Monitoring healthcare processes, such as surgical outcomes, with a keen focus on detecting changes and unnatural conditions at an early stage is crucial for healthcare professionals and administrators. In line with this goal, control charts, which are the most popular tool in the field of Statistical Process Monitoring, are widely employed to monitor therapeutic processes. Healthcare processes are often characterized by a multistage structure in which several components, states or stages form the final products or outcomes. In such complex scenarios, Multistage Process Monitoring (MPM) techniques become invaluable for monitoring distinct states of the process over time. However, the healthcare sector has seen limited studies employing MPM. This study aims to fill this gap by developing an MPM control chart tailored for healthcare data to promote early detection, confirmation, and patient safety. As it is important to detect unnatural conditions in healthcare processes at an early stage, the statistical control charts are combined with machine learning techniques (i.e., we deal with Intelligent Control Charting, ICC) to enhance detection ability. Through Monte Carlo simulations, our method demonstrates better performance compared to its statistical counterparts. To underline the practical application of the proposed ICC framework, real data from a two-stage thyroid cancer surgery is utilized. This real-world case serves as a compelling illustration of the effectiveness of the developed MPM control chart in a healthcare setting.

Although statistical literacy has become a key competence in today’s data-driven society, it is usually not a part of statistics education. To address this issue, we propose an innovative concept for a conference-like seminar on the topic of statistical literacy. This seminar draws attention to the relevance and importance of statistical literacy, and moreover, students are made aware of the process of science communication and are introduced to the peer review process for the assessment of scientific papers. In the summer term 2020, the seminar was conducted as a joint project by the University of Hamburg, the University of Muenster and the Joachim Herz Foundation. In this paper, we present the concept of the seminar and our experience with this concept in the summer term 2020.