Bulk Claims Data Ingestion Into Data Cloud

Population Health Management and Predictive Analytics

Context:
Consider a healthcare provider organization that serves a large population of patients with chronic conditions, such as diabetes or heart disease. These conditions require ongoing management and monitoring to prevent complications and deteriorations that could lead to hospital admissions, which is a high cost for both the healthcare system and patients.

Scenario:
The organization struggles with high rates of emergency room visits and hospital readmissions among its chronic condition patients. Traditional methods of identifying at-risk patients rely on manual review of patient records and reactive approaches to care, which are time-consuming and often too late to prevent adverse events effectively.

Solution:
By integrating CMS BCDA data into Salesforce Data Cloud, the organization can use advanced analytics and AI capabilities to analyze claims data in real time. This data includes comprehensive information on patient encounters, procedures, medications, and outcomes. Combined with clinical data residing in the organization's EMR systems, it provides a comprehensive and rich dataset for analytics. Using predictive analytics, the system identifies patterns and risk factors associated with potential hospital admissions or emergency room visits.

For example, the analytics model identifies patients with diabetes who have had more than three emergency visits in the past year for hypoglycemia and are at a high risk of being readmitted in the next three months. Armed with this information, the healthcare provider can proactively meet these high-risk patients, offering personalized care management programs. These programs might include education on managing blood sugar levels, regular check-ins with a care manager, and home monitoring devices to track their health metrics in real time.

Outcome:
This approach enables the healthcare provider to intervene before a patient's condition worsens, preventing hospital admissions and improving the patient's quality of life. Patients benefit from personalized, timely care that addresses their specific needs and risks, while the healthcare provider reduces costs associated with emergency care and hospital readmissions. Through the predictive analytics capabilities enabled by the integration, the organization transforms its care model from reactive to proactive, focusing on preventing complications and promoting overall patient well-being.