The Impact of Social Determinants of Health on Predictive Healthcare Models: A Data Science Perspective
Abstract
Social determinants of health (SDOH), such as income, education, and access to healthcare services, play a crucial role in patient outcomes. This paper reviews the integration of SDOH into predictive healthcare models using machine learning and statistical techniques. The study explores methodologies for handling missing data, feature engineering approaches, and the impact of SDOH on disease prediction accuracy. Ethical considerations related to algorithmic bias and disparities in healthcare access are also analyzed. Recommendations for enhancing data-driven policymaking and equitable healthcare delivery through SDOH-aware models are provided.
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