Healthcare providers in the United States struggle with the resource-intensive and time-consuming nature of Revenue Cycle Management (RCM). Streamlining RCM is crucial for freeing up staff hours to focus on providing quality healthcare services to patients. Although manual management of RCM is possible, it can quickly overwhelm staff and lead to burnout. Adopting automated solutions to simplify the process and improve staff efficiency is imperative in this context. This blog will explore the benefits of automation in RCM and provide insights to overcome potential challenges.
Revenue Cycle Management Challenges
The revenue cycle is a significant challenge for healthcare providers and payers due to slow and inefficient processes that negatively impact productivity, cash flow, and patient experience. Patients have long been frustrated with the revenue cycle, billing errors, coding errors, and delayed authorizations leading to a perception of inefficiency. Unpaid claims and unprecedented claim denials further compound these issues. To address these challenges, healthcare organizations must adopt automation and implement measures to improve efficiency. Furthermore, adopting automation can help healthcare organizations streamline their revenue cycles and enhance the patient experience while reducing billing errors and delays.
Although new reimbursement models are on the horizon, most commercial healthcare organizations in the U.S. continue to depend mainly on fee-for-service methods. Providers and payers will continue to prioritize the optimization of the revenue cycle in the foreseeable future. To maintain financial stability and patient satisfaction, healthcare organizations must continue to improve their revenue cycle management through automation and other measures.
Revenue Cycle Management Automation
Revenue cycle management automation refers to using technology to streamline and optimize the workflow in healthcare organizations. This process can enhance revenue, boost the organization’s competitive advantage, and improve workflow. Intelligent automation (IA) is an advanced automation technology that involves the use of robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML). RPA is a key component of IA and is used to simplify processes by automating manual tasks such as accounts receivable, insurance verification, and data entry. Digital workers are deployed to perform these repetitive tasks in real-time, allowing employees more time to focus on patient-centered work. By combining RPA with AI and ML, IA offers even greater automation capabilities, enabling organizations to optimize their revenue cycle management processes further.
Intelligent automation (IA)
Intelligent automation (IA) combines artificial intelligence and robotic process automation to expand automation capabilities. Using IA, digital workers can integrate with cognitive technologies like computer vision, natural language processing (NLP), and machine learning (ML) to automate more semi-structured and unstructured processes. This includes financial invoice processing, claim denial management, and email triage. Integrating AI with RPA offers advanced automation capabilities that can significantly improve the efficiency and accuracy of revenue cycle management processes.
Robotic Process Automation (RPA)
Robotic process automation allows digital workers to perform step-by-step tasks and processes within existing applications and systems, replicating human actions. RPA technology enables digital workers to leverage advanced cognitive automation capabilities with minimal human intervention. This automation technology enables healthcare organizations to reduce costs and enhance patient satisfaction.
Artificial Intelligence
Artificial Intelligence (AI) involves the development of machines capable of carrying out tasks that would normally necessitate human intelligence. It refers to the simulation of intelligent human behavior in computers, allowing businesses to analyze and categorize data and improve automated business processes when coupled with RPA.
Machine Learning
Machine learning (ML) allows computers or systems to enhance their performance by continually integrating new data into an existing statistical model, leading to improved learning and better outcomes over time. It also enables the development of new behaviors based on experience. This technology is beneficial for improving the accuracy of automated processes and decision-making by using past data to predict future outcomes.
How Automation Empowers Efficient Revenue Cycle Management
Efficient revenue cycle management (RCM) is crucial to ensure adequate oversight, control, and allocation of resources. It helps to increase operational efficiency, reduce waste of resources, mitigate excess costs, and improve patient engagement.
By automating the RCM process, healthcare organizations can streamline workflow, minimize manual errors, and allocate more time to patient-focused work. This leads to a more agile organization that efficiently allocates resources where they matter most, ultimately improving patient outcomes. Explore the significant advantages of revenue cycle management (RCM) in healthcare and its support towards positive changes for providers.
Improve First-Pass Payment Rate
Improved first-pass payment rate is a critical benefit of revenue cycle management in healthcare. When claims are approved on the first attempt, staff does not have to follow up to correct errors or add the missing information. To achieve a high first-pass payment rate, healthcare providers need a revenue cycle management solution that prioritizes consistency and relies on robust automation. However, an improved first-pass payment rate is essential for more informed and successful operations.
