The Advantages of Artificial Intelligence in Healthcare and Revenue Cycle Management
Updated: Nov 10, 2022
The healthcare industry has traditionally been slow to adopt artificial intelligence (AI). Although the technology has made some inroads into clinical settings, with organizations applying the technology to improve efficiency, accuracy, and consistency, revenue cycle management has remained relatively uncharted territory for AI until now. As automation and artificial intelligence continue to transform the way we think of revenue cycle management, healthcare leaders maintain that artificial intelligence is a high priority.
The use of artificial intelligence in healthcare and revenue cycle management has gone beyond being just a buzzword, and today, it’s being used actively to improve cycle revenue outcomes and efficiency. Artificial intelligence can modernize and improve revenue cycle management by integrating these four capabilities into the workflow: predictive modeling, automated claims adjudication, real-time analytics, and robotic process automation.
Artificial intelligence can make it possible to detect coding problems or missed charges before filing claims, ensuring a more complete claim is filed and paid in a timely manner. It’s even possible to use artificial intelligence instead of rules-based methods that can be difficult to maintain and time consuming.
Today, 72% of respondents report eligibility and benefits verification and 64% report patient-payment estimation as the two most common applications of artificial intelligence in resource-constrained medical settings. By 2023, 68% expect prior authorization and 62% expect payment amount/timing estimation to emerge as leading applications.
While some revenue cycle functions have been more proactive in adopting artificial intelligence, providers anticipate a more widespread adoption of AI across all revenue cycle functions, indicating an evolution from point solutions to a strategic and holistic approach.
Within three years, the widespread adoption of artificial intelligence will require a marked change from current conditions. Currently, 36% of organizations are not using AI at all, and the maturity level of those who are using it is largely (42%) at the emerging stage. Only 12% of healthcare leaders indicate they have a fully mature program.
As in any large-scale change, there will be challenges involved in transforming the existing culture and processes, coordinating the work of multiple teams, and navigating a multifaceted implementation effort. However, with a focus on efficient and cost-effective patient care, these hurdles are manageable.
The potential for providers to use artificial intelligence (AI) is huge and will be invaluable––from improving the entire revenue cycle to better patient level-of-care prediction, clinical insights, and claims accuracy. However, it is increasingly clear that this potential can only be realized if key stakeholders become aligned on AI’s capabilities, embrace a strategic AI vision, and prioritize the most impactful use cases.
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