Proactive Risk Surveillance for Heart Failure and Stroke: A Quality-by-Design Approach With Multimodal Data Integration

OBJECTIVES: The value of real-world evidence (RWE) is widely recognised and is valued by regulators, HTA bodies and manufacturers. The vast number of available data sources provide opportunities to support complementary evidence generation, gaining a deeper understanding of the impact of a disease or treatment. RWE can also be used to evaluate the risk of a disease such as heart failure (HF) and stroke, which are both leading causes of morbidity and mortality worldwide. Early detection and intervention are crucial for improved patient outcomes.

METHODS: We propose a quality-by-design (QbD) framework for proactive risk surveillance in HF and stroke patients. It would integrate information from various data sources to create a comprehensive picture of each patient’s health status and risk factors. The data sources would include Electronic Health Records (EHR), claims data and social media data. The QbD would also include patient characteristics, comorbidities, chronic complications and adverse events, stratified by age groups. Anomaly detection and association mining techniques were employed to identify patients at high risk of future events The QbD emphasises proactive risk management throughout the patient care pathway.

RESULTS: The framework aims to utilise multimodal data Integration:

• Patient-Centric: Focuses on individual patient needs and risk factors

• Data-Driven: Utilises real-world data for risk assessment and intervention strategies
• Proactive: Aims to prevent future events rather than reacting to crises
• Continual Improvement: Regularly evaluates and refines the risk model based on new data and outcomes.

CONCLUSIONS: This proposed QbD framework for proactive risk surveillance in HF and stroke patients leverages the power of multimodal data analysis and advanced statistical techniques. By integrating diverse data sources and employing anomaly detection and association mining, healthcare providers can identify high‑risk patients and implement targeted interventions, leading to improved patient outcomes and reduced healthcare costs.