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RCM Electronification Case Studies

Without a doubt, Artificial Intelligence, Deep Learning, Machine Learning, and other technologies are streamlining the revenue cycle management and healthcare payments industries in many different ways.

Roni Boker, OrboGraph product manager notes: "Market need still exists, and organizations are now having to move faster than ever with new work environments as a means to implement greater controls on their data and assist with compliance and resiliency."

Real-world examples of electronification -- with tangible results -- are occurring throughout the business ecosystem, and those who adopt the technologies are realizing the benefits.

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We've assembled three case studies of unique businesses leveraging OrboAccess for electronification of paper-based remittances and EOBs/EOPs.

Client Profile #1: RCM Cloud Servicer

Challenge: Legacy Vendor, Operational Gaps, and Operational Visibility

After struggling with their existing offshore BPO vendor -- this vendor provided paper EOB conversion to 835 management for over 10 years via the use of an extensive data entry network of keyers -- the RCM Cloud Servicer realized a need to automate and address operational gaps including: process visibility, cost, reliability, process controls, and posting errors — an ongoing problem for healthcare providers and their patients.

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Client Profile #2: US Headquartered BPO and Consulting Company

Challenge: Overcoming a Legacy Platform and a Challenging Labor Environment

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This organization also became frustrated with their existing offshore BPO vendor which, once again, provided paper EOB conversion to 835 management for over 10 years via the use of an extensive data entry network of keyers. And, again, automation and addressing operational gaps were key to their solution.

Client Profile #3: The Traditional RCM Outsourcer

Challenge: Manually Scanning and Processing

Internal data entry processes requiring their U.S.-based labor force to scan paper EOB and remittance documents -- entering all transactional data while managing a complex process of excluding payers and select patient payments -- became a prime candidate for improvement via AI and Machine Learning.

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Each client faced a unique challenge. Click below to see how electronification help them overcome their challenge.

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