Healthcare systems are under intense pressure—staffing shortages, tighter budgets, rising operational demands—all while navigating the relentless pace of digital transformation.
When we talk about improving operational efficiency, testing often flies under the radar. Let’s be honest—software validation and UAT aren’t the flashiest parts of Health IT. But they are absolutely essential to system safety, regulatory compliance, and patient care.
📊 A recent study across14 healthcare systems found that each spends nearly 25,000 hours annually on testing activities. That number might surprise you—but it makes sense. Testing is often manual, fragmented, and performed with spreadsheets, Word docs, and shared drives.
We can do better.
Improving how we test is one of the most practical ways to increase efficiency in Health IT—without sacrificing safety or compliance. And one promising step is to incorporate test automation where it makes sense.
But is it a silver bullet? Not quite.
✅ Where Automation Excels
When used strategically, automation can be a powerful accelerator—especially for the right kind of work.
Think about high-volume, repetitive tasks. Registering hundreds of patients, placing the same types of orders, loading standard panels into a LIS—these are ideal candidates for automation. You don’t need human judgment here, just accuracy and speed. That’s where automation shines.
It also offers consistency. Manual testers can introduce variation without meaning to—clicking out of order, entering inconsistent data. Automation performs the same steps in the same sequence every time, which is especially valuable for regression testing after vendor updates.
Automation also works well for routine smoke tests—quick checks that make sure the system is up and running post-deployment. A well-scripted test can log in, search a patient, place an order, and validate a result in minutes—freeing up your team to focus on more meaningful validation work.
And here’s an underrated use case: test data preparation. Automated scripts can create clean, consistent test data—patients, encounters, orders—so thateveryone starts from the same baseline, avoids setup errors, and saves countless hours of prep time.
❌ Where Automation Falls Short
That said, there are critical areas where automation doesn’t hold up—and trying to force it can actually backfire.
The most obvious?It removes the “user” from user acceptance testing.Automated scripts don’t ask questions. They don’t flag when a field label is confusing or when a result format isn’t clinically appropriate. Real UAT is about real users exercising judgment and offering feedback—things automation simply can’t replicate.
Compliance is another major gap. Automation doesn’t produce audit trails, screenshot testing evidence, or facilitate clinical sign-off. It executes steps, but it can’t explain why a test was run or who approved the outcome. That’s a problem in regulated environments where documentation and human oversight are non-negotiable.
There’s also the reality that robust automation requires a programmer’s mindset. Writing scalable, maintainable test scripts takes structure, abstraction, and planning—not to mention the time and skill to fix things when they break (and they will).
Speaking of breakage: automation is notoriously fragile in dynamic systems. Small UI changes—a renamed field, a new dropdown—can cause tests to fail unless they’re built with proper abstraction and resilience.
And as tempting as it is to automateend-to-end workflows, doing so across multiple systems (say, EHR → LIS → billing) adds huge complexity. Timing issues, data dependencies, and environment variability all make these scripts brittle and difficult to maintain long-term.
Lastly,under CSA guidance, testing should be risk-based. Automation can help execute test steps, but it can’t provide clinical reasoning, traceability, or evidence of validation. That still requires human input—especially in high-risk or patient-facing workflows.
💸 Cost & ROI: What You're Really Signing Up For
There’s no doubt tha/tautomation, when done right, can deliver excellent ROI. It can shorten test cycles, reduce manual burden, and bring consistency to routine validation.
But it’s harder than it looks.
Many automation projects are launched with excitement—and quietly abandoned within a year or two. Why? Because they were approached as the next shiny object, without clear goals, the right resources, or a long-term plan.
Tools like Eggplant by Keysight are widely used in Health IT because they’re flexible and powerful. But they come with real costs—licensing, infrastructure, training, and a steep learning curve. Teams often need 2–3 months just to become productive. And scripts need ongoing maintenance to stay relevant as systems evolve.
The good news? Others have walked this path. Before diving in, talk to similar health systems who’ve succeeded. Ask what worked, what didn’t, and what kind of investment it really took to reach value. These conversations are invaluable for setting realistic expectations and avoiding early burnout.
And if you don’t have the staff or time to build and maintain your own test library, consider a managed automation service. Firms like Software Testing Solutions (for Clinisys SQ) and SureTest (for EHRs) as well as others offer prebuilt test suites, implementation support, and ongoing maintenance—helping you capture the benefits of automation without the overhead.
Bottom line: automation can absolutely pay off—but only if it’s approached with intention, not as a quick fix.
📌 Bottom Line
Many Health IT leaders would love to find a single "one-size-fits-all" testing solution—but testing, like healthcare, doesn’t work that way.
Just as we rely on specialists in medicine to deliver the best outcomes, testing requires the right combination of tools and expertise:
- Use automation where it excels: high-volume, low-variance tasks.
- Trust human testers and subject matter experts where clinical insight, usability, and compliance truly matter.
- And explore modern platforms like Cymetryc that empower testers and close the gaps automation leaves behind in regulated clinical environments.
In today’s do-more-with-less world, the old way of testing—unaided, inconsistent, siloed—is no longer sustainable.
To assure safe, high-quality systems for our patients, we need to move forward—matching the right tools to the right roles, with the right people and mindset behind them.
That’s how testing becomes not just a task—but a true accelerator of better care.
