Addressing technology debt[i] in the health IT environment is crucial for ensuring patient safety, regulatory compliance, efficiency, data security, scalability, innovation, and cost efficiency. Healthcare IT professionals and their organizations must leverage technology effectively to deliver high-quality care while staying competitive in an evolving healthcare landscape.

There are many factors that have increased the focus on technology debt.

Time is the common factor for all people who work at managing technology debt.  All equipment ages over time and will need to be upgraded or replaced.  To address this inevitability, the accounting concept of depreciation was developed to help a company accurately reflect the diminishing value of assets over the useful life of the asset and to plan for its replacement.

Putting an asset on a depreciation schedule should be an unambiguous signal to a company that the depreciating asset will need to be replaced at the end of its useful life but is often unknown or ignored by the operational users.  Leaders with fiduciary responsibility should be disciplined at reserving funds to ensure that fully (sometimes partially) depreciated assets can be replaced without putting an undue financial strain on the organization’s operations.

One popular alternative to using capital for depreciable technology is to acquire equivalent (or better) technology as a service[ii] (TaaS).   There are many products and services you can purchase in a hosted mode that will allow you to avoid depreciation altogether.

There are other cash flow and interest rate considerations that Finance can factor into the acquisition/lease versus TaaS decision.  Work with your Finance team to ensure you both have a complete understanding of the benefits and limitations of both approaches.

Technology advancement is another primary factor.  The flurry of activity is inspired by the promise of AI (artificial intelligence) and the associated increase in investments in existing and new technologies.   AI systems can be highly complex.  They often require people with specialized expertise whose deployment of AI usually necessitates integration of AI and supporting tools into existing infrastructures.  Not all infrastructures can handle the increased computing load associated with AI.

Most AI models rely heavily on large volumes of data for training and ongoing “education” of the AI model.  Useful AI models must be refreshed often as new knowledge and insights are discovered.  If the existing infrastructure cannot perform quickly enough to support improved operations, new infrastructure must be acquired or leased.  The capital requirements and ability to remain flexible and agile and to scale to meet the demand can be significant.  The overall goal should be to avoid capital outlays that tie you to a particular depreciating infrastructure.

Successful Innovation requires theorizing, testing in demonstration environments, then scaling as you deploy novel approaches to problem solving or deploy new, more advanced features and functions.  Success will substantially increase demand.  Having a demonstration model that doesn’t require substantial upfront investments lets you quickly prove your theories and add features and functions without the need to acquire equipment and hire the staff to support it in a complex technology environment.  More importantly, it allows you to grow and shrink to whatever scale you need based on demand, not just forecasts.

Cost savings can be achieved in most implementations of TaaS (or its equivalents).  Variable cost models can allow you to manage expenses more closely tied to revenue, especially for startups or when you expect to grow substantially and deploy broadly.  You can also benefit from using a variable-cost-based model when your volumes are declining or are seasonal or unpredictable.

Technology advancement, however, can wreak havoc with traditional ROI calculations which generally take 3 to 10 years to realize.  Again, work with Finance.  Create a flexible ROI model that can be adjusted as AI impacts existing technologies and as emerging technologies are added.

For more insights, please read Rich Pollack’s recent blog – Technology Debt – when your infrastructure has been ignored too long.

Here are just a few solutions to address technology debt.  There are others.

• When there is a strong, supportable business case, use a TaaS approach to avoid future technology debt, to facilitate scaling (up and down), and to support innovation.
• Ensure that allocations for depreciating equipment are sufficient to offset all or some of the costs of replacement equipment and that you build reserves for the inevitable upgrades or replacements. Hopefully, newer replacements will be less costly[iii] though oftentimes expanded use of products and services accompanies the purchase of the replacements.
• Create a reliable evidence-based value of investment (VOI) model for technology-enabled solutions to clinical and operating challenges. Track actual performance of the VOI model to ensure you’re achieving the desired outcomes to confirm that the option you selected is achieving its desired clinical and business goals. Periodically revisit your decision and explore switching costs.
• Use selective or comprehensive outsourcing to ensure your overall budget goals are met. When technology is a component of the outsource, your outsourcers will have to manage the technology debt.  With outsourcing you may – likely will – experience a certain loss of control and may have to compete for attention from the vendor.  Trade-offs in IT decisions are common.  All options should be explored regularly.

A reliable, adaptable, and sustainable business approach is essential to ensure that you have the technology to support your ongoing increasingly digitally enabled operations.  Modernizing your IT infrastructure allows you to innovate, operate efficiently and effectively, and respond more quickly to ever changing demand – to serve the patients and families in the communities you serve.

[i] From CoPilot, “Technology debt encompasses the accumulation of all the technology work that a company needs to address in the future. This includes deferred maintenance, upgrades .., modifications to comply with data standards, and customizations beyond what the original software vendor can easily support.”.

[ii] There are several similar options: Technology (TaaS), Infrastructure (IaaS), Platform (PaaS), or System not software (SaaS).

[iii] Moore’s Law anticipated significant drops in computer chip production. It was an observation and projection based on historical trends. Rather than a law of physics, it is an empirical relationship linked to gains from experience in production specifically related to information technology.