Usal

Common Semantic Standardized Data Model (CSSDM) to achieve interoperability in continuity of care network

Departamento de Informática y Automática

Investigador: Subhashis Das; Sara Sara Rodríguez González

Descripción de la innovación

The growth of digital platforms has accelerated the shift toward technology-driven, home-based healthcare solutions, empowering individuals to monitor their health and share data with healthcare professionals when necessary. However, developing an effective care plan management system involves more than simply analyzing hospital records and Electronic Health Records (EHRs). It requires addressing individual patient needs and considering social determinants of health, such as living conditions and the exchange of healthcare information across different care settings. This complex healthcare ecosystem faces challenges like schema diversity (across EHRs, personal health records, etc.) and varying medical terminologies (e.g., ICD, SNOMED-CT) used in ancillary healthcare services. Achieving interoperability between diverse systems and applications is essential. The European Interoperability Framework (EIF) highlights the importance of ensuring patient-centric access and control over healthcare data. In this paper, we introduce an integrated ontological model—the Common Semantic Data Model for Social Determinants of Health (CSSDH)—which combines ISO/DIS 13940:2024 ContSys with the WHO framework for Social Determinants of Health. CSSDH is designed to enhance interoperability across the continuity of care networks.

Antecedentes

The objective is to collect an individual’s Social Determinants of Health (SDoH) data and integrate it with their Electronic Health Record (EHR) data in order to support more informed, personalized, and effective clinical decision-making.

Impacto Económico y Social

Economic Impact: 1. Reduced Healthcare Costs: By identifying non-medical factors that affect health (e.g., housing instability, food insecurity), interventions can be made earlier and more effectively. Preventive care becomes more targeted, reducing avoidable hospitalizations, emergency visits, and chronic disease progression. 2. Improved Resource Allocation: Health systems can allocate funding and resources more efficiently by understanding population-level needs beyond clinical data. For example, communities with high food insecurity might receive more nutrition programs, leading to better ROI on public health spending. 3. Enhanced Productivity: Healthier populations are more productive, reducing absenteeism and increasing economic contributions. Employers and insurers also benefit from lower healthcare premiums and better employee health. 4. Value-Based Care Optimization: SDoH data supports value-based care models, allowing providers to meet quality metrics tied to reimbursement. It enables more accurate risk adjustment for reimbursement calculations, especially in Medicaid and Medicare programs. Social Impact 1. Health Equity Advancement: Incorporating SDoH helps address systemic health disparities by recognizing the root causes of poor health in underserved communities. Tailored care plans can be developed that reflect social and environmental realities. 2. Empowered Communities: Communities become more informed and engaged when their social challenges are recognized and addressed in healthcare settings. Programs can be designed to address upstream factors like education, employment, and transportation. 3. Better Patient Outcomes: Holistic care that accounts for both clinical and social needs leads to improved health outcomes, quality of life, and patient satisfaction. Patients are more likely to adhere to treatment plans that are realistic within their social contexts. 4. Improved Trust in Healthcare Systems: When patients feel their circumstances are truly understood, it fosters trust, especially in marginalized groups with historical distrust of healthcare systems. For more information see The 29th EURAS Annual Standardisation Conference accepted paper link https://www.euras.org/img/upload/pdf/Final_Programme-v2.pdf

Colectivos de interés: Administración pública, Ciudadania, Instituciones sin ánimo de lucro

CNAE a 2 dígitos: 86 - Actividades sanitarias

Comunidad Autónoma: Castilla y León

Rama: Ingeniería y Arquitectura

Año: 2025

Palabras clave: Continuity of care, EHR, Knowledge Graph, OWL, Social Determinants of Health