healthsim-membersim

Generate synthetic health plan enrollment, eligibility, and claims data for testing.

1|Updated Jan 9, 2026

Search Tags:#generate #claims #enrollment #synthetic #adjudication #healthsim

Ready to run

npx skills add https://github.com/mark64oswald/healthsim-agent --skill healthsim-membersim

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: healthsim-membersim
Source: https://github.com/mark64oswald/healthsim-agent/tree/main/skills/membersim
Command: npx skills add https://github.com/mark64oswald/healthsim-agent --skill healthsim-membersim

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the generation of realistic synthetic health plan data for testing claims systems, enabling end-to-end scenario validation without using real PHI.

Core Features & Use Cases

Enrollment, eligibility, and enrollment verification: seed realistic member panels, coverage start/end dates, and eligibility results for testing 834/270/271 workflows.
Claims & adjudication workloads: generate professional and facility claims, implement standard adjudication paths, and model CARC/adjustment scenarios.
Cross-domain integration: align MemberSim outputs with PatientSim or RxMemberSim data to enable end-to-end population health testing.

Quick Start

Use the healthsim-membersim skill to generate a representative panel of synthetic members and a sample set of claims for test environment.

Frequently Asked Questions about healthsim-membersim

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate synthetic health data for testing claims adjudication systems?▼

You can generate synthetic health data by creating realistic member panels and claims workloads. This skill models professional claims, facility claims, and standard adjudication paths to test claims systems without using real PHI.

Can I generate synthetic enrollment data for 834 and 270/271 eligibility workflows?▼

Yes, you can generate synthetic enrollment data for 834 and 270/271 workflows. The skill seeds realistic member panels, coverage start and end dates, and eligibility results for testing these specific transactions.

What is the best way to test claims adjudication without using real PHI?▼

The best way to test claims adjudication without real PHI is using synthetic health plan data. This skill generates professional and facility claims while modeling CARC and adjustment scenarios for safe end-to-end testing.

Does this synthetic health data generator support cross-domain integration with other simulation tools?▼

Yes, the synthetic health data generator supports cross-domain integration. You can align its outputs with PatientSim or RxMemberSim data to enable comprehensive end-to-end population health testing across different domains.

Can I use this tool to model CARC adjustment scenarios for claims processing?▼

Yes, you can model CARC adjustment scenarios for claims processing. The skill implements standard adjudication paths and generates claims workloads that include these specific claim adjustment reason codes.

What synthetic data do I need to seed end-to-end testing scenarios for health plan claims?▼

To seed end-to-end testing scenarios, you need synthetic enrollment, eligibility, and claims adjudication data. This skill generates these linked datasets to validate health plan claims systems comprehensively.