Article

Flipping the 80/20 Rule in Healthcare Software Testing

How Gen AI is redefining QA from bottleneck to breakthrough

Gaurav Shrimal
AVP, CitiusTech

19 - Sept

Healthcare software projects are not immune to the ‘not-so-kind’ Pareto principle. 80% of the effort often goes into just 20% of the tasks. More often than not, those tasks revolve around testing.^[1] The Software Testing Life Cycle (STLC) starts with understanding user stories, identifying test scenarios, designing test cases, and progresses to manually automating and verifying every test case. Quality Assurance quietly consumes a massive chunk of time, cost, and energy. It can become the bottleneck that slows product launches and keeps CXOs up at night. More so in an industry where even the smallest software defect can have life-altering consequences.

What if you could flip the equation? What if your teams could reclaim that 80%? How about quality assurance that keeps up with development? Think of test scenarios, test cases, and automation scripts being generated in hours, not weeks. A scenario where human engineers are no longer bogged down by routine checks but are empowered to focus on critical thinking and innovation. All of this without compromising compliance or care standards.

CitiusTech’s Synthetic Quality Engineer (SQE), a Generative AI (Gen AI) powered digital twin for QA teams that redefines the STLC, delivers this possibility to today’s software testing teams. It brings together Gen AI and Foundation Models to transform the STLC.

Pushing the boundaries

Why rope in Gen AI and Foundation Models for software testing? Unlike traditional bespoke AI models, foundation models handle multi-modal data better.^[2] The following aspects make them highly suitable for an automated software testing ecosystem.

They operate with lower development costs.
Most importantly, they do not need the teams to have specialized AI skills to use them.
Their platform-like flexibility allows them to work with most testing tools in the market.
They work well with unclean data, too, and have a conversational design.

Gen AI and foundational models jointly power the “Agentic AI Loop,” a closed feedback system that continuously generates, reviews, validates, and enhances test artifacts with minimal human intervention.

For the healthcare sector, where data variety, privacy, and regulatory scrutiny are high, these models are a game changer. These systems can handle domain-specific needs across the healthcare spectrum - from testing MedTech devices all the way to Payer-Provider systems, or even Life Sciences platforms.

An AI-powered digital twin of the quality professional

The SQE from CitiusTech is a digital twin of the modern Quality Engineer (QE). It is designed to think, act, and deliver like a skilled human QE, but with the speed and scale of AI.

As a digital twin, SQE mirrors the work of a QE professional. It understands feature requirements by reading between the lines to grasp both the context and the intent. It uses this knowledge to create well-structured, testable components. This helps QE teams move smoothly from idea to test execution.

Designed to work with existing automation frameworks, SQE taps into the power of AI agents to rapidly translate feature documentation into verified user stories, test scenarios, test cases, and executable automation scripts. The entire process, from raw feature input to automation output, is achieved with minimal manual effort. All, while maintaining high accuracy and traceability, in case a human traceback is necessitated.

SQE’s modular architecture also supports flexible deployment with support for local tool integration and rapid customization for various tech stacks. Quality Engineers remain part of the loop to ensure contextual relevance and compliance.

Empowering Quality Engineers to redefine themselves

The SQE’s role extends beyond test automation!

SQE takes away the bulk of the efforts needed to convert the feature backlog into an automation output. This frees up Quality Engineers (QEs) to climb up higher on the productivity ladder.^[3] They can possibly evolve from manual testers to strategic overseers and innovation enablers. The additional focus that is now possible on higher-order tasks, such as exploratory testing, performance tuning, security audits, and process optimization, can bring in windfall benefits to the team as a whole.

This shift-left approach ensures that QEs gain a foothold in the project much earlier in the development cycle. Human-in-the-loop capabilities allow QEs to refine AI outputs and enforce domain-specific quality checks when needed.

Real-world Healthcare Applications

Healthcare and life sciences stand to gain the most from this AI-led testing innovation due to their critical dependence on compliance and uptime. The SQE solution can prove its value across a range of real-world healthcare and life sciences scenarios.

In medical devices and technology, it can help automate the test design process of important features like heart monitoring systems and patient tracking. Accuracy and safety are both critical in this sector. For payer and provider applications, it can be used to check if systems like insurance claims, eligibility checks, and medical decision tools are working properly and meeting regulations. In the life sciences sector, SQE can create complete sets of tests for research platforms like clinical trial management systems and laboratory informatics platforms.

Quantifiable business impact

Organizations adopting SQE can see improvements across various key performance metrics.

Figure 1: Business Impact with SQE

These improvements translate into faster go-to-market cycles. SQE can serve as a business accelerator, helping healthcare ecosystem players to roll out features and products faster.

Why it matters for CXOs and Healthcare leaders

For decision-makers in healthcare and life sciences, the value of CitiusTech’s SQE goes far beyond traditional IT efficiency.

With this tool, leaders gain a powerful lever to future-proof their technology investments and navigate the increasing complexity of compliance with greater confidence.
It also helps reduce reliance on scarce and specialized QA talent by automating much of the routine testing workload. This enables organizations to scale their digital initiatives more seamlessly, without compromising on quality.
Most importantly, it enhances product reliability, building greater trust among stakeholders, whether they’re clinicians, patients, regulators, or partners.

The master stroke

CitiusTech’s SQE is not just a new way to test software; it’s a smarter way to rechannel human efforts to more strategic tasks. SQE strategically targets the critical 20% of the testing process that often demands 80% of the effort. The result? A mega-shift in how healthcare and life sciences organizations manage quality. A shift that remodels QA from a resource-intensive challenge to a streamlined, cost-benefit center.

With SQE, CitiusTech isn’t just shaping healthcare possibilities. It’s reshaping the outlook towards quality assurance!