Case Study
Redefining Health Care With Test Automation
FireFlink solved healthcare organization's challenges with data-driven testing, NLP-based evaluations, and precise test scenarios for accurate medical suggestions and patient allocation. Discover how FireFlink improved their testing process. Read on.
Transformation Summary
FireFlink streamlined healthcare application testing through data-driven automation and NLP-based validations, enabling accurate medical recommendations, patient assessments, and practitioner allocation. Read on to discover how FireFlink improved testing efficiency, quality, and release confidence.
Problem Statement
The organization's goal is to provide patients from all over the world with high-quality healthcare that is both affordable and accessible. The group has spent decades working together to earn a reputation for providing high-quality consulting services and a healthcare market to an expanding population. Doctors, pharmacists, psychologists, and many other skilled specialists have come together to form a robust professional community that is connected via a network of applications. They have web and mobile applications that respond to user concerns and offer accurate medical diagnosis and treatment recommendations.
Testing Implementation
As a progressive software organization, they required testing software that matched their ideologies. They encountered several challenges when it came to software tests because they maintained or carried out their healthcare services solely through their web and mobile-based applications. With millions of patients using their applications each year to find answers to their ailments, the application has the functionality to list a variety of symptoms and complications. These are physical symptoms that users or patients are experiencing, and the app provides reasonably accurate suggestions concerning their ailments. The suggestion can range from something as simple as taking vitamins orally to something as drastic as surgery. The application required test automation solutions in order to accurately guide its users or patients to the correct diagnosis. During the COVID pandemic, the organization saw a surge in user activity. The patients' use of wearable monitors to monitor their health stability generated a significant amount of data that needed to be compared to a predetermined parameter. Test automation validations were required so that the appropriate specialist could be suggested for a patient when they entered a list of symptoms. This is done to guarantee that the patient receives a prompt and effective remedy for their issues.
FireFlink Solution
FireFlink created several test automation strategies to address the various test automation problems the organization faced. Team FireFlink approached the subject of accurately suggesting the right set of treatments for the patient's inputs by conducting data-driven testing. We used an external document that contained all of the possible outcomes to a set of sample inputs to validate if the patient was suggested with desired suggestions. We were able to perform test automation validations with greater precision this way. Once the assessment began and reports were generated, the reports were verified within FireFlink. We evaluated the reports generated from the patient assessments and classified the results into high, medium, and low bands using test automation. Predefined NLPs in FireFlink allow for similar evaluations. Test scenarios were also created to verify that the patient is assigned to the correct medical practitioner. To summarize, we correctly defined parameters within the automation test scripts using simple in-built NLP automation steps. We also used test data documents with clearly drawn inputs. Even one cell within a document can be used by a test engineer to retrieve data. To support the results that were shown, validation NLPs were developed.