mlsanityData to 7 Oct 2026

The 2022 n2c2/UW Shared Task on Extracting Social Determinants of Health

arXiv 2301.05571 ↗First posted 13 Jan 2023cs.CLcited by 21

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Abstract (arXiv)

Objective: The n2c2/UW SDOH Challenge explores the extraction of social determinant of health (SDOH) information from clinical notes. The objectives include the advancement of natural language processing (NLP) information extraction techniques for SDOH and clinical information more broadly. This paper presents the shared task, data, participating teams, performance results, and considerations for future work. Materials and Methods: The task used the Social History Annotated Corpus (SHAC), which consists of clinical text with detailed event-based annotations for SDOH events such as alcohol, drug, tobacco, employment, and living situation. Each SDOH event is characterized through attributes related to status, extent, and temporality. The task includes three subtasks related to information extraction (Subtask A), generalizability (Subtask B), and learning transfer (Subtask C). In addressing this task, participants utilized a range of techniques, including rules, knowledge bases, n-grams, word embeddings, and pretrained language models (LM). Results: A total of 15 teams participated, and the top teams utilized pretrained deep learning LM. The top team across all subtasks used a sequence-to-sequence approach achieving 0.901 F1 for Subtask A, 0.774 F1 Subtask B, and 0.889 F1 for Subtask C. Conclusions: Similar to many NLP tasks and domains, pretrained LM yielded the best performance, including generalizability and learning transfer. An error analysis indicates extraction performance varies by SDOH, with lower performance achieved for conditions, like substance use and homelessness, that increase health risks (risk factors) and higher performance achieved for conditions, like substance abstinence and living with family, that reduce health risks (protective factors).

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 9 of its 44 references that are in the map. First posted on arXiv 13 Jan 2023.

Builds on

9 of 44 references.

References · 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 8; 2024: 6; 2025: 2; 2026: 5.

21 papers.

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  1. 2023Large Language Models to Identify Social Determinants of Health in Electronic Health Recordscited by 55
  2. 2023Model Tuning or Prompt Tuning? A Study of Large Language Models for Clinical Concept and Relation Extractioncited by 32
  3. 2023Clinical Concept and Relation Extraction Using Prompt-based Machine Reading Comprehensioncited by 13
  4. 2023Prompt-based Extraction of Social Determinants of Health Using Few-shot Learningcited by 8
  5. 2023Generative Large Language Models Are All-purpose Text Analytics Engines: Text-to-text Learning Is All Your Needcited by 6
  6. 2023Backdoor Adjustment of Confounding by Provenance for Robust Text Classification of Multi-institutional Clinical Notescited by 5
  7. 2024GAMedX: Generative AI-based Medical Entity Data Extractor Using Large Language Modelscited by 5
  8. 2024Leveraging Large Language Models to Extract Information on Substance Use Disorder Severity from Clinical Notes: A Zero-shot Learning Approachcited by 4
  9. 2024BioMistral-NLU: Towards More Generalizable Medical Language Understanding through Instruction Tuningcited by 4
  10. 2023Task formulation for Extracting Social Determinants of Health from Clinical Narrativescited by 3
  11. 2024Synth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Textcited by 3
  12. 2026PVminer: A Domain-Specific Tool to Detect the Patient Voice in Patient Generated Datacited by 2
9 more
  1. 2023Enhancing Robustness of Foundation Model Representations under Provenance-related Distribution Shiftscited by 1
  2. 2024CACER: Clinical Concept Annotations for Cancer Events and Relationscited by 1
  3. 2025A Study of Large Language Models for Patient Information Extraction: Model Architecture, Fine-Tuning Strategy, and Multi-task Instruction Tuningcited by 1
  4. 2026A Causal Language Modeling Detour Improves Encoder Continued Pretrainingcited by 1
  5. 2024Improving Generalizability of Extracting Social Determinants of Health Using Large Language Models through Prompt-tuningcited by 0
  6. 2025Improving Social Determinants of Health Documentation in French EHRs Using Large Language Modelscited by 0
  7. 2026NOWJ @BioCreative IX ToxHabits: An Ensemble Deep Learning Approach for Detecting Substance Use and Contextual Information in Clinical Textscited by 0
  8. 2026A Parameter-Efficient Transfer Learning Approach through Multitask Prompt Distillation and Decomposition for Clinical NLPcited by 0
  9. 2026Using reasoning LLMs to extract SDOH events from clinical notescited by 0