The following is a guest article by Prasanna Ganesan, Founder and CEO at Machinify
With enterprise technology evolving more rapidly than ever before, and the advent of AI and other new tools, it has been a struggle for organizations to keep up. This lag is also known as “technical debt”—the idea that IT systems fall behind the latest and greatest technologies because teams opted to “borrow” against long-term quality in service of short-term workability. A recent report from Forrester found that nearly four in five IT decision leaders in the U.S. face at least moderate levels of technical debt.
For those IT leaders and others in their situation, it’s especially crucial that technical debt is addressed promptly since it compounds at a very high interest rate. Organizations anxious to apply quick fixes to deep-rooted problems might see short-term benefits and avoid large-scale disruption for a while but eventually, too many of these band-aid solutions will slow innovation to a crawl. It’s nearly impossible to improve or change a module when it’s unclear what the follow-on effects will be. When a new tool is added on as a patchwork fix for one problem, it results in additional technical debt in another area, and the cycle continues.
Healthcare’s Technical Debt Problem
Technical debt is ubiquitous across a number of industries, but healthcare is uniquely susceptible to its effects because such a large proportion of the tech stack is past its use-by date, resulting in the stack itself feeling like technical debt.
Providers, payers, and vendors are all impacted by technical debt, but few healthcare stakeholders demonstrate the long-term problems created by short-term fixes better than those in payment integrity. These solutions, which are designed to help health plans pay claims more accurately and efficiently by enforcing specific policies and guidelines, are rife with outdated, inflexible technology.
Today’s payment integrity architecture arose from many small-scale, tactical fixes, made to patch the claim adjudication process with band-aid after band-aid. The result is a complicated chain of cobbled-together elements and processes, many of which are redundant, and each of which has its own flawed understanding of the policies they are intended to consistently enforce. The resulting system is one that’s unable to efficiently help health plans fix claims adjudication processes.
Because insufficient components were patched over rather than replaced, technical debt continued to build, and the system we’ve ended up with is unable to holistically fix root problems from the ground up. Many of these systems need to be entirely redesigned to review claims in a new way.
Steps to Pay Back Technical Debt
Reducing technical debt comes down to two essential steps. First, organizations must isolate the debt into digestible, modular chunks. Then, within each chunk, they need to plan a progressive takeover of one implementation by another in a way that doesn’t impact external systems. For the first step, IT teams need to locate the system or module that is being asked to do more than it’s designed for and, therefore, performing poorly. If it is not yet isolated from other systems, the software implementation needs to be redone so that it can be. From there, the second step can commence, starting by putting a plan in place to replace the module that, critically, will not rely on a hot swap.
Sticking with the payment integrity example, the health plans that have effectively overhauled these processes have done so via a safe migration strategy that relies on a gradual transition. They implement an update that wraps around a primary system that’s a source of technical debt, learns how the module in the primary system is doing its job, and, once confident, offers a new method to correct the primary system. From there, an iterative test-and-expand process is used to shift more and more responsibility to the new system over time. As this process progresses, more functionalities can be transitioned over to the new system to make a centralized, modernized, automated, and patchwork-free technology stack.
Technologies like AI and automation will continue to play a larger and larger role in healthcare processes, and organizations will need to avoid technical debt by proactively staying up-to-date with solutions that allow them to operate as effectively as they can. The ones who don’t will be left behind and once their technical debt compounds face an uphill climb to catch up.
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