Interactive Data Cleaning for Process Mining: A Case Study of an Outpatient Clinic’s Appointment System

Abstract

Hospitals are becoming increasingly aware of the need to improve their processes and data-driven approaches, such as process mining, are gaining attention. When applying process mining techniques in reality , it is widely recognized that real-life data tends to suffer from data quality problems. Consequently, thorough data quality assessment and data cleaning is required. This paper proposes an interactive data cleaning approach for process mining. It encompasses both data-based and discovery-based data quality assessment, showing that both are complementary. To illustrate some key elements of the proposed approach, a case study of an outpatient clinic's appointment system is considered.