Interviews: Questions for Malinka Walaliyadde, AKASA's Co-Founder
Introducing AKASA: Revolutionizing Healthcare Revenue Cycle Management with AI
Parachuting into the realm of healthcare technology, we meet Malinka Walaliyadde, CEO and co-founder of AKASA. This innovative company offers cutting-edge AI solutions, empowering hospitals and healthcare providers to streamline the painstaking process of billing and insurance claims, aka revenue cycle management. This move ensures providers receive their hard-earned payments swiftly and accurately, all while reducing administrative hurdles, boosting hospital productivity, and enhancing the patient experience. Here's the lowdown on how AKASA juggles data, AI, and healthcare revenue cycle management.
Makaryan: Let's dive right in. Could you kick things off by giving us the lowdown on AKASA?
Walaliyadde: On the surface, AKASA aims to reinvent healthcare revenue cycle operations with the help of generative AI. Translation? We help providers get paid efficiently for the care they deliver, and we do this by making their billing system more efficient, reducing frustrations, and optimizing financial operations.
Nurturing American medicine’s global dominance while addressing the telecom industry's convoluted intricacies, we founded AKASA. The healthcare system craves modernization, and advancements in AI mean we now have extraordinary tools to simplify archaic billing and payment processes.
Makaryan: What makes healthcare billing such a headache, and why is AI the golden ticket for innovation?
Walaliyadde: The core challenge in healthcare billing is the interlink between medical records and the revenue cycle-the system hospitals and clinics use to bill insurance companies based on patient care. Since payments rely on a precise understanding of treatment, billing teams have to decode clinical documents.
Historically, this has been a labor-intensive, error-prone process, as the non-medical staff couldn't possibly keep up with the complex medical records. They had to sift through mountains of medical lingo to pinpoint the key billing details, causing bottlenecks, oversights, and inefficiencies.
Enter AI. Trained to grasp both clinical records and financial data, our AI acts as a co-pilot for billing teams, making quick and accurate work of deciphering complex medical documents. This automation enhances operational efficiency, reduces administrative burdens, and ultimately, improves financial outcomes for healthcare providers.
Makaryan: How does AKASA's AI magic unfold, and did you fashion a proprietary model or tweak an existing one?
Walaliyadde: Essentially, our platform uses open-source large language models as a starting point. Imagine a model with general knowledge akin to a high school graduate, yet without specialized expertise. We then fine-tune that foundation with healthcare-specific financial and clinical data, morphing it into a master of healthcare revenue cycle management.
This modified AI bests industry-leading models like GPT-4 by 40 to 50 percent in our domain. To put the icing on the cake, we further customize the AI system for each hospital or healthcare provider we collaborate with, ensuring it understands their unique nuances. This tactic guarantees personalized, precise assistance for billing and revenue cycle teams.
Protecting patient data is essential to us. We carefully adhere to industry-best security standards to maintain trust with healthcare providers. We collect data through standard healthcare integrations, granting our AI the privilege to learn from real-world examples without compromising patient privacy. Our approach aims to cater to healthcare providers with minimal technical snafus and full compliance with regulations.
Makaryan: Could you share some of AKASA's success stories or tangible impacts on healthcare organizations?
Walaliyadde: Medical coding is a crucial aspect of the healthcare revenue cycle. With a diminishing talent pool of coders, providers face inefficiencies, delays, and lost revenue due to inaccuracies in coding. Our AI aids coders by reviewing their work and suggesting improvements, bolstering both accuracy and efficiency. The upsurge in revenue has been significant, with some providers recovering millions in earnings they would have otherwise missed due to human coding errors. Moreover, coders tout our AI as user-friendly and helpful, boosting their overall satisfaction levels.
Makaryan: What are your aspirations for AKASA and AI's future role in healthcare?
Walaliyadde: We envision AKASA as an AI partner that offloads administrative burdens from healthcare staff, allowing them to focus more on patient care than paperwork. As AI technology advances, it will expand its role in simplifying healthcare operations, leading to better financial outcomes for providers and an enhanced patient experience.
Our priority is ensuring every product we develop delivers genuine value to customers. We team up with healthcare providers, gather feedback, and iterate based on their needs. Communicating the advantages of AI-driven automation and fostering a smooth adoption process within healthcare systems is another essential part of our strategy.
- Walaliyadde explaines that AKASA employs generative AI to revolutionize healthcare revenue cycle operations, aimed at facilitating efficient payment for providers and optimizing financial operations.
- The healthcare system's modernization is imperative, and advancements in AI provide the means to simplify outdated billing and payment processes.
- With AI, deciphering complex medical records becomes less labor-intensive, reducing bottlenecks, oversights, and inefficiencies in the billing process.
- AKASA's platform takes open-source large language models as a starting point and fine-tunes them with healthcare-specific financial and clinical data for unparalleled accuracy in healthcare revenue cycle management.
- The AI-driven success of AKASA is demonstrated in medical coding, where it boosts accuracy, efficiency, and provider revenue, all while enhancing coder satisfaction levels.
