Creating the Data-Driven Future of
Care, Research and Insurance
Anywhere from 3 to 10 percent of annual US healthcare spending is involved in improper billings, resulting in up to $200 billion in lost revenues for the healthcare system.
By using machine learning and predictive analytics on the Splice Machine platform, insurance companies can proactively identify suspect payments and prevent them from going out the door instead of using the ‘pay and chase’ payment recovery model with its provider partners.
Data-Driven Value-Based Care
On Splice Machine, insurers can combine claims data with clinical data, electronic health records, lab results, patient-generated data, and other key data sets in a single, integrated data platform.
With a single patient profile, they can better identify opportunities to improve outcomes and help empower providers to provide individualized care that supports value-based reimbursement programs.
Growth in the AI health market is expected to reach $6.6 billion by 2021, and—according to Accenture—the combined deployment of key clinical health AI applications can potentially create $150 billion in annual savings for the U.S. healthcare economy by 2026.
With Splice Machine, organizations can leverage high volumes of patient data and machine learning to help identify and deliver more precise medical treatment options in a timely fashion.
Real-Time Patient Analytics
Healthcare organizations are able to bring together numerous data sources in a single platform on Splice Machine, enabling clinicians to have insights in the moment.
From identifying which patients are most likely to go into septic shock based on historical and real-time data, to spotting trends in its population that can help them rethink the care they are providing, healthcare providers can deliver better patient outcomes.