Open Enrollment Readiness for Health Plans: Why Under-Testing Carries Hidden Costs 

• Part three of a three-part blog series exploring key quality and performance considerations for health plans preparing for open enrollment.

As open enrollment deadlines approach, testing teams are often working within shrinking windows. Late configuration changes, new requirements, competing priorities, and fixed go-live dates can all create pressure to reduce scope or move certain scenarios to the bottom of the list. 

The immediate tradeoff may seem manageable. The cost of under-testing, however, often appears later, after coverage takes effect and an issue begins affecting claims, eligibility, member communications, provider payments, or day-to-day operations. 

That is what makes under-testing particularly risky for health plans. A defect that looks small before launch can become far more expensive once it has moved across interconnected systems and reached members, providers, or operational teams. 

Blogs one and two in this series focused on testing accuracy and performance readiness. This final installment takes a broader view of quality assurance and the costs that can emerge when testing coverage does not fully reflect the complexity of health plan operations. 

Under-testing can create a ripple effect 

Health plan systems rarely operate in isolation. Enrollment data feeds eligibility. Benefit configuration affects claims adjudication and cost sharing. Provider contracts and fee schedules influence payment. Information also moves between core platforms, ancillary applications, vendors, portals, and downstream reporting environments.  

When testing does not account for those connections, the impact of an issue can spread. A configuration problem may require more than a technical correction. Teams may also need to identify affected transactions, determine which members or providers were impacted, correct data downstream, reprocess claims, update communications, and explain what happened internally. 

That makes the costs broader than the original defect. It includes the time and effort required to find, understand, contain, and remediate the issue after it has already entered production. 

Where the hidden costs show up 

Some of the most significant costs of under-testing are operational. Once an issue reaches production, people who were not part of the original implementation may become involved in resolving it. 

Claims teams may need to research or reprocess transactions. Member services may see increased contacts. Provider teams may need to address payment questions. Technology teams may be pulled away from planned work to troubleshoot and repair defects. Business leaders may need to coordinate remediation across multiple functions. 

Those costs are difficult to capture in a single line item, but they consume real capacity. They can also compete with the work teams were already expected to complete after open enrollment. 

Claims accuracy is only one part of the picture 

Claims adjudication is an obvious area of concern because errors can directly affect member cost share, accumulators, coordination of benefits, payment accuracy, and auto-adjudication. But open enrollment readiness extends well beyond claims.

The broader QA scope for health plans can include annual benefit and plan-year configuration, enrollment and eligibility, member communications, provider network and fee-schedule loads, system upgrades, and regulatory processes.  

A member who receives an incorrect ID card, sees inaccurate network information, or encounters an eligibility issue may experience the problem before a claim is ever submitted. That is why testing needs to reflect the full lifecycle of the member and operational experience. 

Integration gaps can be especially costly 

Many defects become visible at the points where systems connect. A component may work correctly on its own while the information passed between applications is incomplete, delayed, or interpreted differently downstream. 

System integration testing helps validate that data moves correctly across core platforms, ancillary applications, vendors, reporting systems, and data warehouses. End-to-end testing takes that further by following a workflow across its full lifecycle, such as enrollment through adjudication and remittance.  

These approaches matter because a health plan can have individually functioning systems and still encounter problems when those systems are expected to work together. Under-testing at the integration level leaves those gaps to be discovered in production. 

Regression gaps can bring old problems back 

Open enrollment frequently involves changes to existing systems rather than entirely new ones. That creates another source of risk: a change that works as expected may unintentionally affect something that was already working correctly. 

Regression testing helps teams confirm that existing functionality remains stable as new changes are introduced. Building a prioritized regression suite, and automating appropriate portions of it, can also make repeat testing more manageable across releases and upgrades.  

This is particularly important when timelines are compressed. Without a defined regression strategy, teams may focus heavily on the newest changes while giving less attention to established workflows that could still be affected. 

The cost of remediation grows after go-live 

Issues identified during testing can usually be addressed within the implementation process. Once those same issues reach production, resolving them often requires more people, more coordination, and more operational disruption. 

The organization may need to determine the root cause, identify affected populations, correct the underlying configuration or code, validate the fix, and address downstream consequences. Depending on the issue, that could include reprocessing transactions, correcting member communications, or reviewing prior outputs for accuracy. 

There is also an opportunity cost. Every hour spent on unexpected remediation is time that cannot be spent on planned improvements, strategic initiatives, or the next release. 

Broader QA helps reveal what individual tests can miss 

A mature QA approach considers multiple types of testing together. Configuration and system testing validate the build against requirements. Integration testing follows data across connected systems. End-to-end and user acceptance testing evaluate full workflows. Regression testing protects existing functionality, while data migration and parallel testing can help validate large-scale transitions.  

The value comes from combining these perspectives. Open enrollment readiness depends on individual functions working correctly, systems performing under demand, and workflows remaining reliable as information moves across the broader environment. 

That is also why testing strategy matters. When teams cannot test every possible scenario with equal depth, they need a clear way to prioritize the workflows, integrations, business rules, and member scenarios where failure would have the greatest impact. 

Protect the testing that matters most 

Under-testing often begins with understandable constraints. Time is limited, resources are finite, and late changes happen. The goal is not necessarily to test everything equally. 

Health plans can instead focus on protecting coverage for high-risk workflows and understanding where one issue could affect multiple downstream processes. That means looking beyond isolated functions and considering the full path from configuration and enrollment through claims, communications, and member experience. 

The hidden cost of under-testing is ultimately the amount of work created after an issue reaches production. A disciplined QA approach can help health plans find those problems earlier, when there is still time to correct them before members, providers, and operations are depending on the new plan year. 

How Tegria can help

Tegria supports health plans across the testing lifecycle, including configuration and system testing, system integration, end-to-end and UAT, regression and automation, and data migration and parallel testing. The focus is on identifying risk before go-live and helping teams align testing coverage to the workflows that matter most.

Prepare for open enrollment with greater confidence. Contact Us. 

Read the other blogs in our Open Enrollment Readiness for Health Plans series: Why Functional Testing Accuracy is Non-Negotiable and Why Performance Testing is Just as Critical as Functional Accuracy.