mlsanityData to 7 Oct 2026

EHR-RAG: Bridging Long-Horizon Structured Electronic Health Records and Large Language Models via Enhanced Retrieval-Augmented Generation

arXiv 2601.21340 ↗First posted 29 Jan 2026cs.AIcited by 6

On the map: Retrieval-augmented generation → Medical and biomedical RAG

Abstract (arXiv)

Electronic Health Records (EHRs) provide rich longitudinal clinical evidence that is central to medical decision-making, motivating the use of retrieval-augmented generation (RAG) to ground large language model (LLM) predictions. However, long-horizon EHRs often exceed LLM context limits, and existing approaches commonly rely on truncation or vanilla retrieval strategies that discard clinically relevant events and temporal dependencies. To address these challenges, we propose EHR-RAG, a retrieval-augmented framework designed for accurate interpretation of long-horizon structured EHR data. EHR-RAG introduces three components tailored to longitudinal clinical prediction tasks: Event- and Time-Aware Hybrid EHR Retrieval to preserve clinical structure and temporal dynamics, Adaptive Iterative Retrieval to progressively refine queries in order to expand broad evidence coverage, and Dual-Path Evidence Retrieval and Reasoning to jointly retrieves and reasons over both factual and counterfactual evidence. Experiments across four long-horizon EHR prediction tasks show that EHR-RAG consistently outperforms the strongest LLM-based baselines, achieving an average Macro-F1 improvement of 10.76%. Overall, our work highlights the potential of retrieval-augmented LLMs to advance clinical prediction on structured EHR data in practice.

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Placed in Medical and biomedical RAG, one of 15 directions in Retrieval-augmented generation. Builds on 35 of its 61 references that are in the map. First posted on arXiv 29 Jan 2026.

Builds on

35 of 61 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025Rethinking Retrieval-Augmented Generation for Medicine: A Large-Scale, Systematic Expert Evaluation and Practical Insights10 Nov
  2. 2024EMERGE: Enhancing Multimodal Electronic Health Records Predictive Modeling with Retrieval-Augmented Generation27 May

Other references · 33

  1. 2023GPT-4 Technical Reportcited by 18,132
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
  4. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  5. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  6. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  7. 2023Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflectioncited by 1,800
  8. 2016RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanismcited by 344
  9. 2022GatorTron: A Large Clinical Language Model to Unlock Patient Information from Unstructured Electronic Health Recordscited by 238
  10. 2019Do NLP Models Know Numbers? Probing Numeracy in Embeddingscited by 157
  11. 2023EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Modelscited by 101
  12. 2020Language Models Are An Effective Patient Representation Learning Technique For Electronic Health Record Datacited by 85
21 more
  1. 2018GAMENet: Graph Augmented MEmory Networks for Recommending Medication Combinationcited by 79
  2. 2024EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Recordscited by 75
  3. 2020Do Language Embeddings Capture Scales?cited by 63
  4. 2025DeepRetrieval: Hacking Real Search Engines and Retrievers with Large Language Models via Reinforcement Learningcited by 62
  5. 2023GraphCare: Enhancing Healthcare Predictions with Personalized Knowledge Graphscited by 57
  6. 2024Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrievalcited by 45
  7. 2024ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?cited by 31
  8. 2023Biomedical knowledge graph-optimized prompt generation for large language modelscited by 30
  9. 2025Large Language Models are Powerful Electronic Health Record Encoderscited by 25
  10. 2024Prompting Large Language Models for Zero-Shot Clinical Prediction with Structured Longitudinal Electronic Health Record Datacited by 22
  11. 2024REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Modelscited by 21
  12. 2025MIRA: Medical Time Series Foundation Model for Real-World Health Datacited by 21
  13. 2025EHR-R1: A Reasoning-Enhanced Foundational Language Model for Electronic Health Record Analysiscited by 17
  14. 2025RAS: Retrieval-And-Structuring for Knowledge-Intensive LLM Generationcited by 16
  15. 2025Training LLMs for EHR-Based Reasoning Tasks via Reinforcement Learningcited by 14
  16. 2024LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instructioncited by 11
  17. 2025Large Language Models with Temporal Reasoning for Longitudinal Clinical Summarization and Predictioncited by 11
  18. 2025Investigating the Robustness of Retrieval-Augmented Generation at the Query Levelcited by 10
  19. 2025Revisiting the MIMIC-IV Benchmark: Experiments Using Language Models for Electronic Health Recordscited by 5
  20. 2024AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontologies-enhanced Large Language Modelscited by 3
  21. 2025MuISQA: Multi-Intent Retrieval-Augmented Generation for Scientific Question Answeringcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 6.

6 papers.

  1. 2026MedGuideX: Internalizing Decision Logic from Executable Guidelines into Large Language Models for Clinical Reasoningcited by 3
  2. 2026Discriminative Representation Learning for Clinical Predictioncited by 2
  3. 2026ClinicalBench: Stress-Testing Assertion-Aware Retrieval for Cross-Admission Clinical QA on MIMIC-IVcited by 2
  4. 2026GuideSkill: Evolving Executable LLM Agent Skills for Guideline-Grounded Clinical Reasoningcited by 1
  5. 2026EviGen: Predictive Evidence Scaffolding for Verifiable Clinical Rationale Generationcited by 0
  6. 2026MedRouter: Demystifying Knowledge Differences Across Medical LLMs for Routing-Based Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026EHR-RAGp: Retrieval-Augmented Prototype-Guided Foundation Model for Electronic Health Records
  2. 2025Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
  3. 2025EHRStruct: A Comprehensive Benchmark Framework for Evaluating Large Language Models on Structured Electronic Health Record Tasks
  4. 2024Lessons Learned on Information Retrieval in Electronic Health Records: A Comparison of Embedding Models and Pooling Strategies
  5. 2025Retrieval-Augmented Generation in Medicine: A Scoping Review of Technical Implementations, Clinical Applications, and Ethical Considerations
  6. 2025Retrieval-Augmented Framework for LLM-Based Clinical Decision Support
  7. 2026Retrieval-Augmented LLMs for Evidence Localization in Clinical Trial Recruitment from Longitudinal EHR Narratives
  8. 2025Grounding Large Language Models in Clinical Evidence: A Retrieval-Augmented Generation System for Querying UK NICE Clinical Guidelines