The growing maturity of Healthcare IT and the digitization of healthcare is improving the quality of care and driving down costs. Nevertheless, the risk of data breaches from the ever increasing interoperability and access to Protected Health Information (PHI) and Personally Identifiable Information (PII) is accelerating. The consequences of a security breach include disruption of operations, cost of fixing IT systems, cost of reporting the incident to federal and state authorities, regulatory fines and class-action lawsuits to business and credibility loss.
Healthcare data breaches
Test coverage vs cyber liability coverage
Data compliance standards (HIPAA, HITECH and Gramm-Leach-Bliley Act) and the implementation of EHR and EMR requirements of the Affordable Care Act (ACA) require healthcare and medical practices organizations to utilize electronic records and data that is secure, and ensure methods are in place to report/recover any lost or stolen information. End-user/Organization misuse in administering and hardware fragmentation across laptops, tablets and smartphones, use of unsecured networks present a growing risk for data loss.
Frequent modification in healthcare regulations makes it a challenge for teams to provide adequate test data for agile/simultaneous releases. Inefficient test planning and coverage can result in data breaches forcing organizations to get Cyber Liability Coverage. This makes Test Data Management all the more relevant. There are only two types of Healthcare organizations right now: those that know they’ve been breached and those that don’t know they’ve been breached – according to a study conducted by Ponemon Institute.
Test data management strategy
With ever increasing complexities and scale of IT applications, quality and reliability of software applications is becoming critical. Test Data Management Strategy plays a very significant role in ensuring that the enterprise applications meet these standards. While delivery of these standards are becoming a real challenge for enterprises, testing teams are expected to follow precise testing methods, while ensuring a high accuracy of test data.
Build a data inventory, replication of the production-like situations, both functionally and technically is also the responsibility of the testing team. A well-defined Test Data Management Strategy can bring down data inefficiencies resulting in availability of secure test data consistently from distributed and heterogeneous data sources.
An effective TDM implementation
TDM works by extracting ‘real’ data from the production environment, applying filters and masking it, so it can be used in the test environment. TDM techniques should address creation of accurate test data where production data is insufficient or unavailable. A structured testing process ensures data to be managed by:
Organizations have data governance teams to review and enforce mitigations to any instances of production data usage in the non-production environment. The team ensures risks are mitigated through data manufacturing, access control, and data masking as applicable. Identifying a right TDM tool and building an appropriate TDM automation strategy brings down both risks and environmental costs.