AI and ML can help providers manage rev cycle staffing challenges

AI and ML can help providers manage rev cycle staffing challenges

Artificial intelligence is a force multiplier for health systems and their RCM professionals, says Noel Felipe, senior vice president and revenue cycle practice leader at Firstsource.

Read on healthcareitnews.com

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The healthcare revenue cycle sector is grappling with a staffing shortage, resulting in challenges for hospitals and health systems in managing claims submissions and follow-ups. To address these issues, more providers are turning to automation, leveraging machine learning (ML) and robotic process automation (RPA) to streamline revenue cycle management (RCM) workflows and bridge critical staffing gaps.

According to Noel Felipe, senior vice president and revenue cycle practice leader at Firstsource, AI and ML serve as force multipliers for providers and their RCM professionals. Automation tools, ranging from RPA bots to generative AI, can automate tasks like eligibility verification, identify patterns in denied claims, and even summarize physician notes. However, while these tools enhance efficiency, they cannot replace human decision-making entirely. Humans must validate outputs from AI/ML tools, particularly in complex processes.

The outcomes of applying AI to RCM include reducing labor costs, increasing financial flexibility, improving work satisfaction rates, and delivering better patient experiences. By automating routine tasks, professionals have more time for patient financial counseling and managing complex claims. Additionally, AI helps streamline payment processes, providing patients with clearer estimates of their financial obligations and guiding them through payment options.

For healthcare provider organizations looking to implement AI tools in RCM, Felipe suggests starting small and ensuring tasks truly require AI rather than RPA. Understanding the complexity of decisions involved in processes helps determine the suitability of AI or ML solutions. Organizations should prioritize opportunities that enhance both employee and patient experiences, building on smaller successes to improve data accuracy and stay abreast of AI advancements within the revenue cycle.

In essence, AI and automation offer significant potential to optimize RCM workflows, improve financial experiences for patients, and enhance revenue flows for providers, provided they are implemented thoughtfully and in alignment with organizational needs and capabilities.




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