Why the Future of Healthcare Operations will be Powered by Digital RCM
Advances in automation, artificial intelligence (AI), blockchain and industry-ready cognitive capabilities have created a perfect storm that has finally reached revenue cycle management (RCM).
Stuck in technology’s Bronze Age, RCM traditionally has been defined by people-intensive, manual-heavy processes, powered by disconnected operational systems.
Digital transformation and related emerging technologies can help transform RCM, and optimize processes for healthcare providers to operate more effectively and efficiently while improving the healthcare experience for patients.
Why Change is Necessary
RCM is a critical business function that obtains reimbursements for all healthcare providers. Compared to advancements in some other critical functions, however, RCM has remained mired in manual processes that have negatively impacted the financial picture for providers. The change to the current state of RCM will be made through the adoption of digital RCM (dRCM). While dRCM is critical to long-term financial success for large and small healthcare organizations, its impact will help pave the way for years to come for both healthcare organizations and patients.
The following highlights the cost of inefficiencies and challenges caused by current-state RCM:
- $150 billion total cost to healthcare incurred due to missed appointments
- 32% of patients pay their share of the medical bill in full; this figure is expected to drop to 5%
- 60% of claim denials traced to front office inefficiencies including missing patient information
- 94% of claims are submitted manually with claim status checks taking 5-12 minutes and costing $9.79 per inquiry
- 90% of denials are preventable and it costs $25 on average to rework denied claims
- Up to 49% of patient responsibilities are written off as bad debt by hospitals
AI, blockchain and automation offer healthcare providers the opportunity to improve reimbursement and recover lost revenue while concurrently improving the patient experience. Receiving payment for healthcare is unlike any other business. In other businesses, the consumer makes a full payment for the service or product when that service is performed or the product is received.
You can’t go to Best Buy and say, “I’ll take the TV home now but I’ll pay you in 90 days, maybe.”
Powering Healthcare with Digital RCM
Moving to the dRCM world is a three-part approach that is a progression from simpler to more sophisticated technology solutions ensures long-term success for provider operations. It’s perfectly acceptable to start dRCM with small steps. Build on what exists, leverage existing data and then improve and add more complex technology over time.
Here is a technology glide-path to the new world:
- Systems-that-Do: Capabilities focused on the elimination of manual execution of routine tasks by automation. Examples include robotic process automation, also known as RPA, for, consumer-driven information capture, RCM operations including eligibility verification, claim status checking.
- Systems-that-Act: Solutions with higher cognitive components driven by data science and predictive analytics, which have the ability to make decisions beyond plain rules-based logic. These systems also can be the basis for blockchain-based solutions.
- Systems-that-Think: Digital technology that adapts its behavior based on insights captured directly from data (without human intervention), with continuous learning that leads to new knowledge and insights. These capabilities are driven by advanced cognitive technologies like natural language processing, AI and machine learning.
Ready, Set, Go to Digital RCM
Every healthcare organization is at a different stage of the dRCM transformation. No matter where an organization is on the timeline, the change will take commitment, time, effort, and human and financial resources.
The process and transformation can be daunting and is certainly a complicated undertaking. Based on our experience, we’ve developed a handful of suggestions to improve the chances of a successful shift to dRCM:
- Take small steps, but start making the change now to improve RCM operations via dRCM.
- Start with existing data and keep adding data from outcomes to improve learning in AI solutions.
- Begin the transformation based on Systems-that-Do and use what’s learned to progress toward the more technologically complex Systems-that-Act and then Systems-that-Think.
No matter the size of the organization, transforming legacy RCM operations to the machine-driven, human-augmented dRCM paradigm is no longer a matter of if, but when. And “when” is now.