Sift Healthcare, a leading innovator in AI-powered healthcare payment solutions, has secured $20 million series B funding to further innovate and scale its AI-based Co-Pilot to support rising market demands.
According to the company’s announcement on Thursday, May 9, 2024, the funding round was led by Rock River Capital, with continued contributions from existing investors, including First Trust Capital Partners, Allos Ventures and Rock River Capital.
Sift will use the additional funds to scale the company and its operations while investing more in technology—specifically in artificial intelligence- as the company works on what could become an industry-first Payments Intelligence Platform.
The company’s series B funding underscores the ever-growing confidence in AI-powered technology solutions to help healthcare organizations leverage data to enhance their payments collections margins and improve cashflow.
RevProtect— AI-powered Payments Intelligence Co-Pilot
RevProtect was built through Sift’s collaborations with industry-leading workflow and service companies to guide clinical workflows and enable utilization review and clinical documentation improvement. This helps coding professionals take meaningful and proactive steps in improving accuracy, which is vital in preventing clinical denials and reducing avoidable write-offs.
The Payments Intelligence platform is designed to help healthcare organisations have greater visibility into payment collections by unifying payment and clinical data to create a longitudinal data set that links clinical outputs directly to financial outcomes.
Based on the data sets, the smart payment systems leverage machine-learning to deliver interventions predicting adverse payment outcomes and deliver workflow-related alerts as well as recommendations, thereby optimising patient financial engagement.
Additionally, the system can accurately determine patient cost responsibility upfront by eliminating variability and opacity surrounding payer reimbursement probability and the amount involved in such cases.
