The Role of Data Quality Engineering in Strengthening Trust and Transparency in Medicare Systems - Sripathi Nagababu (International Journal of Intelligent Systems and Applications in Engineering, 2026)
The increasing number of issues surrounding the reliability of the Medicare data ecosystem is caused by its fragmentation of data flows, heterogeneity of integrations of various systems involved, and inconsistent validation processes for claim information, eligibility data, and data on providers. All these problems undermine the transparency level and decrease the level of stakeholder trust regarding regulation and management processes. In this regard, the article considers the concept of data quality engineering in the context of building the level of trust and improving transparency of Medicare systems through the implementation of structured data validation, governance, and automation processes at different stages of the data lifecycle. It introduces the concept of the trust-centric approach, according to which data integrity should be considered a prerequisite for processing. Additionally, by integrating automation and centralized monitoring, one is able to conduct ongoing monitoring of the quality of the data being used. Governance is noted to be important for facilitating accountability, standardized validation processes, and compliance with regulatory requirements. The article further addresses adaptive methods of validating that can help identify any emerging anomalies beyond the existing rules. In summary, the main takeaways from the paper are that when the abovementioned elements are combined, more trust can be built in decision-making in Medicare.