Healthcare Leader’s Survey Reveals How AI Will Transform Healthcare Revenue Cycle in The Next Three Years
The advent of Artificial Intelligence (AI) is poised to bring about a profound transformation in the healthcare landscape. It promises to revolutionize the way doctors, hospitals, and healthcare systems approach the identification, collection, and management of their revenue cycle. By harnessing the power of AI, healthcare organizations can expect a fundamental shift in their operations, enabling them to optimize processes, enhance efficiency, and unlock new possibilities in revenue cycle management. AI’s potential impact on healthcare is vast, and its implementation is set to reshape the industry in unprecedented ways. As healthcare organizations transition from isolated, fragmented systems to integrated, end-to-end solutions, the next three years promise a significant shift in the industry.
Historically, healthcare has lagged behind other sectors in embracing AI. While AI has found its place in clinical settings, enhancing efficiency, accuracy, and consistency, it has yet to fully penetrate the revenue cycle. However, this is about to change.
From a healthcare-business perspective, the adoption of AI in revenue cycle management (RCM) makes perfect sense. The potential for AI to revolutionize RCM is limitless. By eliminating administrative waste caused by inefficient practices, enhancing decision support, and improving patient engagement, AI can optimize the entire revenue cycle, improve patient access, streamline the claims life cycle, facilitate capacity planning, and much more.
But how is AI currently being utilized? Who are the early adopters? And where is the market heading? To answer these questions and shed light on the transformative power of AI, a comprehensive survey was conducted, polling around 200 revenue cycle, IT, finance, and C-suite decision-makers. The survey aimed to gauge their understanding and familiarity with AI, identify areas for improvement, and explore the current and future utilization of the technology.
Healthcare Leader’s Survey Reveals How AI Will Transform Healthcare Revenue Cycle in The Next Three Years
The survey revealed that hospitals and health systems are on the cusp of a substantial transformation, actively seeking ways to leverage AI in addressing complex business challenges. Two-thirds of hospital and health-system executives reported utilizing AI in some capacity within their revenue cycle, with nearly all respondents expecting widespread AI adoption within the next three years. However, there remains a significant disparity in knowledge and appreciation for AI’s value among executive management, IT personnel, and revenue cycle leadership, posing obstacles to widespread adoption.
AI is gradually making inroads into RCM. The study found that almost all U.S. hospitals (98%) plan to implement AI pervasively across the revenue cycle within the next three years. While two-thirds of respondents (65%) currently employ AI in RCM, its application remains limited and rarely extends across the entire revenue cycle.
Are Healthcare Leaders Aware of Implementing AI in Healthcare RCM?
Despite the progress made, stark differences in opinions hinder healthcare organizations from fully capitalizing on the transformative potential of AI. Usage of AI in RCM is significantly higher among revenue cycle professionals (89%) compared to IT personnel (63%) and non-technical executives (48%). This discrepancy could be attributed to the survey’s broad definition of AI or revenue cycle leaders’ hands-on awareness of the specific technology employed in their departments. Additionally, the maturity of AI applications in RCM is accelerating, with 35% of respondents expecting their AI implementations to reach the “early mainstream/fully mature” stage in 2023, compared to the current 12%.
Healthcare leaders are unmistakably moving towards AI adoption. A staggering 81% of participants undertook a comprehensive technology evaluation within the last two years, actively assessing AI technology providers, solutions, and software systems specifically designed to enhance revenue cycle management (RCM) processes. This signifies a significant commitment from organizations to explore and embrace innovative AI solutions that can drive improvements in their RCM operations. By actively seeking out AI technologies, healthcare entities demonstrate their dedication to staying at the forefront of technological advancements and maximizing the potential of AI in enhancing RCM performance.
Return of Investments and Implementation Satisfaction of AI in Healthcare RCM
Presently, the most common applications of AI in RCM are eligibility and benefits verification (72%) and patient payment estimation (64%). Looking ahead to 2023, respondents anticipate prior authorization (68%) and payment amount/timing estimation (62%) to emerge as leading AI applications.
While these areas receive considerable attention, providers expect a widespread increase in AI utilization across various revenue cycle functions, signaling a shift from fragmented solutions to a comprehensive and strategic approach. Although AI already drives many improvements, its adoption remains tactical rather than holistic. The survey respondents highlighted driving patient and payer payments (83%) and optimizing cash flow (80%) as the most significant benefits of AI implementation in the revenue cycle.
Although eligibility and benefits verification (71%) and patient payment estimation (62%) will remain prominent areas for AI integration, there is a growing expectation of significant AI utilization in other critical functions. These functions, which play a vital role in revenue cycle management, are anticipated to experience substantial growth in their adoption of AI. This trend reflects the recognition of AI’s potential to address various challenges and optimize processes across the entire revenue cycle. As healthcare organizations expand their AI capabilities, they are poised to unlock further efficiencies and improvements in areas beyond eligibility and payment estimation.
For instance, prior authorization is anticipated to witness a 24 percentage-point increase, while payment amount/time estimation and denials prevention are expected to see an 18 percentage-point increase. AI solutions hold promise in addressing existing RCM pain points such as cost-to-collect, accounts receivable, underpayments, as well as challenges related to accounts receivable management and staffing.
The widespread adoption of AI within three years requires a significant departure from the current state. At present, a significant 36% of organizations have not yet adopted AI, while the maturity level of those organizations utilizing AI is predominantly in the emerging stage (42%). Only a small fraction, approximately 12% of healthcare leaders indicate a fully mature program.
Several barriers hinder the widespread adoption of AI, including financial constraints, security risks, and privacy concerns. Budgetary concerns are the primary obstacles cited by 76% of non-technical executives, hindering both initial AI implementation and full integration. Liability, risk, and privacy concerns are reported by a majority of providers (56%), while staffing challenges (50%), lack of trust in provided information (45%), and infrastructure limitations (43%) are also significant hurdles. From a technical perspective, liability and security risks are the most prominent concerns (61%). A clear demonstration of ROI will be essential to overcome these doubts and promote greater adoption.
Conclusion
A strategic approach is crucial to overcome the challenges associated with implementing AI and ensure its successful integration. By establishing an AI platform and embracing AI holistically, rather than adopting a piecemeal approach, healthcare organizations can unleash the full potential of AI across the revenue cycle and achieve what was previously considered impossible. Collaboration, alignment, and prioritization of impactful use cases among key stakeholders will be essential in realizing the promise of AI in healthcare.
In conclusion, AI is poised to revolutionize revenue cycle management in healthcare. With its ability to optimize processes, improve patient access, and guide decision-making, AI offers tremendous opportunities. However, its adoption requires overcoming barriers, aligning stakeholders, and adopting a strategic mindset. By doing so, healthcare organizations can unlock the full potential of AI, transforming the revenue cycle and paving the way for more efficient, cost-effective, and patient-centered care.
