Automation & Outsourcing – Options for Medical Billing Revenue Cycle

Does automation & outsourcing work efficiently for the medical billing revenue cycle? The medical billing revenue cycle has been a complex and complicated process in the healthcare industry, but automation and outsourcing offer distinct solutions for efficiency. Certain technologies are deployed to support automation and outsourcing that have been ranging from brittle robotic process automation (RPA) to robust artificial intelligence (AI) and machine learning (ML) that determines overall utility, compared to outsourcing across the revenue cycle.

This article brings you a different perspective on the medical billing revenue cycle and evaluating options for automation and outsourcing. Why wait? Let’s get started!

What is the Medical Billing Revenue Cycle?

  • Explaining from the basic, overall revenue cycle is a financial process that hospitals and healthcare systems follow to manage all of the administrative steps in identifying, processing, and collecting patient revenue. Everything from billing customers to collecting payments.
  • In recent years, the medical billing revenue cycle has evolved significantly, transforming from an almost entirely manual and paper-based process into a set of more automated workflows.
  • Having improved, this journey had become more efficient with automation with a goal of attaining higher clean claims and first-pass payment rates.
  • “Implementing automation doesn’t have to be difficult or involve hundreds of combined hours of work,” says the head of revenue cycle operations at a healthcare company.

Automation & Outsourcing to Medical Billing Revenue Cycle

  • Many healthcare organizations are doing medical billing revenue cycle operations manually yet.
  • Some have started harnessing the full power of automation driven by AI and ML, which can have a great impact across the revenue cycle.
  • Since healthcare professionals start navigating challenges like the rise in telehealth services and growth in patient responsibility for medical billing, and automation has become phenomenally integral to the revenue cycle, while outsourcing has also gained popularity.


  • In 2020, a survey from McKinsey & Co. revealed that the healthcare industry has the most increased and improved investment in AI during the pandemic.
  • This survey also noted high performance in terms of value-added services of their AI implementations.
  • It has also pointed and revealed some AI models that had not performed to the expectations due to sudden shifts in the revenue cycle that year.


  • Another survey report had revealed that the healthcare organizations were planning to outsource revenue cycle operations to the most in the wake of Covid-19.
  • A different study had estimated that the medical billing revenue cycle outsourcing market would double in size from 2020 to 2027, to $27 billion.
  • Both have their pros and cons. At a level, automation can offer a more efficient way to do anything from developing process documentation to determining insurance eligibility off of a patient card.
  • But not all automation is treated and created equal or the same. Older variants, such as RPA for automating discrete tasks in a similar way to a Microsoft Excel macro, are often too fragile to be either technically or economically sustainable for providers.
  • In the case of an outlier or edge case, RPA often can’t solve it, but AI and ML would provide more robust automation.
  • Moreover, outsourcing will provide more personnel with the necessary expertise, but at the costs of increased cyber-security risks and possibly longer time to collect.
  • Automation and outsourcing are well designed to address challenges in managing medical billing, reimbursement, and other revenue collection activities.
  • These challenges have evolved substantially over time and continue to change.

Few Medical Billing Revenue Cycle Challenges that Automation & Outsourcing can solve

  1. Persistence of manual processes
  2. Remote work environments
  3. New modes of care delivery
  4. The move towards the patient as a payer

Persistence of manual processes

  • With a long-term trend towards automation, manual processes actually remain common throughout the medical billing revenue cycle.
  • The Black Book survey found that only 20% of revenue cycle leaders have automated at least one-quarter of their operations.
  • For the healthcare professionals who have automated more than 25%, they are reported with substantial ROI, such as faster time to payment.

Remote work environments

  • Few types of research found that more than 75% of CFOs and revenue leaders have planned to make specific structural changes to their revenue cycle operations.
  • With the pandemic results, intentions to automate more functions and expand remote work to address drops in revenue and similar disruptions.
  • Outsourcing also accelerates in response to staffing issues and the need to clean up accounts receivable.

New modes of care delivery

  • Telemedicine raised in 2020 due to the pandemic like creating new medical billing codes and finding the correct codes within a legacy electronic health record (EHR) solution.
  • Insufficient integration between EHR, billing, and telehealth platforms has also led to a lot of time-consuming manual re-entry of data across systems.
  • The expensive efforts to coordinate help all of these new and updated codes, also appealing or correcting and re-billing incorrectly billed claims.

The move toward the patient as payer

  • Patient financial responsibility has increased over time. It has also created multiple challenges for healthcare organizations in generating revenue.
  • Almost three-fourths of providers say patient collections take at least a month, largely because of paper-based processes, and 88% of healthcare providers rely on them.

Automation vs. Outsourcing in Healthcare Revenue Cycle Management

  • Automation and outsourcing provide distinct solutions to the challenges.
  • For instance, automation is driven by AI, and ML can be blended with traditional RCM practices in a healthcare organization.
  • It automatically captures revenue cycle workflows directly within existing EHR and billing systems.
  • When an outlier event occurs, an expert-in-the-loop can intervene, taking care of the problem and, in turn, teaching the automation system how to handle similar future occurrences.
  • This particular approach to revenue cycle automation is robust and scalable, with the ability to work across existing applications, expand to numerous medical billing revenue cycle functions and remain resilient against procedural, technical, and regulatory changes.
  • Healthcare professionals might outsource its revenue cycle to expand the current staff’s capacity or add additional staff to learn new codes and reimbursement policies.

AI and ML drive high revenue cycle performance at a low cost. Moreover, they improve the accuracy of a revenue cycle process, like billing, and save time previously lost to manual activities. AI and ML enable uniquely proactive, predictive, and non-fragile workflows not possible through other forms of automation.

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