Navigating Budgets and Cost Solutions with AI Radiology Vendors

Many tools are available to help the use of AI for medical imaging, but the majority of the companies creating AI software for radiology applications operate under pay-per-analysis models and take part in pilot programs to test the technology.

Every purchasing analysis and decision must take into account the possible risks and costs, both capital and ongoing that come with implementing and using an AI system. Consulting the risk matrix and risk-benefit analysis found in vendors' regulatory files can help with risk assessment in part. Some dangers, meanwhile, might not be mentioned in these regulatory files or might only surface when the product is being used.


The licensing fees paid to the vendor are the most visible aspect of the cost, but they usually represent a very minor portion of the overall cost of ownership. Contracts and legal agreements, IT work and expert services for integrating with current systems, administrator, and user training, infrastructure for executing the AI, and ongoing maintenance and monitoring are additional cost sources.


Selecting the best AI radiology solution for your radiology team and understanding the different pricing models is essential to align financial planning with the department's needs and usage patterns. Here’s how each model works and what a radiology department should consider:

1. Subscription-Based Models

There are differences in the cost structures of AI software, and most vendors provide a subscription model rather than a capital purchase. There are several licensing choices, such as licensing for each workstation, user, research, or complete site. The most straightforward choice is one that permits the processing of an infinite number of studies since it permits testing on a greater variety of test kinds. Since the majority of businesses are still in the process of acquiring consumers, they can be open to customizing their payment plans to meet the demands of the organization.

How it works: In a subscription-based model, the radiology department pays a regular fee (monthly, quarterly, or annually) to access the AI radiology solution. This fee typically covers usage up to a certain limit, along with support, maintenance, and sometimes updates.

Pros:

• Predictable costs: Budgeting is easier because the department knows its expenses upfront.
• Ease of access to updates: Subscriptions often include automatic updates, ensuring access to the latest features and improvements.

Cons:

• Long-term commitment: Contracts might lock the department into using the solution for a considerable period, reducing flexibility.
• Possibly higher costs over time: If the department's usage doesn't fully leverage the subscription, it may end up paying more per use compared to other models.

Usage considerations: A subscription model suits departments with consistent imaging volumes that closely match the subscription's usage limits and those looking for predictable budgeting.

2. Pay-Per-Use Models

A popular billing technique that bases prices on a customer's actual use of a service or product. People who appreciate payment alternatives with flexibility find it particularly appealing. Customers are billed based on how well they use the service, as opposed to a set charge. A multitude of variables, including the quantity of units used and the length of consumption, may be used to determine the billing.

How it works: Costs are incurred each time the department uses the AI tool, based on the number of images analyzed or reports generated. There's no fixed monthly fee; you pay for what you use.

Pros:

• Flexibility: Ideal for departments with fluctuating imaging volumes.
• Scalability: Costs align with department growth or contraction, making it suitable for departments experiencing variable demand.
• Transparency: The customer can easily see where the costs came from. In addition, those who use a service seldom will pay less for it, matching the price to the amount used.

Cons:

• Unpredictable expenses: Costs can vary significantly from month to month, making budgeting more challenging.
• Potentially higher costs during peak periods: If there’s a sudden increase in imaging volume, the costs could escalate quickly.

Usage considerations: This model is beneficial for departments with variable imaging volumes or those starting to integrate AI tools and uncertain about their long-term usage patterns.

3. Custom or Tiered Pricing Models

    
It is based on the idea of providing different price points for different attributes or features of a good or service. This approach departs from the "one-size-fits-all" mentality that characterizes flat-rate pricing. Rather, layered pricing offers a range of options, from entry-level products to premium bundles. This guarantees that clients will have the freedom to choose a package that closely matches their requirements and financial constraints.

    

How it works: These models offer a mix of fixed and variable costs, customized or adjusted based on specific features, usage levels, or additional services the department requires. Pricing may have tiers that correspond to different levels of usage or feature access.

Pros:

• Customizability: Can be tailored to fit the exact needs and budget of the department.
• Scalability: Adjustments can be made as the department's needs change over time.
• Customized Pricing: This can be easily customized by businesses to match the specific requirements of different client segments.
• Tailored value: By providing clients with varying degrees of value and services
• Flexible tiers: By modifying pricing tiers, businesses can effectively accommodate both new and existing clients.

