AI-as-a-Service: Aligned Incentives Drive the Best Results

Incentivizing performance: How AI-as-a-Service aligns incentives to drive the best results

The shift from fee-for-service (volume as priority) to value-based care (value as priority) has been an active topic for healthcare executives for the past decade. If done correctly, it’s an intuitive and resonating concept to improve outcomes for patients and cut costs for the entire healthcare ecosystem. But it’s not without controversy, particularly regarding the investment required, operational and financial dependencies, and new risks and complexity for health systems to consider.

Without getting bogged down in the tactics of when and how the shift from volume to value occurs, there is fairly universal agreement that the strategy is sound. It’s not if, but when. It’s extremely logical to measure the effectiveness of a healthcare ecosystem by the outcomes it drives and the resources required to deliver those outcomes. And by aligning incentives, we can improve performance and create a win/ win/ win scenario. A win for the patients, a win for their caregivers, and a win for those communities across the globe who aren’t yet receiving care but are absolutely dependent on a highly optimized and efficient system for when they might need it.

So, what do AI-as-a-Service and the value-based care model have in common? Like value-based care and pay for performance models, AI-as-a-Service partners focus on delivering exceptional outcomes and are incentivized by the ability to manage the resources and process, aligning incentives and optimizing results.

AI-as-a-Service puts the accountability back on the vendor

The value-based care model works by aligning patient, provider, and payer incentives in hopes to advance the common goals of healthcare: to improve patient and population health while reducing costs. Similarly, AI-as-a-Service aligns the incentives of the AI provider with the goals of the health system: improving operations, reducing costs, and delivering consistent results that meet or achieve the established ROI targets for any given program. Simply put, the AI-as-a-service framework allows health systems to own the results while the partner organization owns the risks and resources.

Ownership and responsibility of the AI solutions stay with the vendor; it’s up to the AI-as-a-Service partner to manage a solution that works 24/7 and delivers the desired outcomes regardless of the dynamic nature of healthcare. Changing payer and Federal/ State/ local requirements, changing technology – all can be managed. And in the AI-as-a-Service model, the responsibility of “figuring it all out” lands squarely on the shoulders of the partner organization best-suited to manage it with speed, agility, and scale. Just like in value-based care, patient, provider and payer stakeholders are looking for results, not just a product.

When healthcare systems choose AI-as-a-Service, they’re able to reinforce their strategic priorities and investments on core competencies, like delivering exceptional care. Through this model, distractions are minimized and organizations are more likely to realize their goals of near-term financial performance and improved operational efficiencies – both of which are key for sustainable growth so healthcare organizations can expand the populations of patients and communities they serve. Instead of selling a product that may or may not deliver on its promises and then vanishing post-implementation, an AI-as-a-Service vendor becomes your partner – equally invested in your ability to deliver results because of a shared vision and aligned incentives.

The cost problems of traditional healthcare AI purchases

The traditional method of purchasing standalone RPA “bots” or building AI programs internally isn’t always working as planned. Some organizations are even beginning to react negatively outright to the term “bot.” Given it’s a reference to a completely un-human thing – a cog in a machine that prioritizes activity rather than outcomes – it’s somewhat understandable. AI is intended to unlock human potential and accelerate the pace at which we can improve the human condition – not make human processes more mechanical.

We now have enough data to support the fact that operating at a limited scale hurts the effectiveness of “bot-centric” programs. In fact, over 50% of RPA projects fail to deliver their expected performance. The root causes? Higher-than-expected costs, unpredictable timelines, resource limitations, gaps in internal expertise, and post-live support. AI-as-a-Service addresses those issues head on.

Already a big upfront investment, AI and RPA programs often become more expensive due to administrative costs necessary to ensure their success. Licensing fees, software maintenance, consultants, extra technology integration requirements, surprise implementation or support costs – these all add up. The total cost of automation becomes much higher than originally expected, putting a drain on internal financials, hurting the project’s ROI, and dampening internal enthusiasm for AI initiatives. Additionally, small-scale RPA bots are notoriously fragile, and often “break” due to third party software updates and changing file structure, Application Programming Interfaces (APIs), User Interfaces (UIs) – in other words, more money and effort to merely sustain baseline performance.

Managing changing technology and payer regulations while balancing patient needs is getting more difficult and expensive by the day. To stay focused on delivering care, health systems are choosing a single partner that can own, manage, and optimize the success of their AI program. With AI-as-a-Service, health systems coordinate annual licensing arrangements consistent with the program performance they desire. Once the operational and financial performance levels are set and other key priorities are established, that single license includes everything necessary to deliver your results: requirements gathering, design, build, implementation, ongoing support, and performance optimization. No surprise costs, just results.

Olive is the only healthcare-specific AI-as-a-Service solution

When you hire Olive, you’re hiring a partner invested in the same outcomes you are: increasing efficiencies, improving capacity, and delivering value to your stakeholders across the ecosystem. You can focus on delivering exceptional patient care, improving caregiver well being, growing new community initiatives – whatever’s necessary to drive your Mission and expand your influence. The Olive Works and Helps AI workforce runs 24/7/365, with a team of experts constantly expanding Olive’s ability and intelligence every day. Olive gets results for our customers quickly and with scalable impact. Our AlphaSite customers even get a guaranteed 5:1 return on the program. From reducing denials and avoidable losses to accelerating revenue collection, Olive is committed to our health systems across the country and the patients and communities they serve.

Considering AI and automation at your organization? Learn more about the AI-as-a-Service advantage and why it’s the preferred model of purchasing AI and automation.

Investing for Enterprise Impact Whitepaper

A Healthcare Executive's Guide to AI Workforce Models

Read this white paper to understand the total cost of ownership of various purchasing models for AI and automation, so you can chart the right course as you invest.

Get the White Paper

Related Articles

Learn more