­AI-Powered Solutions for RCM now an everyday reality

There is great optimism that the AI-powered solutions for RCM can provide substantial improvements in the area of healthcare from diagnostics to treatment. It is believed that AI tools can facilitate and enhance human work and not replace the work of physicians and other healthcare staff as such.

AI is ready to support healthcare personnel with a variety of tasks from administrative workflow to clinical documentation and patient outreach as well as specialized support such as in image analysis, medical device automation, and patient monitoring.

The New Age Healthcare:

The demand for healthcare services is ever-increasing and many countries are experiencing a shortage of healthcare practitioners, especially physicians. Healthcare institutions are also fighting to keep up with all the new technological developments and the high expectations of patients.

The healthcare ecosystem is realizing the importance of AI-powered tools in the next-generation healthcare technology. It is believed that AI can bring improvements to any process within healthcare operations and Insurance facilities.

What is Revenue cycle automation for AI-powered solutions?

Revenue cycle management automation uses technology to manage the tasks and workflows involved with an organization’s revenue cycle. The revenue cycle is the financial process that allows a practice, physician, or healthcare organization to receive reimbursement for care.

RCM automation eliminates the need for manual, human-powered intervention within the revenue cycle. In other words, it offloads tedious work related to eligibility, claim submission, denials, and payments.

The Healthcare Revenue Cycle Process

The Healthcare Revenue Cycle Process

Why We Need Revenue Cycle Automation in Healthcare?

Anyone who has worked within RCM knows how tedious and time-consuming it can be. Reimbursement sounds simple on the surface, but beneath it is a behemoth of tricky coding and complex payer rules that make it challenging to get paid.

The tedious processes of RCM pinpoint major pain points our industry feels today: 

  • Provider and employee burnout
  • Lower compensation and reimbursement rates amidst rising inflation
  • Increasing patient expectations and the rise of healthcare “consumerism”

When you can automate much of the RCM workload, you can save time and eliminate many of the errors that delay reimbursement. With fewer manual RCM processes, private practices can dedicate more resources to patient care, resulting in higher patient satisfaction and better outcomes.

Employing automation within existing RCM tools reduces employee workload and eliminates the need to hire additional staff to manage the claims process.

The use of AI in contemporary Revenue Cycle Management:

AI can be applied to the revenue cycle management process in several ways: 

  • claim processing
  • rejection management
  • patient billing
  • collections

According to a study done by Change Healthcare, two-thirds of healthcare facilities and health systems are utilizing AI to help their revenue cycle. Of those, 72% of respondents said they use AI tools to verify their eligibility for benefits, and 64% said they use them to estimate payments.

AI impacts RCM in the following ways:

Claim Denial Management:

Managing denials is one of the most difficult problems that medical practices encounter. Claims can be processed and analyzed with AI substantially more quickly and accurately to eliminate problematic contradictions. They are allowing RCM to smoothen the revenue cycle. According to CMS, RCM spends an average of 45% of the time on claims-related activities, so technology can help streamline this process.

Assist in forecasting trends:

Concluding patient behavior is another way AI can optimize the revenue cycle management solution. AI can detect which patients are more likely to make on-time payments and even predict how much they will ultimately owe by analyzing enormous volumes of data and forecasting trends and patterns. This allows your practice to generate more revenue effectively.

Knowledge of Patient Financial Affairs:

AI can assist your firm in better understanding the financial circumstances in addition to accounting cash flow. Practitioners may get a clear picture of the payers available for each patient by examining data like insurance plans and payment histories, making it simpler to give them the support they require.

Improving claim submission decision-making process:

AI can strengthen the decision-making process regarding claim submissions in addition to helping to improve claims processing and decrease denials. RCM solutions can choose which claims to submit to improve their reimbursement chances by looking at patient demographics, insurance plans, and prior payment history provided through the assistance of AI.

Improve billing precision:

Medical billing could become more accurate and precise using AI. The professionals dealing with RCM can decide which services are being given and what prices should be charged for them by analyzing enormous volumes of data, enabling greater consistency and better records management. By doing so, AI technologies could make it obsolete for claims to be manually audited to ensure accuracy, saving practitioners much money.

Analytics and Reporting:

Using AI in revenue cycle management also has the benefit of generating precise and comprehensive reports. This can then be used to pinpoint problem areas and implement new procedures to increase revenue process effectiveness. Revenue cycle management solutions can boost patient care and satisfaction while also improving operational efficiency in this way.

Thus, AI plays an increasingly important role in revenue cycle management.

To optimize AI-powered solutions for RCM capture and reimbursement mechanisms to incentivize high-quality, cost-effective care delivery, while also ensuring accurate documentation, coding, and billing practices to support value-based payment models, health systems must take advantage of technology to:

  • Aggregate all available data about patients and populations
  • Analyze and apply various algorithms and AI models to the data to extract actionable insights
  • Leverage these insights to orchestrate care automation through targeted and timely outreaches and through driving action in workflows

Powered by the right technology, healthcare providers can aggregate data from multiple sources to create a comprehensive view of patients, population health, and financial performance. By integrating revenue cycle management strategies with value-based care principles, healthcare organizations can achieve financial sustainability while improving patient outcomes and overall healthcare value.

CONCLUSION

The integration of AI into Revenue Cycle Management is no longer a futuristic vision; it is an integral part of the contemporary healthcare ecosystem. As organizations continue to prioritize efficiency, accuracy, and financial optimization, AI-powered solutions will undoubtedly remain at the forefront of innovation in RCM.

Embracing these technologies is not just a choice but a necessity for healthcare providers aiming to thrive in an era of rapid technological advancement and ever-increasing demands for financial transparency and accountability.

Medical Billers and Coders (MBC) is on a mission to help private practices and health tech companies thrive by improving the reimbursement process. We use AI-powered automation to optimize the revenue cycle, minimize administrative workload, and reduce time-to-reimbursement. Learn more today with a quick intro call.