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revenue cycle analytics

Machine Learning

Rules Are Too Rigid For The Revenue Cycle

Automation (RPA) makes the revenue cycle more efficient — saving time and decreasing errors. While this is an improvement for health systems and hospitals RPA efficiencies are one-dimensional. Fully optimizing the revenue cycle and getting the most out of AI (including RPA) requires a clear and holistic view of payments, an understanding of the full lifecycle flow of claims.

Justin Nicols
June 19, 2019
Data Science

Want To Add AI to Your Revenue Cycle? Data Intelligence is the First Step.

So you want to add AI to your revenue cycle? You have to start by establishing a solid foundation of data intelligence. This comes from normalizing and organizing payments data in a way that provides actionable insights. This works will establish the where/why/how of your AI goals.

Justin Nicols
June 19, 2019
Healthcare Payments

Healthcare Providers Have Become Lending Organizations

Every day healthcare providers are extending credit in the form of care, and they have little idea whether, how much or when they will be paid. It’s time for healthcare providers to start deploying well-established data science and analytics tools to forecast payments and optimize outcomes.

Justin Nicols
June 19, 2019
Healthcare Payments

6 Ways To Use Your Healthcare Payments Data To Improve Collections

AI, machine learning and predictive models are abstract terms in the revenue cycle. How do you actually move past the buzzwords and get value out of your healthcare payments data? Here are six ways healthcare providers and RCMs can truly operationalize healthcare payments data to improve patient collections and revenue cycle operations.

Justin Nicols
June 19, 2019
Revenue Cycle Analytics

Filling The Gap In Revenue Cycle Reporting

Sift Healthcare's Rev/Track provides revenue cycle leaders with instant access to detailed intelligence that enables them to extract meaningful insights from their healthcare payments data -- information that drives better-informed decisions around revenue cycle operations.

Justin Nicols
June 19, 2019
Revenue Cycle Analytics

Rev/Track Leverages AI To Improve Revenue Cycle Operations

Rev/Track leverages Sift Healthcare's AI and machine learning to help healthcare providers and RCMs to optimize revenue cycle operations. Rev/Track delivers detailed intelligence around payments behavior, insurance denials, collection trends, patient segments and revenue cycle work efforts.

Bethany Grabher
September 25, 2019
Revenue Cycle Analytics

Introducing The Sift Quality Score

Introducing The Sift Quality Score. For revenue cycle managers, understanding account quality and its impact on patient collections is essential for forecasting revenue, optimizing rcm workflows and ensuring the best strategy is in place for managing resources. Sift’s Quality Score is derived from Sift’s predictive model scores — it tracks account quality over the early-out period, enabling RCMs to more intelligently forecast revenue throughout each billing cycle.

Bethany Grabher
September 25, 2019
Revenue Cycle Analytics

Hospital CFO’s & The “Negligible” Use Of Data Analytics

93% of healthcare administrators say that data analytics are “crucial” to future healthcare operations. At the same time, 84% say the usage of advanced analytics at their organization is “negligible”. In healthcare payments, there are three key roadblocks to the utilization of advanced analytics to improve the revenue cycle.

Justin Nicols
June 19, 2019