mlsanityData to 7 Oct 2026

DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queries

arXiv 2205.01290 ↗First posted 3 May 2022cs.AIcited by 17

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Abstract (arXiv)

This paper develops the first question answering dataset (DrugEHRQA) containing question-answer pairs from both structured tables and unstructured notes from a publicly available Electronic Health Record (EHR). EHRs contain patient records, stored in structured tables and unstructured clinical notes. The information in structured and unstructured EHRs is not strictly disjoint: information may be duplicated, contradictory, or provide additional context between these sources. Our dataset has medication-related queries, containing over 70,000 question-answer pairs. To provide a baseline model and help analyze the dataset, we have used a simple model (MultimodalEHRQA) which uses the predictions of a modality selection network to choose between EHR tables and clinical notes to answer the questions. This is used to direct the questions to the table-based or text-based state-of-the-art QA model. In order to address the problem arising from complex, nested queries, this is the first time Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers (RAT-SQL) has been used to test the structure of query templates in EHR data. Our goal is to provide a benchmark dataset for multi-modal QA systems, and to open up new avenues of research in improving question answering over EHR structured data by using context from unstructured clinical data.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 16 of its 30 references that are in the map. First posted on arXiv 3 May 2022.

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16 of 30 references.

References · 16

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2019Publicly Available Clinical BERT Embeddingscited by 995
  4. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 420
  5. 2020HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Datacited by 263
  6. 2021MultiModalQA: Complex Question Answering over Text, Tables and Imagescited by 177
  7. 2018emrQA: A Large Corpus for Question Answering on Electronic Medical Recordscited by 134
  8. 2021Multi-modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Trainingcited by 96
  9. 2019Text-to-SQL Generation for Question Answering on Electronic Medical Recordscited by 76
  10. 2021MMBERT: Multimodal BERT Pretraining for Improved Medical VQAcited by 68
  11. 2020ManyModalQA: Modality Disambiguation and QA over Diverse Inputscited by 38
  12. 2020A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reportscited by 35
4 more
  1. 2018CliCR: A Dataset of Clinical Case Reports for Machine Reading Comprehensioncited by 34
  2. 2020CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answeringcited by 26
  3. 2020Entity-Enriched Neural Models for Clinical Question Answeringcited by 8
  4. 2021Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notescited by 4

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Citing papers per year: 2023: 4; 2024: 4; 2025: 4; 2026: 5.

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  1. 2023EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Imagescited by 53
  2. 2023EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Recordscited by 42
  3. 2024Interpretable LLM-based Table Question Answeringcited by 18
  4. 2023Enhancing Small Medical Learners with Privacy-preserving Contextual Promptingcited by 11
  5. 2025Experience Retrieval-Augmentation with Electronic Health Records Enables Accurate Discharge QAcited by 9
  6. 2024SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMscited by 8
  7. 2023Question Answering for Electronic Health Records: A Scoping Review of datasets and modelscited by 7
  8. 2024Retrieval Augmented Thought Process for Private Data Handling in Healthcarecited by 5
  9. 2024EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Recordscited by 5
  10. 2025Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRscited by 4
  11. 2025Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluationcited by 4
  12. 2026Patient-Similarity Cohort Reasoning in Clinical Text-to-SQLcited by 3
5 more
  1. 2025RephQA: Evaluating Readability of Large Language Models in Public Health Question Answeringcited by 2
  2. 2026CodeClinic: Evaluating Automation of Coding Skills for Clinical Reasoning Agentscited by 2
  3. 2026EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMscited by 2
  4. 2026EHRNavigator: A Multi-Agent System for Patient-Level Clinical Question Answering over Heterogeneous Electronic Health Recordscited by 1
  5. 2026HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answeringcited by 1