Posted June 10, 2020

For every $1 of revenue collected by a hospital, $0.25 is spent on the administrative tasks required to collect it. That’s several multiples higher than the highest payment processing fees in other industries, and even worse, most of that spend is on human labor to perform mundane tasks. The ratio of doctor to non-doctor workers in healthcare is roughly 1:16, and the high rate of workforce growth over the past several years—combined with only modest improvements in health outcomes—has resulted in one of the worst labor productivity challenges we’ve seen in any industry.

This morass, which represents hundreds of billions in administrative spend related to billing, collections, and payment, is one of the major drivers of high healthcare costs in the U.S. In addition, the slow but steady shift to value-based care has left most large hospital systems managing multiple payment models under one roof, which has only increased the complexity of revenue cycle processes.

On top of this, hospitals and clinics are amongst the businesses most devastated by COVID-19, with revenue streams evaporating nearly entirely overnight, which has forced many to shrink the size of their administrative teams to stay afloat. This has resulted in an inability to keep up with the billing practices required to maintain a steady income for hospitals and clinics. 

We are at a critical turning point where the revenue cycle world of healthcare needs a major reboot—one that will help providers rejuvenate their practices with agility, capital efficiency, and operational resilience, in our journey towards a more cost-effective healthcare system.

This is the mission of AKASA (PKA Alpha Health), which intelligently automates the end-to-end revenue cycle for provider organizations. Inspired by some of the most advanced applications of machine learning and human judgment seen in driverless cars, AKASA’s platform is purpose-built for the areas of financial clearance, billing, and claims processing. It infers how to construct the optimal path for completing each job in that process, rather than simply replicating the rote tasks that humans perform (errors and all), as generic RPA-based approaches do. And AKASA’s technology dynamically learns as new paths are introduced or historical paths change, which means you don’t need to halt everything in order to manually rebuild scripts when they break.

The result  is a fully virtualized billing system, “Unified Automation”, which eliminates unnecessary work, continuously learns, and can perform the equivalent of 10+ people’s administrative work. Unified Automation takes over management of the billing work queue, grabs and executes the tasks it is confident it can complete, and escalates those that require more complex problem solving to its human peers. Over time, it also dynamically adapts to the rules of each payor and claim type to develop more sophisticated capabilities, thus allowing staff members to shift their focus to higher order work, and rapidly improving the overall efficiency, performance, and employee satisfaction in the practice.

This approach enables some of the most complex provider organizations to streamline their administrative costs and redirect their investments into clinical services and patient support. At a time when both a shortage of clinicians and the overburdening of physicians has pushed care delivery to a breaking point, AKASA is taking on the heavy lifting behind the scenes so that their customers can focus on improving the patient and physician experience.

The teams we invest in to tackle these holy grail problems tend to be interdisciplinary in nature, bringing top-tier expertise from multiple domains to derive fresh insights on how to build the winning solution. The AKASA team is no exception: founders Malinka Walaliyadde, Varun Ganapathi, Andy Atwal, and Ben Beadle-Ryby have deep roots in complex revenue cycle operations from The Advisory Board Company and Counsyl, as well as experience in cutting edge AI, computer vision, and automation from Stanford, Google, and Udacity. The rest of the team exhibits a similar mix of complementary expertise, from AI teams at prominent tech companies, and revenue cycle leadership positions at leading provider organizations. This combination of skills has resulted in a best-in-class solution that brings first-class technology to bear, but packaged in a way that traditional provider organizations can easily adopt without having to fundamentally change the way they operate.

Talk of how to fix our broken healthcare system frequently focuses on the clinical and front office opportunities. But the tangled web of back office administration is perhaps where the biggest immediate impact can be delivered in the form of cost savings and improvements in efficiency—especially when it comes to the very process by which providers get paid. At a time when the fragility and antiquity of our healthcare system’s infrastructure is so visible, I couldn’t be more excited to be leading AKASA’s Series A and joining their board. We look forward to continuing to support Malinka, Varun, Andy, Ben and team in their quest to use machine learning and automation to decrease the cost of care and help providers be “better stewards of the healthcare dollar.”