Medical Claims Coverage Reasoning Dataset

Name: Medical Claims Coverage Reasoning Dataset
Creator: MOBIUSI INC
Published: 2026-10-19
License: https://creativecommons.org/licenses/by-nc-sa/4.0/

#coverage eligibility reasoning #policy exclusion analysis #evidence-based reasoning #medical insurance claims assessment #healthcare coverage verification #insurance policy compliance

5000
0.3GB
JSON
CATL
MOBIUSI INC

Updated:2026-10-19

AI Analysis & Value Prop

This dataset organizes medical insurance claim cases around plan provisions, billed services and costs, visit details, and exclusions, with labels indicating whether a specific expense meets coverage conditions. Each example calls for multi-hop question answering that connects policy language, case facts, and exclusions to produce a coverage outcome, its rationale, relevant provisions, and any unresolved facts. It supports reasoning SFT, training, and evaluation for medical claims workflows.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
policy_terms	string	Source text containing the applicable insurance plan provisions, coverage limits, and benefit conditions.
coverage_status	string	Determination of whether the claimed service is covered, partially covered, not covered, or cannot be determined from the available information.
exclusion_terms	string	Source text containing applicable exclusions, limitations, and exceptions that may affect coverage.
service_details	string	Source text describing the billed medical service, procedure, or item and its claimed cost.
unresolved_facts	array	Missing or ambiguous facts that materially limit the coverage determination; an empty array indicates that no such facts remain.
visit_information	string	Source text describing the relevant encounter, including dates, diagnoses, provider, and other claim circumstances.
coverage_reasoning	string	Explanation connecting relevant plan provisions and exclusions to the service and visit facts.
supporting_provisions	array	Specific policy clauses or exclusion provisions that support the coverage determination.

Compliance Statement

Authorization Type	Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use	Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization	No PII, no real company names, simulated scenarios follow industry standards
Compliance System	Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What does the dataset contain?: Each example is organized around a medical expense claim and includes policy terms, service and cost details, visit information, exclusions, and fields for the coverage outcome, reasoning, supporting provisions, and unresolved facts.

Which capabilities can it train or evaluate?: It supports training and evaluation of multi-hop question answering across policy terms and case facts, including coverage determination, evidence linking, policy provision retrieval, and explanation of conclusions.

Can it be used to make actual claim decisions?: The dataset can support model training, evaluation, and claims assistance workflows, but it should not replace formal review by an insurer, verification of complete documentation, or professional judgment. Actual coverage decisions must be confirmed against the applicable policy and case details.

How can I obtain the dataset and confirm usage rights?: Check the dataset product page or the platform where it is offered for available versions, delivery options, and licensing terms. Access conditions and permitted uses are governed by the relevant listing or license agreement.

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Cite this Work

@dataset{Mobiusi2026,
  title={Medical Claims Coverage Reasoning Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/ebf2742801354bd2ef1bd6f3b2dcc491},
  urldate={2026-10-19},
  keywords={medical claims dataset,insurance coverage reasoning,medical claims question answering,insurance policy QA,claims reasoning training data,multi-hop QA dataset,claims automation,medical insurance SFT},
  version={1.0}
}

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