Generative AI Appeals to Healthcare Orgs for Revenue Cycle Operations
Nearly 60 percent of surveyed healthcare organizations are considering using generative AI for revenue cycle operations.
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- Financial leaders at healthcare organizations are interested in using generative artificial intelligence (AI) to streamline revenue cycle operations, according to a survey from AKASA.
The survey reflects responses from more than 250 chief financial officers (CFOs) and financial leaders at health systems and hospitals nationwide.
More than 70 percent of respondents are actively considering the use of generative AI, the results indicated. Nearly 60 percent of financial leaders are considering using this technology for revenue cycle operations.
Almost a quarter (23 percent) are interested in using generative AI in clinical documentation, 18 percent are considering using it in other functions, and 13 percent are thinking about using it in clinical care. Meanwhile, 30 percent of respondents are not actively considering using generative AI.
Generative AI is artificial intelligence technology that can produce text, imagery, audio, and synthetic data. In healthcare, generative AI can make sense of complex clinical documents, extract information from documents, and use the data across revenue cycle operations.
As healthcare organizations face financial challenges, staffing shortages, and growing patient volumes, leveraging generative AI for revenue cycle tasks may help reduce administrative burden and improve efficiency. In addition, using AI for these operations would not pose a direct risk to patient health.
Healthcare organizations have used generative AI to generate appeal letters after a claim denial from a payer and to streamline the prior authorization process. Revenue cycle leaders can also use generative AI to improve front-end processes, such as assisting with data validation and scrubbing.
Despite the recent boom of AI and the benefits it can generate for the healthcare industry, healthcare organizations and providers still face barriers to AI adoption in revenue cycle management.
For example, it may be difficult to integrate AI with existing IT systems like EHRs. Additionally, providers may be skeptical of the technologies or be concerned about job losses due to AI.
Aside from revenue cycle management, healthcare stakeholders have been using generative AI as diagnostic tools. One study found that ChatGPT, a large language model (LLM), was able to generate diagnoses when provided with complex patient cases and corresponding clinical data.
Data from Deloitte also found that consumers believe that generative AI may help reduce healthcare costs and improve access to care.
