice space

• A job aid

• A confidence booster

It's also an effective sample of performance support design using AI.

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Tools Used:

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• OpenAI CustomGPT Builder – for creating AI-powered learning and performance support tools

• ChatGPT (GPT-4o) – for prompt engineering, scenario design, and simulation testing​

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Try It

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Launch the CareAccess GPT

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This is an interactive training module in Articulate Storyline, integrating custom JavaScript with OpenAI’s GPT API to provide AI-generated feedback based on learner inputs. The module simulated real-world tasks, requiring users to extract key details from AI-generated call transcripts and enter responses, which were then analyzed by GPT to deliver curated, context-aware feedback. This use of AI-driven evaluation ensured more dynamic and adaptive learning, enhancing accuracy and engagement. The project demonstrated the strategic application of AI and coding in instructional design, creating a scalable and immersive training experience.​​​