Collecting payments in the healthcare industry is not as simple as sending invoices and processing payments. Healthcare providers have to determine who owes the money, insurance eligibility, and document verification before any transaction is made.

And the most common billing problems in the healthcare industry occur due to manual errors in data entry and management. And if stuck with an ad-hoc manual approach, healthcare staff might get too bogged down to improve patient care. In order to increase revenue and focus on value-based patient care, healthcare providers must have effective healthcare revenue management.

Healthcare Revenue Cycle Management(RCM) Challenges

What are Healthcare Revenue Cycle Management Challenges?

Healthcare revenue cycle management involves multiple back and front office activities and data sharing among three stakeholders: patients, providers, and payers. And when healthcare providers have to maintain the revenue cycle management activity manually, this whole process becomes resource-intensive and time-consuming. There are several stages in revenue cycle management that poses a range of challenges for effective revenue management. These challenges are-

  • Interoperability

    With a large amount of data involved in the healthcare process, there is an urgent need to share that information all across the department efficiently. Inadequate implementation and integration of health records, medical images, billing and claims cycles, and other data exchanges can negatively impact patient care. In addition, keeping track of these records manually is extremely time-consuming and expensive for healthcare providers.

  • Erroneous Medical Billing

    Healthcare providers need data related to claims, patient registration bills, medical bills, and others to manage their revenue cycle effectively. With the large number of documents involved in integrating data into healthcare systems, healthcare staff often find it tough to maintain data processing errorless. Hence with wrong medical billing and erroneous data, there is a chance of a long time resolution between billing and payment that impacts the healthcare revenue cycle.

  • Maintaining Regulatory Compliance

    New regulations and compliance standards are constant in healthcare, and maintaining them is vital for healthcare providers. Failing to be updated with the evolving compliance landscape can lead to claim denials, payment delays, and appointment and billing backlogs that directly impact the revenue cycle.

  • Lack of Data-Driven Insights

    Multiple data points are available at various stages of healthcare revenue management. And gaining efficiencies in healthcare revenue cycle management requires a big picture behind these data points that showcase what is happening inside the enterprise. Lack of these data-driven insights is not always by default in the healthcare system, and in the absence of these insights, it is tough to check where the scope of improvement in the healthcare life cycle is.

  • Security Management

    With a large amount of data shared all across the healthcare staff, physicians and IT service providers, the chances of data branches and identity thefts might delay the insurance claims process and payment initiation. And this friction hampers the healthcare revenue cycle management and creates more challenges.

    [Also Read:What is Robotic Process Automation (RPA) in Healthcare? Use Cases, Benefits, and Challenges in 2023]

Healthcare Revenue Cycle Management(RCM) Automation With RPA and AI

As per Grand View Research, the global market for revenue cycle management is projected to expand at a compound annual growth rate of 11.6% from 2022-2030. Considering the amount of increment in revenue cycle management, demand for a technology solution like AI and RPA in healthcare is also accelerating. Some reports stated that AI in healthcare is expected to expand at an annual growth rate of 38.4% from 2022-2020. As healthcare revenue management involves multiple steps, leveraging AI and automation solutions can help drive better revenue management.

In simple words, the RCM process begins with patient appointments and ends when full payment is initiated in the provider’s account. Between these two points occur five important steps that complete the whole revenue cycle. Automating these steps and processes with RPA and AI can help create better revenue management systems. These five steps are–

  • Insurance Eligibility Verification

    Before seeing a patient, healthcare providers often check the insurance eligibility to verify whether the patient is able to fill the claims or not. Verifying the information provided by each patient and manually checking data can take minutes to an hour and a week which hinders the organization’s referral rate. Utilizing RPA bots can help healthcare organizations get rid of the tedious task of following the paper trail. AI-driven bots can access the data faster using OCR and machine learning capabilities and make the data extraction for verification an easy task.

  • Medical Coding and Claims Preparation

    The medical codes are reports from physicians, which can include diagnostics, treatments, or surgery performed by the healthcare provider. In a field reliant on accurate data, medical coding is vital for insurance claims and other processes to maintain the revenue cycle. And collecting codes from multiple physicians and integrating them into the healthcare systems is an uphill task. But, RPA bots can help healthcare providers’ data integration all across the healthcare system be better and more efficient. Automation cuts down the time and effort used in integrating medical codes and preparing claims. With faster data access, claim preparation gets better with less manual effort and time.

  • Claims Submission

    Healthcare providers share insurance claims with insurance providers through portals. With a large number of healthcare portals, the data integration for multiple systems is a tedious process. To wipe out these challenges, automation and AI are the solutions to drive process efficiency. RPA bots can easily operate through as many interfaces and help healthcare providers submit faster claims.

  • Dispute Management

    Insurers don’t agree with every claim processed by healthcare providers. They may reject claims outright and delay the payment process, which directly affects patient care. Also, keeping an eye on every piece of data to recheck claims from insurers and effectively resolve the dispute requires a talent pool of employees for faster resolution and payment. Using RPA bots with a predefined set of rules can escalate these exceptions for human staff and enhance employee productivity for faster resolution and payment.

  • Claims Reconciliation

    Once insurers receive the claims and verify the information and transfer the funds directly to healthcare providers’ accounts, it is the healthcare staff’s responsibility to reconcile the payment information in their financial system. Aggregating this large volume of information and reconciling it to the system is a challenging process for employees. AI chatbots can easily track the data shared by insurers and integrate this information directly into the system autonomously.


To make sure that patients are getting excellent patient care along with faster reimbursement for their services, healthcare providers must turn to AI and automation solutions for better revenue cycle management. AI and automation enable healthcare providers to offer excellent patient care beyond costs and facilitate healthcare experience for patients, healthcare providers and physicians. That’s the power of RPA and AI.

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