Artificial intelligence (AI) is becoming increasingly prevalent in various industries, including healthcare. AI can provide healthcare professionals with tools to improve patient care and streamline administrative activities.

One area where AI can have a significant impact is in payer administration and operations. By implementing AI technologies, payers can optimize their processes for more efficient and cost-effective healthcare delivery.

Exponential AI, a healthcare AI platform company, recognizes the challenges payers face due to rising demand, dynamism and complexity in healthcare. They offer payers a suite of tools to create smarter processes that can help them succeed. Through their Enso Decision Intelligence Platform, reusable Decision Agent Ecosystem, and a wide range of AI solutions, Exponential AI can help payers integrate decision intelligence into any process, resulting in exponential value creation.

Let’s understand in detail what the company is into whilst in conversation with Nikhil Mendhi, President and COO

What were the main driving factors behind the development of Exponential AI and how has it evolved since its inception?

 In 2019, a few of us, all healthcare leaders, founded Exponential AI to address the challenges faced by healthcare organizations in delivering better quality care, more efficiently and economically. Traditional rule-based systems and manual processes are unable to solve these problems, and we saw AI as a tool that could respond to these pressures very well.

 Our mission was to bring AI and ML capabilities as a core competency to the healthcare industry. Instead of selling algorithms by the slice, we opted to provide a platform that clients could control, and evolve over time. This approach allows AI to be applied in real-time alongside existing workflows and systems. It also enables a shift from reactive to proactive processes and transactions, driving better cost, quality, and productivity outcomes.

 In your opinion, what emerging technologies have the potential to significantly impact the future of healthcare and why?

 I think artificial intelligence (AI) is the most promising emerging technology that has the potential to significantly impact the future of healthcare. Healthcare is a complex and dynamic industry, and AI’s ability to learn and train on the information that flows through it is particularly well-suited to address the challenges facing healthcare today.

As you know, healthcare is delivered, consumed, and demanded in different ways across different populations and geographies, making it difficult to apply standardized solutions. It needs a more adaptive and context-specific approach, and AI has the ability to learn and understand those local behaviors and environments. By analyzing longitudinal information, claims history, and social determinant data, AI can help payers and providers streamline administrative processes and improve predictive capabilities. This, in turn, can lead to significant bottom-line savings, making the investment required for AI adoption more feasible.

While there are also exciting use cases for AI and ML on the clinical side, turning those into bottom-line savings can be a challenge due to the need to change provider and payer behavior. Starting with administrative simplification and predictive capabilities can generate immediate value and drive investment in AI and ML. And as AI becomes more integrated into the fabric of healthcare operations, it will usher in a new era that delivers better cost, quality and experience of care. 

Could you share a success story about how your company has helped a healthcare organization accelerate AI adoption and reduce costs? 

In one instance, a Fortune 50 company approached us to assist in applying AI to transform a process in their Claims Value Chain. Upon onboarding the client, we helped them build an AI-driven solution that delivered on their savings expectation in less than 6 months.

With this success and the opportunity to replicate this success across processes, they chose the platform to be their one-stop destination for all things AI and they went on to build and manage over 30 solutions.

Moreover, more than 80 per cent of those solutions were built by the client’s internal team. The client was able to scale their AI solutions across processes in 18 months with Exponential AI’s Enso. Our platform enabled them to build AI solutions three times faster. They could launch more solutions than they planned and generate more ROI from AI solutions.

How and why is the adoption of AI becoming urgent for healthcare payers?

The healthcare industry in the US is a massive ecosystem, accounting for a third of the country’s GDP, but it is fundamentally broken. The system is focused on procuring healthcare services rather than improving care, and the mechanisms underneath do not provide the transparency or measures of value necessary to deliver higher quality care. Efforts over the years to improve the system, such as ACOs, medical homes, and new technologies, have only added complexity and administrative burden, and failed to address the underlying problems. Furthermore, the industry is operating on outdated systems that are siloed and fractured, making it difficult to create transparency and longitudinal views on how care is delivered.

The government has tried to step in with regulations and star scores, but these have added additional economic burden to the payers and compressed their margins. Patients’ deductibles are going up, and large payers have reported tremendous losses in the last six weeks. 

Payers are under a lot of pressure to figure out how to operate more efficiently, in a very inefficient ecosystem. AI may very well be their answer. AI has the unique ability to pierce through healthcare’s silos and pull in data from everywhere to deliver data-driven decisions in real-time thereby reducing manual efforts. 

How has real-time AI impacted healthcare operations and what are some potential use cases in the near future?

Real-time AI can have a significant impact on healthcare operations by allowing for proactive processes and transactions. In healthcare, most transactions occur on-premises, while AI adoption has mostly been cloud-driven. This creates a challenge as it takes too long to send data to the cloud, analyze it using AI and ML, and bring it back on-premises, resulting in missed opportunities. To address this, AI needs to work in a hybrid environment, both on-premises and in the cloud, and apply insights in real-time.

Regarding use cases, healthcare payers can benefit from real-time AI by using it to identify fraud, waste, and abuse in healthcare claims. AI can analyze healthcare claims data in real-time, identifying patterns and anomalies that may indicate fraudulent activity, saving payers money by reducing fraudulent claims. Real-time AI can also help payers find cost-saving opportunities by analyzing claims data to identify areas where costs can be reduced without harming patient care. 

Could you walk us through how your products and services have been utilized to help healthcare organizations accelerate their AI journeys?

Exponential AI’s healthcare Decision Intelligence suite addresses the main challenges that healthcare organizations face when adopting AI. The suite includes three products: Discover, Insights, and Execute. 

Discover allows clients to prepare and test AI solutions with small local healthcare data sets, which helps evaluate AI readiness. Insights enables feature engineering and training on broader data sets to evolve AI on a wider cross-section of data to estimate potential business value. 

Finally, Execute enables clients to run and manage AI in production. 

Using these products, healthcare organizations can accelerate their AI adoption journey by enabling faster access to healthcare data, addressing fragmented and siloed data, and getting AI into production quickly and efficiently.

Should healthcare companies build their own AI solutions instead of using off-the-shelf solutions, and how does Exponential AI help them overcome the challenges associated with building custom solutions?

Healthcare companies must build their own AI solutions because it lets them create solutions that are customized to their specific needs and business objectives. Off-the-shelf solutions may not always fit seamlessly into their existing systems and processes. Additionally, healthcare is very dynamic and local, with wide variations in how healthcare is delivered, consumed, demanded, and behaves locally. This makes it difficult to apply standardized solutions. Off-the-shelf solutions 

may not be set up to learn and understand those local behaviors and environments, Custom AI solutions can be built to learn and understand these nuances, providing a more context-specific approach to healthcare.

Furthermore, building AI solutions gives healthcare companies control over their data, which is critical when it comes to compliance and security. When buying an AI solution, they may have to share their data with the vendor, putting their sensitive information at risk. 

However, building AI solutions may require large investments and technical expertise, which can be a longer process than buying a ready-made solution. To enable faster adoption and time-to-value without sacrificing flexibility, Exponential AI’ offers pre-built Healthcare solutions that are built on an Open Architecture. 

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