دورية أكاديمية
On the development and validation of large language model-based classifiers for identifying social determinants of health.
| العنوان: | On the development and validation of large language model-based classifiers for identifying social determinants of health. |
|---|---|
| المؤلفون: | Gabriel RA; Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92037.; Department of Biomedical Informatics, University of California, San Diego Health, La Jolla, CA 92037., Litake O; Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92037., Simpson S; Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92037., Burton BN; Department of Anesthesiology, University of California, Los Angeles, CA 90095., Waterman RS; Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92037., Macias AA; Division of Perioperative Informatics, Department of Anesthesiology, University of California, San Diego, La Jolla, CA 92037. |
| المصدر: | Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2024 Sep 24; Vol. 121 (39), pp. e2320716121. Date of Electronic Publication: 2024 Sep 16. |
| نوع المنشور: | Journal Article |
| اللغة: | English |
| بيانات الدورية: | Publisher: National Academy of Sciences Country of Publication: United States NLM ID: 7505876 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1091-6490 (Electronic) Linking ISSN: 00278424 NLM ISO Abbreviation: Proc Natl Acad Sci U S A Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: Washington, DC : National Academy of Sciences |
| مواضيع طبية MeSH: | Social Determinants of Health* , Electronic Health Records* , Food Insecurity* , Ill-Housed Persons* , Domestic Violence*, Humans |
| مستخلص: | The assessment of social determinants of health (SDoH) within healthcare systems is crucial for comprehensive patient care and addressing health disparities. Current challenges arise from the limited inclusion of structured SDoH information within electronic health record (EHR) systems, often due to the lack of standardized diagnosis codes. This study delves into the transformative potential of large language models (LLM) to overcome these challenges. LLM-based classifiers-using Bidirectional Encoder Representations from Transformers (BERT) and A Robustly Optimized BERT Pretraining Approach (RoBERTa)-were developed for SDoH concepts, including homelessness, food insecurity, and domestic violence, using synthetic training datasets generated by generative pre-trained transformers combined with authentic clinical notes. Models were then validated on separate datasets: Medical Information Mart for Intensive Care-III and our institutional EHR data. When training the model with a combination of synthetic and authentic notes, validation on our institutional dataset yielded an area under the receiver operating characteristics curve of 0.78 for detecting homelessness, 0.72 for detecting food insecurity, and 0.83 for detecting domestic violence. This study underscores the potential of LLMs in extracting SDoH information from clinical text. Automated detection of SDoH may be instrumental for healthcare providers in identifying at-risk patients, guiding targeted interventions, and contributing to population health initiatives aimed at mitigating disparities. Competing Interests: Competing interests statement:The authors declare no competing interest. |
| فهرسة مساهمة: | Keywords: AI; large language models; social determinants of health |
| تواريخ الأحداث: | Date Created: 20240916 Date Completed: 20240916 Latest Revision: 20240916 |
| رمز التحديث: | 20240917 |
| DOI: | 10.1073/pnas.2320716121 |
| PMID: | 39284061 |
| قاعدة البيانات: | MEDLINE |
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