Transforming SDOH Screening: Towards a General Framework for Transformer-based Prediction of Social Determinants of Health

Social Determinants of Health (SDOH) play a crucial role in healthcare outcomes, yet identifying them from unstructured patient data remains a challenge. This research explores the potential of Large Language Models (LLMs) for automated SDOH identification from patient notes. We propose a general framework for SDOH screening that is simple and straightforward. We leverage existing SDOH datasets, adapting and combining them to create a more comprehensive benchmark for this task, addressing the research gap of limited datasets. Using the benchmark and proposed framework, we conclude by conducting several preliminary experiments exploring and comparing promising LLM system implementations. Our findings highlight the potential of LLMs for automated SDOH screening while emphasizing the need for more robust datasets and evaluation frameworks.