Alpha Health: Using machine learning to create fully autonomous revenue cycle operations
How do you help healthcare organizations?
In the U.S., the complexity of healthcare reimbursement drives up the hidden costs that affect what every consumer pays and erodes the trust people have in the healthcare system. At Alpha Health, our mission is to remedy the financial complexity crippling U.S. healthcare with a new approach called Unified Automation. This provides health systems with a single solution that uses machine learning to improve the efficiency, accuracy and scalability of revenue cycle management. Ultimately, our solution helps hospitals and health systems increase productivity and reduce waste while decreasing cost-of-care, allowing them to become better stewards of the healthcare dollar.
What are some of the biggest challenges you see affecting healthcare organizations?
I would say the challenges fall into two main categories. The first pertains to the traditional hurdles healthcare organizations have faced, including how to manage an efficient revenue cycle and provide a positive patient financial experience while navigating an overly complex reimbursement environment. The other category relates to the trials and tribulations that have emerged due to the COVID-19 crisis. Health systems across the country have seen significant decreases in the number of elective procedures and patient volumes. Eventually those procedures and volumes are going to return, and when they do, it will be in waves. Health system leaders must be prepared with the right amount of staffing to accommodate the unpredictability. The timing is going to be difficult to anticipate, and if an organization doesn’t get it just right, it could be understaffed or overstaffed. Organization leaders need to find ways to manage through the volatility. They also need to create a stronger infrastructure to ensure business continuity in the face of future crises, whether those include a re-emergence of COVID-19 or some other catastrophe.
How does your solution address these needs?
Regarding the first set of challenges, our solution automates and simplifies revenue cycle management, allowing organizations to do more with less. Our product is designed to learn existing revenue cycle workflows, automate them and then perform them at scale while accommodating outliers. Onboarding our solution involves a three-step process — observe, learn and perform. The observe step starts with reviewing an organization’s current revenue cycle workflows. We deploy proprietary software to capture a range of data that yields a 360-degree view of what’s happening in the organization from a revenue cycle perspective. We then move to the learning step, which uses machine-learning algorithms to learn the organization’s workflows and includes making corrections and modifications to broken or cumbersome processes. Then, the system begins to perform tasks, taking on new ones as it learns. The system flags issues to our team of revenue cycle experts who immediately triage any outliers, resolving them in real time while our system learns the new process.
Since our solution lives and operates within our clients’ existing electronic health record (EHR) and billing systems, we can deploy entirely remotely, and there is no new training required for existing health system staff. As a result, our technology can be up and running within 90 days of receiving data. As our solution learns and takes on more tasks, health systems can reallocate staff to more meaningful work, allowing the organization to boost productivity while reducing costs.
For the more recent challenges, our solution is completely scalable for revenue cycle teams. In high volatility periods like what we’re going to see over the next year, healthcare organizations can use our system to scale up and absorb near-infinite demand during surges, and then quickly and painlessly scale down as volume decreases. For example, we recently had a customer that increased demand by 50% with little advance notice. We were able to rapidly scale-up the automation system and absorb that demand.
Future business continuity will entail identifying resources that will be unaffected by future crises, so that revenue cycle operations can continue unaffected. Our customers have access to this type of resource now. For instance, as one customer’s revenue cycle team saw staff productivity slowdowns due to the sudden transition to remote work required by COVID-19 shelter-in-place orders, we were able to assume the excess demand while keeping quality and accuracy high.
What are some key considerations for healthcare leaders when choosing this type of solution?
When we set out to create our technology, we were thoughtful about designing it from the ground up. We evaluated modern automation approaches from some of the most complex domains in the world, such as self-driving cars. We then embedded several of their core principles into our development process, including incorporating the best ways to monitor existing workflows, learning from workflows at scale and quickly adapting to change. Our team built proprietary technology to apply these core principles to the unique nuances of healthcare revenue cycle management, seamlessly blending human judgment and subject matter expertise with machine learning.
Our unique development process has allowed us to make sure every component of the solution fits together perfectly because we built the system from scratch. We don’t white label software from other vendors. Our solution is vertically integrated, is purposefully built for healthcare revenue cycle management and eliminates the need for a cumbersome patchwork of solutions.
Alpha Health has been able to create this comprehensive solution because of the experienced technical and revenue cycle subject matter experts we’ve assembled. Our deeply knowledgeable team has pushed the company to be thoughtful about the entire revenue cycle and build a single solution that incorporates everything that financial leaders need to be successful.
As healthcare organizations implement your solution into their day-to-day operations, what advice would you offer so they can best set themselves up for success?
It’s important to be practical in the short-term and ambitious in the long-term. For initial deployment, organizations should focus on a clearly defined area in which to apply Unified Automation. Leaders should be strategic when identifying this area, looking for options that minimize the need for change management. We can share best practices based on our experience around ideal focus areas to help guide the decision.
Thinking about the long-term, organizations should be ambitious about the scope and scale of the overall initiative. We’ve found that many healthcare leaders don’t dream big enough because more traditional automation tools, like robotic process automation, are limited in their capabilities. However, when you bring a machine learning-enabled approach into the picture, the scope of the project can and should expand.
Another key area of consideration pertains to the solution’s pricing model. If organization leaders truly want to be forward thinking with their vision, they should consider pursuing a shared value model. This ensures both the solution vendor and the client have a stake in the results and that the cost outlay truly reflects the solution’s value and ability to deliver outcomes.
How can healthcare organizations learn more about your company?
To learn more about Alpha Health and access some of our latest insights, check out these links:
- alphahealth.com
- https://medium.com/@alphahealth/how-did-healthcare-in-the-u-s-get-so-complicated-a30d3c734e35
- https://www.youtube.com/watch?v=YlsRaNgScHg&feature=youtu.be
About Alpha Health
At Alpha Health, we believe every dollar spent on healthcare matters because healthcare matters to everyone. The first Unified Automation company for healthcare, Alpha Health uses the same machine learning approaches that made driverless cars possible to provide health systems with a single solution for revenue cycle management. Alpha Health’s Unified Automation brings together the best of people, data and technology to efficiently, accurately and autonomously navigate the complex state of medical reimbursement in the United States. This enables health systems to reduce their cost-of-care and be better stewards of the healthcare dollar. Alpha Health is based in the heart of Silicon Valley. Learn more at www.alphahealth.com.