Revolutionizing Healthcare Testing: A Non-Invasive Approach to Automation
Healthcare is more at risk of data breaches than ever before.
In 2021, one in three third-party data breaches targeted healthcare organizations. Since 2009, breaches have accounted for the loss, theft, or exposure of more than 340 million healthcare records, with the size of each data breach increasing yearly. As a result, concerns about personally sensitive data privacy are at an all-time high.
Despite these gloomy statistics, there is hope.
While privacy threats expand daily, so do potential solutions, whether from new privacy legislation, the emergence of blockchain, or more robust software security.
On this National Data Privacy Day, we will discuss the current state of data privacy in healthcare. We will also share essential considerations for quality assurance (QA) leaders and the role noninvasive artificial intelligence-driven test automation can play.
Top Data Privacy Challenges in Healthcare
Over the last 10 years, the healthcare industry has undergone tremendous digital transformation, spurred by government efforts to eliminate paper-based clinical practices and facilitate value-based care. The COVID-19 pandemic accelerated the transformation with rising demand for virtual care and telehealth.
QA teams’ primary responsibility is protecting valuable patient data from cyber threats and breaches while adhering to current and emerging data privacy laws. Here are three challenges they need to grapple with:
1. Increasing risks of cyberthreats
You can’t keep things private if they are not secure.
Today’s cyberattackers are becoming more sophisticated and increasingly targeting small hospitals and health centers. One primary reason is that the increasing adoption of cloud and web-based systems makes large amounts of valuable personal health information (PHI) more available. For example, a single patient record could contain a Social Security number, medical history, insurance, and payment.
A recent study found that almost 50% of US clinics, hospitals, and organizations were victims of ransomware in 2021. The average cost of healthcare data breaches in 2022 hit a record high of $10.1 million, which is just the beginning of the expenses associated with an attack.
2. Maintaining compliance with data privacy laws
Highly regulated sectors such as healthcare must comply with a growing number of data privacy regulations. They include the Health Insurance Portability and Accountability Act (HIPAA), the California Consumer Privacy Act, the Health Information Technology for Economic and Clinical Health Act, and the EU’s General Data Protection Regulation.
Regulations are getting more complicated and stringent to adapt to ever-changing technology. Take HIPAA as an example. It requires specific domain knowledge from QA specialists. And HIPAA compliance doesn’t end with an application’s deployment. Instead, frequent audits and updates are necessary. Thus, every QA team must quickly fulfill a long list of requirements and regulatory obligations. Failing to comply can lead to disastrous consequences such as fines, loss of patient trust, lawsuits, and jeopardized patient outcomes. You may even need to remove your software from the market.
3. Greater vulnerabilities from connected devices
Security and compliance concerns continue to grow with the rise of connected healthcare. These issues put a lot of pressure on healthcare software testing, especially when a small team must test multiple releases simultaneously.
Since the onset of the pandemic, many healthcare organizations have accommodated the need for telehealth. A modern healthcare software ecosystem can include diagnostic devices (such as CT, PET, and MRI scanners), life support equipment (ventilators and heart-lung bypass machines, for example), therapeutic equipment, picture archiving and communication systems, and imaging systems.
However, because of the lack of built-in security features, connected devices and patient portals introduced additional cyberattack risks. A recent study found that more than 60% of healthcare organizations reported security incidents on connected devices. It is more critical than ever to review your testing strategy to ensure end-to-end security and compliance throughout the care system.
Four Testing Considerations for Healthcare Data Privacy
A robust software testing strategy helps organizations protect PHI throughout the care system and through any health information exchange. While a “one size fits all” approach is impractical, there are several areas to address to make software testing efficient and impactful.
1. Continuous testing within DevOps
As experts have been saying for some time, “shift left” is a key strategy to improve software quality and security. Automate testing and bake it into the software development life cycle. Developers can get and act on immediate feedback about security and compliance issues in earlier stages.
2. Non-invasive testing
As the name suggests, non-invasive test automation allows teams to test software that does not require access to the underlying source code. Instead, by interacting with software at the interface level, you can test anything a human operator would see. This opens up a number of possibilities for healthcare organizations to ensure that the testing environment is consistent with real user experience without the risk of compromising security or regulatory protocols.
3. Data encryption
Encrypting data between uses is critical for reducing the risks of cyber threats. HIPAA is specific about testing data encryption, whether the data is in transit or at rest. To uphold the HIPAA checklist, QA teams need to do the following:
- Secure encryption keys while only allowing authorized people to access the data.
- Encrypt all types of sensitive data, including those stored elsewhere, such as in the cloud.
- Analyze encryption algorithms, two-way authentication, and other measures.
4. Modern test data management
Test data management (TDM), the process of planning, designing, storing, and retrieving test data, is key to delivering high-quality software and fulfilling regulatory requirements. Given the huge volumes of production data, however, TDM can be time-consuming and error-prone for the QA team. Automation can greatly simplify TDM by doing four things:
- Identifying sensitive PHI and implementing test data masking faster while reducing human errors.
- Enhancing traceability of the test data to test cases and then to requirements.
- Easing maintenance of the central repository of test data to keep it consistent, accurate, and secure.
- Improving the reusability of test data for better data coverage at a lower cost
In a Nutshell
Over the last decades, we have heard that “privacy is dead.” However, in healthcare, stricter legislation and advanced security technologies are proving that the battle for patient data privacy has only just begun. And now is the time for every healthcare organization to add AI-powered test automation platforms to its arsenal.
Whether you are using a connected device, EMR / EHR system, patient portal, mobile app, microservice, mainframe, or anything in between, Eggplant’s noninvasive test automation solution is well-positioned to protect data privacy and optimize user experiences for patients and physicians alike.
Catch up on other privacy-related resources:
- Download this checklist to overcome the challenges of testing in secure environments
- To Err Is Human. Read about the security and privacy benefits of RPA.