Cons:

• Complexity in planning: Determining the best tier or custom plan might require more effort and negotiation.
• Potential for overpaying: Without careful planning, departments might end up in a higher tier or with services they don't fully utilize.

Usage considerations: Ideal for departments with specific needs that don't fit neatly into a one-size-fits-all model, or those looking for a balance between predictable costs and flexibility.

Total Cost of Ownership (TCO)

In addition to direct and indirect costs, TCO also includes certain intangible costs that could have a monetary value. Beyond the initial pricing model, consider the TCO, which includes:

• Integration costs: Time and resources needed to integrate the AI solution with existing systems.
• Technical cost: Depending on the type of integration chosen—cloud or on-premise—there might be an associated cost.
• Maintenance: Ongoing costs to ensure the solution operates smoothly.
• Upgrades: Potential future costs for accessing advanced features or updates.

Challenges:

• Various Approaches: There are numerous software programs and approaches available for figuring out the TCO.  When businesses don't use the same approach, they make different purchases.
• Difficulties in Establishing Operating Costs: Determining the extent of IT equipment operating costs can be challenging.
• Example of Support Cost: Spare components may be part of the support expenses for one server, which could raise support costs while lowering acquisition prices when compared to another server.
• Changes in Vendors: Businesses encounter unanticipated and substantial extra expenses if a software provider discontinues support for a particular program after three years, stops carrying parts after five years, or cancels functionality.

Cost analysis for various possibilities is completed by enterprise managers and purchasing decision-makers, who then compare TCOs to ascertain total expenses and, ultimately, the lowest long-term cost. The purchase price or license costs for one server, for instance, may be less expensive than in a competitive model, but decision-makers can see that any apparent cost savings would be greatly offset by expected upgrades and yearly service contracts. Without TCO analysis, businesses run the risk of making serious mistakes in their IT budget calculations or buying servers and other components that aren't right for their computing requirements, which could lead to sluggish services, unplanned downtime, and other issues.

Scenario

    
Let's consider a hypothetical use case for an AI radiology solution within a medium-sized hospital's radiology department. This department is weighing its options between subscription-based, pay-per-use, and custom/tiered pricing models. We'll outline the financial implications of each model over one year to aid their decision-making process.

The department processes an average of 5,000 imaging studies per month. They seek an AI solution to enhance diagnostic accuracy and efficiency. Their average monthly imaging volume can fluctuate by ±20% depending on the season.

1. Subscription-Based Model

• Cost: $10,000 per month, covering up to 6,000 studies.
• Annual Cost: $120,000
• Pros: This model suits the department's average volume well, provides cost predictability, and includes updates and support.
• Cons: The department pays the same even if the monthly studies drop below 5,000, potentially overpaying during slower months.

2. Pay-Per-Use Model

• Cost: $2.50 per study.
• Annual Cost Variation: Depending on volume, the cost ranges from $135,000 (5,000 studies/month average) to $162,000 (if the volume increases by 20% for several months).
• Pros: This model offers flexibility and aligns costs with actual usage, beneficial for fluctuating demand.
• Cons: Budgeting is challenging due to cost variability, and peak periods could lead to unexpectedly high expenses.

3. Custom or Tiered Pricing Model

• Setup: A custom plan is negotiated to include a base of 5,000 studies per month for $8,000, with each additional study over the limit costing $1.75.
• Annual Cost for Average Use: $96,000 base + variable costs for overage. Assuming an additional 10% usage for half the year, the total cost would be approximately $108,500.
• Pros: This model offers a balance between predictability and flexibility, allowing the department to save money during average or lower usage months while accommodating occasional surges.
• Cons: Requires accurate estimation of needs and close monitoring of usage to avoid unnecessary expenses.

Considerations

In this scenario, the custom or tiered pricing model appears most cost-effective, given the department's variable imaging volumes and specific needs. It allows the department to enjoy lower costs during regular or slow months while still managing to contain expenses during peak periods.


Do you want to learn how to implement these technologies in your medical department? Click HERE to download your free copy of "Choosing the Best AI Radiology Vendors"