Unique Challenges of Healthcare Application Testing: Why It Is So Different
Voltaire, Winston Churchill, and most recently, Uncle Ben from Spiderman, all highlighted the concept of greater responsibility that comes with greater power. In the field of healthcare application testing, it has a simple meaning: If you can stop something bad from happening, do it.
However, in a recent study by Keysight and HIMSS, 2/3 of providers surveyed struggle to scale testing to meet future requirements. Today’s healthcare software testing presents a unique set of challenges due to the critical nature of the industry. This article will delve into five emerging challenges that make healthcare application testing different from other domains. By understanding and addressing these hurdles, QA teams can choose the most reliable and affordable tools, empowering them to ensure the delivery of quality digital health solutions.
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Reliability: Ensuring performance for connected medical applications
The consequences of unreliable software in healthcare can have severe implications, especially in today's landscape of more customized and interfaced electronic medical record (EMR) systems.
A 2020 study by the University of Utah Health found that EMR systems failed to detect up to 33% of drug interactions and medication errors that could injure or kill patients. One reason is that hospitals customize their EMR systems to meet their unique requirements, making it difficult to keep up with the latest updates. Consequently, a serious drug interaction that triggers an EMR system warning at one hospital could fail to do so at another. The increasing integration of EMR systems with connected medical devices and other healthcare software amplifies the risks to patient safety due to software glitches, user errors, or other flaws.
Figure 1. The increasing integration of EMR systems with connected medical devices and other healthcare software poses new challenges to healthcare application testing.
Healthcare applications must deliver error-free performance regardless of workload or databases. Achieving reliability requires a quality-first approach to healthcare software testing and development. Comprehensive testing coverage, including smoke, functional, and performance testing, are essential to identify and resolve any potential issues. Additionally, implementing advanced analytics to assess release readiness can further enhance reliability and ensure continuous quality improvement of critical healthcare applications.
Interoperability: Expanding features through APIs in digital health technologies
Interoperability in healthcare has transitioned from a best practice to a regulatory requirement in recent years. Countries like the US and Canada have embraced standards such as Fast Healthcare Information Resources (FHIR) to facilitate seamless data exchange. An exponemtial growth of APIs enables healthcare software developers to expand the feature set of their products without starting from scratch, saving time and resources.
As a result, interoperability testing has become a top priority in healthcare software development due to the increasing emphasis on seamless data exchange between different systems. Seamless integration testing across devices and platforms ensures that APIs function properly and communicate effectively with the target systems. API compatibility checks can verify that the APIs conform to industry standards, enabling smooth integration and safe data exchange. According to the HIMSS study, 76% of respondents identify the most important capability of a test automation platform as interoperability testing.
Figure 2. The rise of interoperability testing in healthcare
Ease of use: Intuitive experience for diverse users
In the highly competitive digital healthcare market, high usability is crucial due to the diverse range of users, from busy hospital staff to patients managing their conditions. Did you know that 28% of patients switched providers due to poor digital experiences since the pandemic? A seamless user experience testing is critical to thriving in the $211 billion digital health market.
Therefore, the user interface (UI) and user experience (UX) design of healthcare applications must prioritize accessibility, conciseness, and intuitiveness. However, user experience (UX) testing in healthcare faces complexities due to multiple modules, frequent updates, and the need to address key areas such as functionality, localization, performance, accessibility, and the entire user experience. QA teams encounter time and resource constraints when addressing such extensive testing requirements. Traditional manual testing becomes time-consuming, leaving various potential user journeys unexamined.
To navigate this testing landscape efficiently, test automation tools leverage machine learning (ML) algorithms. By analyzing historical patterns, prioritized cases, and real-user insights, ML algorithms can auto-generate test cases and meticulously scrutinize each user interaction, ensuring optimal digital experiences.
Privacy: Safeguarding sensitive patient data
Privacy and security are of paramount importance in healthcare software systems, given the sensitive nature of patient data. Compliance with data protection regulations, such as HIPAA and the NHS White Paper, is crucial to safeguard patient information. More healthcare QA teams have employed non-invasive solutions, such as Eggplant, to enhance data privacy and security in healthcare software testing. Unlike invasive approaches, non-invasive testing does not require agents installed on endpoints, parsing through the code base, or parsing through the documents object model (DOM). This approach ensures that patient data remains secure during the testing process, reducing the risk of compliance violations or unauthorized access.
Figure 3. Five emerging challenges in healthcare application testing
Compliance: Meeting industry standards requirements
Compliance in healthcare software is an ongoing commitment. Regulations and industry practices evolve over time, requiring continuous monitoring and updates to ensure ongoing compliance. Regular assessments and monitoring help identify any gaps or changes in regulatory requirements, allowing software teams to address them promptly.
One of the key challenges is scaling testing coverage. The sheer volume of test cases required for compliance, covering areas such as data protection, privacy, security measures, and adherence to industry standards, can overwhelm manual testing processes. On the other hand, automated tests can execute a vast number of test cases, which ensures that all aspects, such as data protection, privacy, security measures, and adherence to industry standards, are thoroughly examined. It gives the QA team peace of mind knowing that their medical software is being tested extensively for compliance, reducing the risk of non-compliance issues. Moreover, traditional manual testing lacks repeatability, hindering the ability to achieve accurate and reliable results across multiple iterations of compliance testing. Additionally, manual testing may find it tedious to provide the required documentation, making it difficult to track and verify compliance efforts during audits and inspections.
The good news is that automated EMR testing solutions can execute a vast number of test cases consistently, ensuring comprehensive coverage of compliance requirements. Automated test scripts capture and record test results, making it easier to track and verify compliance efforts.
Adopting test automation tools in the AI future
The healthcare software testing industry is undergoing a transformative shift, with the adoption of automated software testing solutions expected to triple within five years, according to the HIMSS study. Immense responsibility is placed upon QA leaders to keep pace with the fast-paced digital innovations and deliver high-quality software that meets the demands of this ever-evolving landscape.
In this context, embracing AI-powered test automation takes on a profound significance. AI has the potential to reinvent the way testing is done, creating value by improving testing efficiency, coverage, and accuracy. Healthcare organizations can streamline testing workflows, reduce manual efforts, and allocate more time for business testers, such as nurses and clinicians, to focus on what matters most – providing care to patients.
