#### [The $265 Billion Problem: How Unified Data Unlocks Revenue Intelligence in Healthcare](/content/sift-perspectives/the-265-billion-problem-how-unified-data-unlocks-revenue-intelligence-in-healthcare/index.html)

Discover how unified clinical and financial data can solve healthcare’s $265B revenue cycle inefficiency problem with actionable AI-driven insights.

[January 7, 2025](/content/sift-perspectives/the-265-billion-problem-how-unified-data-unlocks-revenue-intelligence-in-healthcare/index.html)

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#### [Rules Are Too Rigid For The Revenue Cycle](/content/sift-perspectives/rules-are-too-rigid-for-the-revenue-cycle/index.html)

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...

[November 3, 2021](/content/sift-perspectives/rules-are-too-rigid-for-the-revenue-cycle/index.html)

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#### [Want To Add AI to Your Revenue Cycle? Data Intelligence is the First Step.](/content/sift-perspectives/want-to-add-ai-to-your-revenue-cycle-data-intelligence-is-the-first-step/index.html)

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...

[November 3, 2021](/content/sift-perspectives/want-to-add-ai-to-your-revenue-cycle-data-intelligence-is-the-first-step/index.html)

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#### [6 Ways To Use Your Healthcare Payments Data To Improve Collections](/content/sift-perspectives/6-ways-to-use-your-healthcare-payments-data-to-improve-collections/index.html)

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...

[May 20, 2020](/content/sift-perspectives/6-ways-to-use-your-healthcare-payments-data-to-improve-collections/index.html)

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#### [Your Data Is Too Messy For Data Science](/content/sift-perspectives/too-messy-for-data-science/index.html)

In healthcare payments, where data flows from multiple systems and standards are a moving target, data can be pretty filthy. This means mismatched formats, errors and inconsistencies. Having clean data is often the biggest roadblock to being able to reap...

[July 9, 2019](/content/sift-perspectives/too-messy-for-data-science/index.html)

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