Healthcare applications are well-known for their inherent complexity, heterogeneous structure, variety in data leading to data integration issues and most importantly, the challenge of maintaining a variety of medical plans, enrolments and annual contracts. All of these lead to difficulty in finding adequate test data to support testing for the frequent IT releases.
Reasons that make test data management a challenge in healthcare:
Upstream and downstream dependencies:
Dependencies between different systems like provider environment, claims processing, patient records and static data like ICD10 codes, diagnostic codes etc. make it difficult to pull the required test data. Changes made for any release are never solitary in terms of system impact. Due to the interdependency between systems, any minor change has cross-system impacts, at least where testing is concerned.
Healthcare Standards and Laws:
Like banking and insurance, healthcare is also governed by state and federal laws like HIPAA that make it mandatory for all stakeholders to guard and protect patient information. These laws vary from country to country. Healthcare insurance firms that have a presence across nations need to ensure their applications are always in compliance.
Gender and age specific processing:
Most processing in healthcare is specific to gender and age of patient. Contracts, treatments, diagnostic codes all differ based on gender and age.
Contracts and payments:
Healthcare applications are characterised by their massive size, variety and complexity. Contracts also frequently change due to changing patient preferences and market trends.
Better testing through better test data management
The success of your testing depends on how good your test data is. A good test data set mirrors your production data and is correctly proportioned to your testing needs.
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