Tracing Real-World Patient Pathway by Harnessing Healthcare Administrative Claims

In healthcare research, the utilization of Healthcare Administrative Claims (HAC) data has gained increasing importance. Retrospective observational studies of real-world patient pathways can highly benefit from accurate HAC data analysis. They provide valuable insights into the sequential and temporal progression of patient interactions within the healthcare system. This type of analysis helps identify factors that influence treatment effectiveness, resource utilization, and healthcare quality. Consequently, it contributes to evidence-based decision-making and better healthcare policies. Effectively harnessing the potential of HAC data requires careful data processing due to several challenges. We proposed a stepwise approach for HAC data processing that involves several key steps, including population selection, data enrichment, establishment of an index date, application of inclusion/exclusion criteria, identification of clinical events, and determination of pathway milestones. These steps collectively construct a structured practical framework for healthcare administrative data analysis.