The $2.7 trillion US healthcare market suffers from significant inefficiencies with as much as $800 billion of healthcare spending each year being wasteful or redundant. With increasing pressure to reduce costs, the healthcare industry is turning
to the wealth of newly available, digitized and standardized data: clinical data (electronic medical records, medical images), claims and cost data (care utilization and cost estimates), pharmaceutical data (pharmaceutical trials), patient demographic
data (patient behaviors and preferences), and sensor data from wearable devices and smart phones. The volume of healthcare data is expected to swell to 2,314 exabytes by 2020, more than the projected annual global IP traffic in 2019. By correlating
and performing advanced analytics and machine learning on these data, both insurance companies and healthcare providers can reduce the cost of care, improve health outcomes, and promote patient engagement.
For example, C3 HealthScore Analytics applies advanced machine learning algorithms to cost and claims data, clinical diagnostic data, hospital admissions data, and electronic medical record data to clarify and optimize decisions about how best
to care for patients and reduce the overall cost of care. With C3 HealthScore Analytics, providers and payers are able to track the efficacy of care management at the individual patient and aggregate portfolio level; identify high-risk patients;
and prioritize remediation efforts to deliver tailored patient care plans and incentives to promote long-term health.
Product Trials C3 Applications