Datasets:

TIM0927
/

MedPIC-Bench

license: cc-by-4.0
language:
  - en
pretty_name: MedPIC-Bench
task_categories:
  - question-answering
tags:
  - medical
  - medication-safety
  - multiple-choice
  - counterfactual-reasoning
size_categories:
  - n<1K
configs:
  - config_name: default
    data_files:
      - split: test
        path: questions.json

MedPIC-Bench

MedPIC-Bench is an English multiple-choice benchmark for evaluating whether large language models apply medication-safety rules to patient-specific clinical contexts. Questions may have one or more correct options.

Dataset overview

The dataset contains 467 questions:

Task family	Questions
Guideline following	284
Counterfactual reasoning	183
Total	467

Loading the dataset

from datasets import load_dataset

dataset = load_dataset("TIM0927/MedPIC-Bench", split="test")

Data fields

Field	Type	Description
`instance_id`	string	Unique question identifier.
`patient_vignette`	string	Patient-specific clinical context.
`question`	string	Medication-safety question.
`options`	object	Mapping from option letters to answer text.
`answer`	list[string]	Correct option letter or letters.
`taxonomy_clinical_department`	string	Clinical department category.
`taxonomy_clinical_system`	string	Organ-system category.
`taxonomy_drug_categories`	list[string]	Drug classes represented in the question.
`taxonomy_patient_info_type`	string	Patient-information or condition type.
`taxonomy_population_source`	string	Population group represented by the question.
`taxonomy_reasoning_operation`	string	Required reasoning operation.
`benchmark_task_family`	string	`guideline_following` or `counterfactual`.

Example:

{
  "instance_id": "SS-HF-HFREF-001",
  "patient_vignette": "A 71-year-old man has heart failure with reduced ejection fraction (LVEF 32%), currently asymptomatic on guideline-directed therapy review. No other significant past medical history; renal and hepatic function normal; not on other prescription medications; no known drug allergies.",
  "question": "For this patient, which of the following drugs should be avoided?",
  "options": {
    "A": "Verapamil",
    "B": "Dextromethorphan-quinidine",
    "C": "Diltiazem",
    "D": "Amlodipine",
    "E": "Cilostazol"
  },
  "answer": [
    "A",
    "B",
    "C",
    "E"
  ],
  "taxonomy_clinical_department": "cardiology",
  "taxonomy_clinical_system": "cardiovascular system",
  "taxonomy_drug_categories": [
    "calcium-channel blockers",
    "antiarrhythmics",
    "pde3 inhibitors/peripheral vascular drugs"
  ],
  "taxonomy_patient_info_type": "disease presence",
  "taxonomy_population_source": "older adults",
  "taxonomy_reasoning_operation": "static risk identification",
  "benchmark_task_family": "guideline_following"
}

Ethical statement and disclaimer

MedPIC-Bench is a research benchmark for evaluating model behavior. It is not a clinical decision-support system, medical device, prescribing reference, or source of medical advice. Benchmark questions and model outputs must not be used to make decisions about diagnosis, treatment, medication selection, or patient care.

The benchmark covers a limited set of medication-safety rules, clinical contexts, and patient populations. It is not an exhaustive representation of clinical practice. Performance on this dataset does not establish that a model is medically accurate, safe, unbiased, or suitable for deployment. Model outputs may contain clinically harmful errors even when aggregate benchmark scores are high.

Users are responsible for appropriate expert review, risk assessment, and compliance with applicable ethical, institutional, and legal requirements.

Acknowledgments

We gratefully acknowledge Yuting Long (龙宇婷) and Xinyao Ma (马馨瑶) for their valuable support in dataset validation. Their careful review helped improve the consistency and reliability of the benchmark.