mlsanityData to 7 Oct 2026

Question Answering for Electronic Health Records: A Scoping Review of datasets and models

arXiv 2310.08759 ↗First posted 12 Oct 2023cs.LG cs.IRcited by 7

Not on the map. Why?

Abstract (arXiv)

Question Answering (QA) systems on patient-related data can assist both clinicians and patients. They can, for example, assist clinicians in decision-making and enable patients to have a better understanding of their medical history. Significant amounts of patient data are stored in Electronic Health Records (EHRs), making EHR QA an important research area. In EHR QA, the answer is obtained from the medical record of the patient. Because of the differences in data format and modality, this differs greatly from other medical QA tasks that employ medical websites or scientific papers to retrieve answers, making it critical to research EHR question answering. This study aimed to provide a methodological review of existing works on QA over EHRs. We searched for articles from January 1st, 2005 to September 30th, 2023 in four digital sources including Google Scholar, ACL Anthology, ACM Digital Library, and PubMed to collect relevant publications on EHR QA. 4111 papers were identified for our study, and after screening based on our inclusion criteria, we obtained a total of 47 papers for further study. Out of the 47 papers, 25 papers were about EHR QA datasets, and 37 papers were about EHR QA models. It was observed that QA on EHRs is relatively new and unexplored. Most of the works are fairly recent. Also, it was observed that emrQA is by far the most popular EHR QA dataset, both in terms of citations and usage in other papers. Furthermore, we identified the different models used in EHR QA along with the evaluation metrics used for these models.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 42 of its 122 references that are in the map. First posted on arXiv 12 Oct 2023.

Builds on

42 of 122 references.

References · 42

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2016SQuAD: 100,000+ Questions for Machine Comprehension of Textcited by 4,115
  3. 2016Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answeringcited by 2,498
  4. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,935
  5. 2019LXMERT: Learning Cross-Modality Encoder Representations from Transformerscited by 1,548
  6. 2017Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answeringcited by 1,310
  7. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  8. 2015Effective Approaches to Attention-based Neural Machine Translationcited by 1,024
  9. 2019ERNIE: Enhanced Language Representation with Informative Entitiescited by 525
  10. 2016Bidirectional Attention Flow for Machine Comprehensioncited by 278
  11. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  12. 2018emrQA: A Large Corpus for Question Answering on Electronic Medical Recordscited by 134
30 more
  1. 2017Bilateral Multi-Perspective Matching for Natural Language Sentencescited by 120
  2. 2018Coarse-to-Fine Decoding for Neural Semantic Parsingcited by 110
  3. 2023Do We Still Need Clinical Language Models?cited by 97
  4. 2019Entity-Relation Extraction as Multi-Turn Question Answeringcited by 96
  5. 2018TRANX: A Transition-based Neural Abstract Syntax Parser for Semantic Parsing and Code Generationcited by 88
  6. 2019Text-to-SQL Generation for Question Answering on Electronic Medical Recordscited by 76
  7. 2023MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Recordscited by 54
  8. 2023EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Recordscited by 42
  9. 2023A Comparative Study of Pretrained Language Models for Long Clinical Textcited by 35
  10. 2018CliCR: A Dataset of Clinical Case Reports for Machine Reading Comprehensioncited by 34
  11. 2018Medical Exam Question Answering with Large-scale Reading Comprehensioncited by 29
  12. 2020CliniQG4QA: Generating Diverse Questions for Domain Adaptation of Clinical Question Answeringcited by 26
  13. 2020Clinical Reading Comprehension: A Thorough Analysis of the emrQA Datasetcited by 23
  14. 2022KALA: Knowledge-Augmented Language Model Adaptationcited by 21
  15. 2020Knowledge Graph-based Question Answering with Electronic Health Recordscited by 19
  16. 2022DrugEHRQA: A Question Answering Dataset on Structured and Unstructured Electronic Health Records For Medicine Related Queriescited by 17
  17. 2022Learning to Ask Like a Physiciancited by 16
  18. 2022DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processingcited by 14
  19. 2021Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecturecited by 9
  20. 2023Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasetscited by 9
  21. 2023Evaluation of AI Chatbots for Patient-Specific EHR Questionscited by 9
  22. 2020Entity-Enriched Neural Models for Clinical Question Answeringcited by 8
  23. 2018Annotating Electronic Medical Records for Question Answeringcited by 6
  24. 2019Adapting and evaluating a deep learning language model for clinical why-question answeringcited by 5
  25. 2021Attention-based Aspect Reasoning for Knowledge Base Question Answering on Clinical Notescited by 4
  26. 2022Uncertainty-Aware Text-to-Program for Question Answering on Structured Electronic Health Recordscited by 4
  27. 2021Slot Filling for Biomedical Information Extractioncited by 3
  28. 2022Development of an Extractive Clinical Question Answering Dataset with Multi-Answer and Multi-Focus Questionscited by 3
  29. 2023Question-Answering System Extracts Information on Injection Drug Use from Clinical Notescited by 2
  30. 2022Toward a Neural Semantic Parsing System for EHR Question Answeringcited by 1

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 3; 2026: 4.

7 papers.

  1. 2025A Dataset for Addressing Patient's Information Needs related to Clinical Course of Hospitalizationcited by 13
  2. 2026EHRNavigator: A Multi-Agent System for Patient-Level Clinical Question Answering over Heterogeneous Electronic Health Recordscited by 1
  3. 2026HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answeringcited by 1
  4. 2025FirstAidQA: A Synthetic Dataset for First Aid and Emergency Response in Low-Connectivity Settingscited by 0
  5. 2025SCARE: A Benchmark for SQL Correction and Question Answerability Classification for Reliable EHR Question Answeringcited by 0
  6. 2026FHIRPath-QA: Executable Question Answering over FHIR Electronic Health Recordscited by 0
  7. 2026sebis at ArchEHR-QA 2026: How Much Can You Do Locally? Evaluating Grounded EHR QA on a Single Notebookcited by 0