ArticleJournal of the American Medical Informatics Association : JAMIA2023
Leveraging natural language processing to augment structured social determinants of health data in the electronic health record.
Article in Journal of the American Medical Informatics Association : JAMIA, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 2 syntheses or guidelines pooled it, 39 citations in OpenAlex.
- Applications of Natural Language Processing and Large Language Models for Social Determinants of Health: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.Perspectives in health information management · 2024Pooled it
- Maternal Vulnerability Indicators Derived from Free-Text Clinical Documentation in Adolescent Pregnancy.Medicina (Kaunas, Lithuania) · 2026Article
- Article
- Article
- Social Determinants of Health and 1-Year Buprenorphine Initiation Among Justice-Involved Veterans.JAMA network open · 2026Article
- Integration of fairness-awareness into clinical language processing models.Communications medicine · 2026Article
- Lightweight open-source large language models versus cTAKES for information extraction from discharge summaries: tobacco smoking status test case.JAMIA open · 2026Article
- Social Work-Supported Strategies to Reduce Postoperative Readmissions in Orthopedic Surgery: A Narrative Review.Cureus · 2026Review
- Using reasoning LLMs to extract SDOH events from clinical notes.Proceedings. IEEE International Conference on Healthcare Informatics · 2026Article
- A Research Agenda to Mitigate Racial and Ethnic Disparities in U.S. Critical Care Medicine: An Official American Thoracic Society Research Statement.American journal of respiratory and critical care medicine · 2025Article
- A large language model-based approach to quantifying the effects of social determinants in liver transplant decisions.NPJ digital medicine · 2025Article
- Synth-SBDH: A Synthetic Dataset of Social and Behavioral Determinants of Health for Clinical Text.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2025Article
- Predicting Behavioral Determinants of Health from Clinical Text Using Transformer Models and BiLSTM.medRxiv : the preprint server for health sciences · 2025Article
- Informatics at the Frontier of Cancer Research.Cancer research · 2025Review
- Extraction of Social Determinants of Health From Electronic Health Records Using Natural Language Processing.JCO clinical cancer informatics · 2025Article
- Social determinants of health extraction from clinical notes across institutions using large language models.NPJ digital medicine · 2025Article
- Patient and clinician acceptability of automated extraction of social drivers of health from clinical notes in primary care.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study.Journal of medical Internet research · 2025Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveSocial determinants of health (SDOH) impact health outcomes and are documented in the electronic health record (EHR) through structured data and unstructured clinical notes. However, clinical notes often contain more comprehensive SDOH information, detailing aspects such as status, severity, and temporality. This work has two primary objectives: (1) develop a natural language processing information extraction model to capture detailed SDOH information and (2) evaluate the information gain achieved by applying the SDOH extractor to clinical narratives and combining the extracted representations with existing structured data. MATERIALS AND
methodsWe developed a novel SDOH extractor using a deep learning entity and relation extraction architecture to characterize SDOH across various dimensions. In an EHR case study, we applied the SDOH extractor to a large clinical data set with 225 089 patients and 430 406 notes with social history sections and compared the extracted SDOH information with existing structured data.
resultsThe SDOH extractor achieved 0.86 F1 on a withheld test set. In the EHR case study, we found extracted SDOH information complements existing structured data with 32% of homeless patients, 19% of current tobacco users, and 10% of drug users only having these health risk factors documented in the clinical narrative.
conclusionsUtilizing EHR data to identify SDOH health risk factors and social needs may improve patient care and outcomes. Semantic representations of text-encoded SDOH information can augment existing structured data, and this more comprehensive SDOH representation can assist health systems in identifying and addressing these social needs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.