As providers continue to face new and unexpected challenges navigating modern healthcare, there are critical tools they can leverage to overcome obstacles and thrive. One of the most significant recent solutions revolutionizing healthcare is predictive analytics.
Predictive analytics is crucial for helping healthcare providers (HCPs) eliminate errors, optimize processes, and prepare for changes. It is arguably one of the most effective tools transforming the future of healthcare revenue cycle management (RCM). Read on to learn more about predictive analytics, how it’s benefiting HCPs today, and tips for successfully implementing it for your organization.
Predictive Analytics Defined
According to Deloitte, predictive analytics leverages data mining, statistics, modeling, artificial intelligence, and machine learning to analyze historical and real-time data to make predictions. This information allows organizations to look beyond what has happened to provide the best assessment of what will happen.
Predictive analytics has been increasingly leveraged across various sectors, and healthcare is no exception. It transforms how providers approach RCM to manage administrative and clinical functions associated with claims processing, payment, and revenue generation.
Cutting-edge techniques like predictive analytics are critical for organizations looking to get a detailed understanding of their data. They can use this information to fine-tune their revenue streams, manage costs, and improve patient satisfaction. Plus, these methods promote the “democratization of data,” allowing users to access and interpret data through advanced intelligence tools independently. This means that data is no longer in the hands of a select few but can be used by many in the organization to make informed decisions.
Potential Benefits of Predictive Analytics
With the variety of advantages that predictive analytics offers healthcare providers, it’s unsurprising that many are adopting it to improve their RCM. Some of the most significant benefits include:
Find Revenue Cycle Process Errors
By implementing predictive analytics tools, organizations identify errors in their revenue cycle process. By using advanced algorithms to analyze historical data, predictive analytics allows HCPs to detect patterns and inconsistencies that may indicate an underlying problem. These could be billing errors, missed steps in the claims process, or inefficiencies causing delays.
By identifying these errors, HCPs can take corrective actions to improve the accuracy and efficiency of their revenue cycle management. This is especially important as many organizations struggle with keeping their RCM departments staffed: 90% of surveyed executives said they were experiencing shortages. Automation tools, like predictive analytics, are critical for HCPs to remain efficient and beat these shortages.
Review Insurer Payment Behavior
Predictive analytics study more than just the organizations themselves. It can also provide valuable insights into the behavior of payers, including patterns in payment times, rates of claim approval or denial, and tendencies toward certain medical billing codes or treatments. By understanding these behaviors, HCPs can better tailor their billing and claims submissions to maximize acceptance rates and expedite payments. This understanding is especially important as payer denials become more common: research shows that denials have increased over the past three years.
Eliminate Denials
Claims denials put a significant drain on organizations’ resources and have serious impacts on cash flow. In the same survey above, 48% of leaders mentioned experiencing increased errors due to inexperienced staff for reimbursement, coding, and claims.
Predictive analytics is vital in eliminating denials by identifying the common reasons for claim rejections, including errors in coding, missing information, or non-compliance with insurer-specific submission rules. Once these issues are identified, HCPs can address them proactively, reducing the likelihood of future denials.
Get Ahead of Payer Changes
Insurer policies and reimbursement rules change frequently. It is challenging for organizations to keep up. For example, changes in 2021 CPT® E/M guidelines resulted in 20% of under-coded medical records. However, predictive analytics can help healthcare providers stay ahead of these changes. By analyzing trends and patterns in payer behavior and policy adjustments, predictive analytics can help predict potential changes, giving HCPs the time to adjust their processes.
Best Practices for Implementing Predictive Analytics
Implementing predictive analytics to enhance RCM processes is transformative but requires careful planning and consideration. Here are some best practices to make integrating it a success.
Assess Readiness. Before jumping into predictive analytics, assess your organizational readiness by evaluating your current technology infrastructure, data management systems, and human resources.
Define Clear Objectives. Have clear objectives about what you want to achieve with predictive analytics. Whether improving operational efficiency, reducing costs, or improving the patient experience, a clear vision will guide your implementation strategy.
Involve Key Stakeholders. From clinicians to administrative staff, involve all key stakeholders in the process. At a minimum, conduct training sessions to help them understand the benefits and use of predictive analytics.
Partner with Experts. If you lack in-house expertise, consider partnering with a reliable third-party vendor specializing in healthcare predictive analytics. They will guide you through the process and provide continued support to ensure your investment in predictive analytics is successful.
Start Small and Scale. Consider starting with a small, manageable project to test the waters. Once you’ve gained experience and seen the benefits firsthand, you can increase your efforts.
Review and adjust. Once you’ve implemented predictive analytics, continually monitor its performance. Be prepared to make adjustments as needed to optimize results.
Focus on Actionable Insights. The goal of predictive analytics is to provide actionable insights. Ensure your efforts are geared towards translating your analytics results into concrete actions that improve your healthcare delivery.
Technology evolves rapidly, so staying current is crucial to maximizing its potential. Continually update your knowledge about the latest advancements in predictive analytics and how they might be relevant to your organization.
Embracing the Future with Predictive Analytics
As providers face several challenges with labor shortages and increasing denials, adopting automation and tools like predictive analytics is crucial. From identifying process errors, reviewing insurer payment behaviors, eliminating denials, and preemptively adapting to payer changes, predictive analytics is the future of RCM.
With thoughtful and strategic implementation, predictive analytics enhance the efficiency, accuracy, and financial health of healthcare RCM, ultimately leading to improved patient care and satisfaction. As technology continues to advance, the role of predictive analytics in RCM is set to become even more pivotal, indeed heralding it as the future of healthcare revenue management. Harness the power of predictive analytics with GeBBS Healthcare Solutions’ iCodeWorkflow and iCode Assurance. These advanced tools leverage sophisticated algorithms to improve the accuracy and efficiency of your coding and concurrent auditing processes. Whether you want to eliminate coding errors, enhance compliance, or simply streamline your revenue cycle management, GeBBS has the solution you need. If you’re ready to embrace the future of RCM, we can help. Contact us today at gebbs.com to see how the latest technology can help you thrive in modern healthcare.
