README.md

metadata

task_categories:
  - text-classification
language:
  - en
tags:
  - medical
  - triage
dataset_info:
  features:
    - name: chosen
      dtype: string
    - name: chosen_level
      dtype: float64
    - name: chosen_comments
      dtype: string
    - name: rejected
      dtype: string
    - name: rejected_level
      dtype: float64
    - name: rejected_comments
      dtype: string
    - name: difficulty
      dtype: string
  splits:
    - name: test
      num_bytes: 4357226
      num_examples: 1502
  download_size: 454779
  dataset_size: 4357226
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*

PMR-Bench: Patient Message Ranking Benchmark

Project Page | Paper

PMR-Bench is a large-scale public dataset for studying medical triage in the context of asynchronous outpatient portal messages. The benchmark treats patient message triage as a pairwise inference problem, where models are tasked to choose which of two messages is more medically urgent.

The dataset contains 1,569 unique messages and over 2,000 high-quality test pairs for pairwise medical urgency assessment. It includes unstructured patient-written messages paired with real electronic health record (EHR) data to emulate real-world medical triage scenarios.

Task Description

The primary task is to perform a head-to-head re-sort of a physician's inbox by comparing pairs of messages. The dataset follows a "chosen" (more urgent) vs "rejected" (less urgent) format, making it suitable for training reward models (using Bradley-Terry objectives) or Supervised Fine-Tuning (SFT) for pairwise classification.

Data Fields

• chosen: The patient message or EHR context determined to be more medically urgent.
• chosen_level: Numerical urgency level for the chosen message.
• rejected: The patient message or EHR context determined to be less medically urgent.
• rejected_level: Numerical urgency level for the rejected message.
• difficulty: A difficulty rating for the comparison.
• chosen_comments/rejected_comments: Annotator feedback or reasoning.

Citation

@article{gatto2026medical,
  title={Medical Triage as Pairwise Ranking: A Benchmark for Urgency in Patient Portal Messages},
  author={Gatto, Joseph and Seegmiller, Parker and Burdick, Timothy and Resnik, Philip and Rahat, Roshnik and DeLozier, Sarah and Preum, Sarah M.},
  journal={arXiv preprint arXiv:2601.13178},
  year={2026}
}