John Hataway | Senior Director - Continuous Improvement & Automation
The healthcare revenue cycle historically, and in all too many cases presently, has relied heavily on manual processes and paper-based systems. This is a labor-intensive, time-consuming method prone to errors. Gradually, we’ve seen digitalization such as electronic health records and billing software systems, significantly improve efficiency and accuracy via standardization and improved integrations and information sharing.
Today, we stand on the cusp of a new era where advanced technologies, capable of moving beyond efficient movement and storage of data to synthesis of the information contained within, are becoming real and practical for use within the Revenue Cycle environment. These technologies, like AI, blockchain, and predictive analytics are not just concepts, but realities shaping the future of the healthcare revenue cycle. But, as with all transitions, this one requires thoughtful planning, adoption, and iterative learning.
Differentiating Emerging Technologies
Understanding the categories and capabilities of emerging technologies is critical in identifying the best way(s) to leverage them in optimizing processes within the revenue cycle:
Artificial Intelligence (AI) is the capability for a computer to synthesize data in a way analogous to a human. Capabilities (and notoriety) in this area have increased dramatically within recent years. However, AI is a broad concept and contains a number of components:
- Machine Learning (ML) allows us to leverage the vast amounts of data generated within our hospitals to enhance our decision-making process. By using ML, we can create more accurate patient segments based on their health profiles and history, leading to more accurate and efficient billing. ML can also enhance the coding process, minimizing errors that lead to claim denials.
- Natural Language Processing (NLP) enables more efficient interactions with AI-enhanced systems by allowing humans to use normal language syntax to make requests; this capability also facilitates the creation of human-readable outputs by these systems. For example, through automated transcription of medical records and extraction of key information from clinical notes, NLP is able to enhance the accuracy of coding and billing, easing the burden on healthcare providers and allowing them to spend more time on patient care.
Predictive Analytics is pivotal for future planning. It allows us to anticipate key events and outcomes based on current status: patient payment behavior, denial propensity, expected volumes, etc. This capability allows for proactive measures and aids in determining better allocation of resources to maximize revenue and minimize waste.
Blockchain Technology introduces an unparalleled level of transparency and security. By using smart contracts to automate billing, Blockchain hastens revenue recognition and provides an immutable record, thus reducing the potential for fraud.
Automation, particularly robotic process automation, serves as the foundational layer that enhances efficiency across these and other technologies. It streamlines routine tasks such as checking insurance eligibility and scheduling appointments by connecting disparate systems and triggering required next steps, thereby minimizing human error and freeing up staff to focus on more complex tasks. As such, Automation is essential for maximizing the benefits derived from each of these emerging technology platforms.
