1. Revealing the impact of social circumstances on the selection of cancer therapy through natural language processing of social work notes
- Author
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Sun, Shenghuan, Zack, Travis, Williams, Christopher YK, Butte, Atul J, and Sushil, Madhumita
- Subjects
Health Services and Systems ,Health Sciences ,Cancer ,Breast Cancer ,Clinical Research ,Women's Health ,Good Health and Well Being ,natural language processing ,social work notes ,social determinants of health ,cancer therapy ,selection of cancer therapy ,Health services and systems - Abstract
ObjectiveWe aimed to investigate the impact of social circumstances on cancer therapy selection using natural language processing to derive insights from social worker documentation.Materials and methodsWe developed and employed a Bidirectional Encoder Representations from Transformers (BERT) based approach, using a hierarchical multi-step BERT model (BERT-MS), to predict the prescription of targeted cancer therapy to patients based solely on documentation by clinical social workers. Our corpus included free-text clinical social work notes, combined with medication prescription information, for all patients treated for breast cancer at UCSF between 2012 and 2021. We conducted a feature importance analysis to identify the specific social circumstances that impact cancer therapy regimen.ResultsUsing only social work notes, we consistently predicted the administration of targeted therapies, suggesting systematic differences in treatment selection exist due to non-clinical factors. The findings were confirmed by several language models, with GatorTron achieving the best performance with an area under the receiver operating characteristic curve (AUROC) of 0.721 and a Macro F1 score of 0.616. The UCSF BERT-MS model, capable of leveraging multiple pieces of notes, surpassed the UCSF-BERT model in both AUROC and Macro-F1. Our feature importance analysis identified several clinically intuitive social determinants of health that potentially contribute to disparities in treatment.DiscussionLeveraging social work notes can be instrumental in identifying disparities in clinical decision-making. Hypotheses generated in an automated way could be used to guide patient-specific quality improvement interventions. Further validation with diverse clinical outcomes and prospective studies is essential.ConclusionsOur findings indicate that significant disparities exist among breast cancer patients receiving different types of therapies based on social determinants of health. Social work reports play a crucial role in understanding these disparities in clinical decision-making.
- Published
- 2024