An Investigation to Identify Factors that Lead to Delay in Healthcare Reimbursement Process: A Brazilian case

Abstract

Abstract Healthcare reimbursement has had a tremendous impact on healthcare institutions and the economy. The healthcare reimbursement process consists of coding, billing, and payment based on the care provided to the patient. The rapid development of new medical treatments and procedures and changes in regulations and policies have been increasing the complexity of the reimbursement process, resulting in financial, operational, and care delivery issues for healthcare institutions. Therefore, methods of process analysis, such as process mining, have been used as a basic strategy to improve the organizational effectiveness of healthcare institutions. In this context, the main objective of this study is to propose an approach to investigate the factors that may cause delays in the reimbursement process using a combination of process mining and data mining techniques to extract information from the process data and support decision-making. To accomplish this analysis, process mining is applied to map the reimbursement process from the event log and to determine possible bottlenecks. In contrast, data mining is used to identify frequent patterns and interesting associations in the process data. Finally, by applying the proposed approach to a real case of a healthcare institution in Brazil, we extracted valuable insights regarding process execution and confirmed the effectiveness and potential of combining process mining and the association rules mining techniques.