AI and ML-based automation tailored for healthcare revenue cycle management are vital for claims submission, preparation, and management. AI can handle tasks that typically demand human intelligence, such as collecting patient information and claim status management. ML allows the solution to learn, adapt and enhance with minimal human intervention, improving the efficiency of the claims process.
Increase Process Efficiency
Automation is crucial to efficient revenue cycle management processes, providing reliability, effectiveness, and adaptability. AI and ML-powered automation can be applied to every aspect of the revenue cycle, from patient engagement to addressing claim denials.
The benefits of automation can be broadly categorized into two groups:
More reliable processes: AI and ML provide a higher level of dependability than humans, with the ability to repeat tasks without error and adjust strategies with minimal human intervention.
Reduced opportunity for human error: Automated RCM solutions significantly reduce the risk of errors caused by human oversight, even from the most skilled and attentive employees.
Increase Staff Efficiency
Automation in revenue cycle management allows staff to focus on critical and timely issues. Repetitive yet essential tasks are handled by automation, freeing up staff to use their talents and experience more effectively. Staff members can apply their abilities, such as critical thinking and complex interpersonal communication, to add value to the organization. This increases staff efficiency and productivity, improving provider and patient outcomes.
Providers understand the importance of human involvement in certain aspects of the revenue cycle management process. In complex billing issues, a human touch can provide crucial assistance in resolving the issue. Interactions with patients about payments can also benefit from a more personalized, person-to-person approach instead of a fully automated process. Implementing an effective RCM solution empowers team and department leaders to assign their staff the most critical and time-sensitive issues, freeing up valuable time and resources for the most important tasks.
Denial Management
As per an American Hospital Association survey spanning from 2016 to 2020, claim denial rates have been increasing for 89% of hospitals, making it crucial to have an adequate response for handling denied claims. Denial management is essential for collecting more revenue for healthcare organizations and helping patients navigate the complicated world of insurance eligibility. According to the AHA, a significant factor in the rise of claim denials is issued with prior authorization.
It is important to submit complete and accurate information as part of the initial claim and carefully review denials and their reasoning supplied by payers. Performing a root analysis can help identify the underlying issues and prevent future denials. It can also predict denials, making them crucial to effective denial management. Making necessary adjustments before submitting the claim can lead to a shorter timeline for payment and resolution.
An Optimized Revenue
Optimizing the healthcare revenue cycle through automation offers several benefits to both providers and patients. A comprehensive automation strategy is more effective than automating just a few processes. The type of automation used is crucial to success. RPA offers a rule-based approach to tasks, but it requires significant scripting and maintenance work and is less reliable than AI and ML. RPA is suitable for specific administrative tasks, but other techniques may be necessary for more complex tasks.
Automating all significant aspects of the revenue cycle can increase process efficiencies and reduce waste. Purpose-built and dependable automation can provide adaptability to changing workflows on the payer and provider sides. Analytics generated from automation can lead to strategic course corrections and leaner processes over time. Optimizing revenue cycle management can result in more claim approvals, fewer denials, and faster timelines for crucial functions. The result is a broadly effective revenue cycle management system that supports improvements in cash flow.
Robotic Process Automation in Revenue Cycle Management
Automation using RPA in revenue cycle management can provide a wide range of benefits to various stakeholders in the healthcare organization, including patients, providers, and accounts receivable departments. It can help improve the efficiency of processes, reduce errors, and speed up reimbursements.
Examples of RPA in RCM
Submitting Claims: RPA can automate claims processing, which can help optimize throughput, and payer communications and provide easier access to claims status updates, follow-ups, and reimbursements.
Back-Office: RPA bots can be deployed across back-office functions such as processing plan enrollments, determining eligibility, and filing expense reports.
Finance & Accounting: RPA can streamline manual data entry for accounts payable and accounts receivable transactions, payments, billing, and reimbursements.
Hospital Records: Automation can extract and process data to speed up new patient appointment requests and patient enrollments.
Intelligent automation and RPA are poised to revolutionize the healthcare industry by streamlining revenue cycle management processes. Additionally, RPA can help maintain HIPAA compliance and boost revenue.
Conclusion
Automating revenue cycle management processes enables healthcare providers to cut costs by reducing manual labor, ultimately boosting their profits. Providers can also save money in the long run by reducing their reliance on costly third-party billing services through automation. Healthcare providers can improve accuracy and expedite their revenue cycle by implementing automation software. It can also enhance patient satisfaction and make a savvy business decision that positively impacts their financial performance. Automation provides flexibility and scalability, enabling organizations to increase efficiency, improve output quality, reduce processing costs, and enhance the patient experience.
