AI Changes Everything In Revenue Cycle Management

Artificial Intelligence (AI) is tackling some of the most pressing issues in revenue cycle management, resulting in higher revenue capture and claims for early adopters. The revenue cycle management (RCM) is a process that leads to the generation of revenue. These processes take place at all stages from pre-billing to collections. The artificial intelligence helps improve the revenue cycle management (RCM)  process by reducing the claims denial rates and increasing collection rates, thus overcoming some of the key challenges in the manual process. Artificial intelligence is the ability of computers to replicate intellectual process characteristics of humans, such as the ability to reason, discern meaning, generalize, and learn at an extremely fast pace from past experience.

What is Revenue Cycle Management?

Countless healthcare practices have suffered from a failing revenue cycle management (RCM) process, but the advert of new technologies such as artificial intelligence and machine learning allows for superior analytics and smarter collection methods. Revenue cycle management (RCM) has evolved to be about for more than just collections.

Revenue cycle management (RCM) is the process of discovering, collecting, and managing revenue from payers based on the services given by the practice. Revenue cycle management (RCM) supports a successful financial survival and capacity to keep delivering great healthcare to its patients. As healthcare has shifted toward value-based compensation and more holistic patient care., providers have been compelled to reconsider their approach to RCM.

Poor billing methods can lead to financial losses and jeopardize the capacity to provide quality care. Efforts to strengthen and streamline fundamental operating operations can assist providers with remaining financially  viable. Revenue cycle management (RCM) benefits medical facilities through increased collection rates, which can help them remain financially viable. Revenue cycle management (RCM) is a system that allows healthcare businesses to identify, collect, track, and process revenue generated by their services.

How Artificial Intelligence Can Modernize Your Revenue Cycle Management

Medical collections had benefitted from revenue cycle management (RCM). AI has brought ideas and solutions to process problems, resulting in improved revenue. With over 80% of medical clinic bills containing errors, AI has proven to be a game changer in revenue cycle management (RCM).

Healthcare companies continue to struggle with collections despite having sophisticated revenue cycle management and RCM tools. Revenue cycle management (RCM) is the process of managing a hospital's or medical clinic's billing operations, accounts receivable and cash flow. Revenue cycle management (RCM) has become more complex with rising patient financial responsibility, intricate payer contracts, and the transition to value-based payments. Yet, healthcare companies continue to struggle with manual collection methods.

1. Claim Denials

A claims life-cycle artificial intelligence system captures a detailed patient information picture that can be used to identify trouble claims. Revenue cycle managers can then proactively identify those risk factors in order to develop a more focused denial management approach.  

According to a study conducted by Becker's Healthcare, revealed that hospitals lose $260 Billion each year due to insurance denials.One area where artificial intelligence could have an impact on the revenue cycle is in predicting denials. Changing payer guidelines, human error, and other factors contribute to high claim denial rates for hospitals and other provider organizations. Reworking claims is costly, and every claim that is rejected or denied introduces the risk of a hospital not getting paid. Its clear that forecasting is not just about identifying what to do next- it's more important to understand why we aren't doing it already.

       2. Predicting and minimizing claim denials.

Using artificial intelligence, hospitals and health systems uncover trends in denial rates. This enables them to identify problems before claims are submitted, leading to lower denial rates and higher revenue.

       3. Cutting cost to collect

Using artificial intelligence and automation also presents an opportunity for hospitals and health systems to cut costs by streamlining and optimizing manual process while also improving the overall quality of patient care. Crowe predicts the cost to collect at healthcare organizations will decrease between 25% and 50% over the next 5-10 years, based on the number of revenue cycle positions that could potentially performed by AI and automation.

In conclusion, outsourcing to AI healthcare firms like Jorie Healthcare Partners, can fix the majority of these problems and ultimately enhance revenue paybacks. Through outsourcing to AI healthcare firms, hospitals and medical clinics have access to cutting-edge artificial intelligence technology to address some of the revenue cycle's most pressing issues while maximizing revenue integrity.

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