Emily Yan, Product Marketing Manager at Keysight Technologies
The COVID-19 pandemic set the stage for an unprecedented acceleration in digital transformation across industries, especially in the healthcare sector. In an era where the healthcare software ecosystem accounts for a prodigious 30% of global data, there’s no turning back from the cusp of this digital revolution.
However, with greater digitalization comes a labyrinth of intricate software systems and a more stringent regulatory landscape, making the need for rigorous and efficient software testing more pressing than ever.
To gain insights into this complex terrain and forecast impending trends, the Healthcare Information and Management Systems Society (HIMSS) and Keysight Technologies conducted a comprehensive survey, named Vital Signs, probing the current state of software testing within the healthcare industry and its desperate call for automation.
The slow horse in a fast-paced digital world: Manual testing
While the world rushes towards automation, the healthcare industry has been relatively slow off the starting block. The HIMSS survey reveals that only a meager 15% of healthcare providers have incorporated test automation platforms into their software development lifecycle (SDLC).
Electronic Medical Records (EMR), with their interwoven, highly customized, and interdependent architecture, have proven to be a Gordian Knot for manual testing. The high-frequency system upgrades often outpace the capabilities of manual testers, leading to only 33% of them expressing satisfaction with their organization’s capacity to scale testing activities.
Manual testers often struggle to access actionable testing analytics and achieve comprehensive test coverage across the panoply of platforms and browsers. This is reflected in the survey, with a scant 38% of manual testers reporting satisfaction in these areas. These stats underscore the urgency to resort to automation to bridge the skill gap and bolster scalability.
An aegrescit mendendo: DIY
The survey shows a curious predilection for a Do It Yourself (DIY) approach to software testing, preferred by over 40% of the respondents.
However, this route is fraught with inefficiencies and stumbling blocks. The most formidable of these hurdles is the dearth of technical expertise necessary for developing and maintaining robust in-house testing solutions. The complexity of healthcare applications, the unruly landscape of automation frameworks, and the multiplicity of programming languages necessitate highly specialized skill sets. Consequently, only 38% of respondents who adopted DIY methods expressed satisfaction with their organization’s strides in enhancing the Quality Assurance (QA) team’s productivity.
A Bold Leap Forward: AI-powered automation
On the brighter side, the survey shows a promising trend: 75% of healthcare providers plan to onboard test automation within the next half-decade. The early adopters are already reaping benefits, with 80% expressing satisfaction with their organization’s ability to scale testing to meet the ever-evolving requirements.
The advent of generative AI tools, such as OpenAI’s ChatGPT, heralds a paradigm shift in the software testing landscape. With its remarkable capability to generate code, ChatGPT paves the way for previously untapped opportunities within the software development process. For example,
- AI in Load & Smoke Testing: AI can emulate realistic user behavior and fabricate corresponding load scenarios, augmenting the veracity and effectiveness of load and smoke tests.
- AI in Security Testing: By pairing AI with machine learning algorithms, testers can simulate advanced cyber-attack scenarios, revealing potential security vulnerabilities that might slip through traditional testing methodologies.
- AI in Compatibility Testing: AI can automate the process of testing applications across different platforms, operating systems, and browsers, trimming down the time and effort required for compatibility testing.
- AI in Integration Testing: AI can conjure up and execute test cases for different combinations of integrated software modules, enhancing the comprehensiveness of integration testing.
The Road Ahead
The landscape of digital healthcare is undergoing rapid transformation, and its impacts on software testing are profound. It’s imperative to stay abreast of the evolving dialogue and start investigating the potential integration of these AI tools into your software testing setup.
If you’re dipping your toes into AI-driven software testing for the first time or contemplating a shift from in-house tools to a commercial platform, the full “Vital Signs” report is an invaluable resource. The survey offers a comprehensive array of findings, best practices, and industry insights to help your organization navigate the future of healthcare software testing. By embracing automation and harnessing the power of AI, healthcare providers can transcend the limitations of manual testing, enhance testing coverage, and ensure the ultimate goal – patient well-being.
Guest article written by: Emily Yan is a Product Marketing Manager at Keysight Technologies, with a focus on automated software testing solutions for healthcare and life sciences. Before joining Keysight, Emily had worked in EDA marketing at Synopsys and led branding and digital media at Fivetran, a data integration startup. Emily holds an MPA degree from Columbia University and dual Bachelor’s degrees in math and economics from UC Berkeley. (LinkedIn)