Among the biggest contributors to the high cost of healthcare in the U.S. are the inherent complexities and misaligned financial interests of payers, providers, and patients. Change Healthcare is using artificial intelligence (AI) and machine learning (ML) to identify inefficiencies and drive them out of administrative processes in the healthcare system and, as a result, help reduce costs and improve outcomes for payers, providers, and patients.
Healthcare struggles with a massive administrative burden that costs hundreds of billions of dollars annually.1 In fact, many of these unnecessary administrative costs are associated with fraud, waste, and abuse; no- or low-value-added work; and a lack of collaboration between stakeholders. Machine learning and AI have the power to change this––helping to reduce costly, time-consuming manual processes, and truly changing the cost-quality curve in healthcare.
By embedding AI into our financial, clinical, and engagement solutions, we are steadily eliminating inefficiencies from our customers' workflows and removing barriers to collaboration. Our practical approach to AI focuses on making healthcare more efficient and cost-effective. Today, solutions and services across our portfolio use AI to help customers improve payment accuracy, reduce denials, enhance payment forecasting, and slash administrative overhead.
CareSelectTM Imaging is a decision support solution for health systems that want to leverage their EHR to develop an enterprise-wide standard of care for advanced imaging, and to comply with the Protecting Access to Medicare Act.
service lines representing $268B, used to train Claims Lifecycle AI Model*
of denials can be identified and flagged pre-submission*
faster speed of auto-coding vs. manual coding EMS claims
1. Health Affairs and the Robert Wood Johnson Foundation. "Health Policy Brief: Reducing Waste in Health Care," Health Affairs, December 13, 2012.
*Statistics are Internal Change Healthcare Metrics