DATA-DRIVEN STRATEGIES FOR ADDRESSING SOCIAL DETERMINANTS OF HEALTH IN VALUE-BASED CARE MODELS

Abstract

Social Determinants of Health (SDoH) encompass a broad range of social and economic factors, such as access to education, stable employment, safe housing, and adequate nutrition, all of which profoundly influence individuals' health status and well-being. Recognizing the profound impact of SDoH on health outcomes is fundamental to advancing healthcare delivery and pursuing health equity. Value-Based Care (VBC) frameworks, which aim to improve patient outcomes while controlling costs by incentivizing quality care delivery, addressing SDoH emerges as a critical imperative. However, integrating SDoH considerations effectively into VBC models poses significant challenges, primarily due to the complex interplay of socioeconomic factors and healthcare delivery systems. This is where the role of data engineering becomes paramount.

Data engineering, the discipline concerned with designing and managing data processing systems, plays a pivotal role in unlocking the potential of SDoH within VBC frameworks. By leveraging advanced data analytics techniques and technologies, data engineering facilitates the systematic collection, integration, and analysis of diverse data sources relevant to SDoH. This includes electronic health records, socioeconomic databases, community resources information, and even data from social media platforms. Through sophisticated data engineering approaches, healthcare organizations can gain deeper insights into the social determinants influencing patient health outcomes.

The objectives of this paper are multifaceted. It aims to provide a comprehensive understanding of the importance of SDoH in shaping patient health outcomes within the context of VBC. It seeks to elucidate the pivotal role of data engineering in addressing SDoH challenges and opportunities. By examining methodologies for SDoH data collection, analysis, and integration, the paper aims to equip healthcare stakeholders with actionable insights to enhance their SDoH interventions within VBC models. The paper endeavors to contribute to the advancement of data-driven strategies that promote health equity and improve patient outcomes in value-based healthcare delivery.