GREATER MADISON CHAMBER OF COMMERCE: Wind River Financial and Sift Healthcare Announce Partnership

Greater Madison Chamber of Commerce issued the following announcement on Jan. 25.

Wind River Financial, a payment processing company based out of Madison, announced its strategic partnership with Milwaukee-based revenue cycle intelligence company, Sift Healthcare. The new partnership will allow the two companies to provide a unique set of solutions that greatly optimize the revenue cycle for healthcare providers by improving claims workflow, reimbursement performance and patient financial engagement.

Wind River Financial brings extensive experience helping healthcare organizations improve their payment related cashflow and efficiency. While working with healthcare networks, independent clinics, hospitals, doctors’ offices and laboratory facilities, Wind River provides superior experience and know-how for patient-related payments. At the same time, Wind River provides all its related solutions with an eye toward a patient data security approach versus basic “check-the-box” PCI compliance.

Sift Healthcare puts an organization’s data to work creating a true picture of patients’ submissions, claims and payments across multiple siloed data sources. By leveraging the latest big data technology, the platform allows organizations to gain deep and actionable insights into trends, all in an easy-to-use analytics dashboard. Sift brings all of this together on a HIPAA-compliant platform to ensure security best practices. The team behind Sift has a broad understanding of data analytics and decades of experience with medical and insurance claims.

“Wind River is thrilled to expand our portfolio of products,” said Steve Staden, Wind River’s senior vice president of product management. “By combining Wind River’s payment technology, expertise and first-class service with revenue cycle optimization, our partnership with Sift Healthcare can help healthcare organizations collect more and sooner. Being able to lower costs and collect more will be on the wish list of every CFO and director of revenue cycle in 2019, and we can help make that happen.”

Established in 2013, the Sift Healthcare team has built enterprise data technology platforms and pioneered data mining and predictive analytics technology. The company is compelled to help eliminate the 25 percent of wasted administrative costs and over $200 billion in wasted billing costs seen annually in healthcare. That includes accelerating insurance payments, reducing overall denials, increasing patient responsibility collections, providing visibility into payer contracts and creating smarter workflows for organizations.

“We are eager to begin working with the long-trusted payment experts at Wind River,” said Sift Healthcare founder and CEO Justin Nicols. “I’m looking forward to what our teams will do together, paving the path to improved intelligence in healthcare.”

About Wind River Financial

Wind River Financial is a payment processing company based in Madison, Wis. Its team of experts works to make payment processing safer and easier for thousands of merchant clients throughout the country. In addition to healthcare, Wind River partners with software providers, banks, credit unions and trade associations to design and customize processing solutions for their clients and stakeholders. To learn more, visit

About Sift Healthcare

Sift Healthcare revolutionizes the revenue cycle through predictive analytics. The Milwaukee-based company provides revenue cycle management and revenue cycle technology companies with analytic insights that drive workflow optimization, reduce denials and customize the patient pay experience, which increases collections and helps maintain relationships for providers. Sift Healthcare’s predictive analytics platform turns the most challenging and important healthcare data into a powerful operational and patient financial management tool that improves the reimbursement and patient pay collections process and reduces the need for human intervention. To learn more, visit

Original source can be found here.

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