Abstract: Process mining is a promising approach that turns event logs into valuable insights about processes. One domain amenable to process mining is healthcare, where an enormous amount of data is generated by care processes, but where realistic care models are seldom available. In this paper, we perform a systematised literature review to assess the status of process mining, particularly in healthcare. We first provide an overview of process mining in general, and in healthcare in particular. Based on 2371 research publications related to process mining, obtained by querying six relevant search engines in May 2016, we found that the trend of publications in this domain has been growing over the past decade, especially in healthcare. Among the eleven existing literature reviews on process mining selected for further analysis, only two are systematised, and only three relate to healthcare. This paper contributes a systematised review in healthcare that is much needed to fill this void. Important challenges specific to healthcare are identified, and threats to the validity of the results are also discussed. Keywords: Process mining, healthcare, care processes, clinical pathways, literature review The number of processes whose event logs are being recorded is highly increasing. Process mining is a promising approach that can use these logs and turn them into valuable insights about processes. In particular, process mining plays an important role as a bridge between traditional model-based process analysis (e.g., simulation) and data analysis techniques (e.g., data mining). This leads into a huge demand for data scientists who are not only able to analyse big data, but also to relate them to real operational processes. According to van der Aalst (2011), process mining techniques are classified into three categories: i) discovery, where a model is being created using the event logs; ii) conformance, where the data generated from the model is compared with the actual data in event logs to compare the model with reality; and iii) enhancement, where the desired data is used to improve or/and extend an existing process model. One of the domains amenable to process mining is healthcare. In this domain, an enormous amount of data is being generated by care processes, but care models that reflect the reality are seldom available. On the other hand, healthcare expenditure is consistently rising (independently of outcomes and countries) and on average it amounts to 10% of the gross domestic product (GDP) of countries across the world (The World Bank, 2015). It is not surprising to see that the demand for high quality care at low cost is increasing, especially with our aging society. Consequently, healthcare service providers are highly motivated to use their data to improve the quality and performance of their care processes and lower their costs. Process mining is an approach that promises to support the analysis and understanding of such processes. Process mining is a broad area of literature that received enormous research interest in the past few years. The objective of this study is to review the literature (and trends) related to process mining and, in particular, to review surveys describing studies that have been conducted in the healthcare domain. In such context, a systematised literature review (SdLR) can help provide insight into this active area. An SdLR is less rigorous and complete than a systematic review (Kitchenham et al., 2009) and is based on the analysis of papers obtained through existing reviews rather than on the direct analysis of a large list of first-hand papers. This paper is a SdLR that first provides a historical trend of the number of publications on process mining in general. Then, it focuses on healthcare processes and current trends. The most relevant papers reviewed in this research area are also discussed in this paper. This SdLR is more systematic and focused on healthcare than most existing reviews, and provides more accurate insight about the status of process mining in healthcare. The organization of this paper is as follows. Section 2 presents an overview of process mining, including history, basic concepts, types, tools and techniques. Then, a typical example of application of process mining activities on an event log in healthcare is presented in Section 3. In the first step of our literature review, a brief analysis of the amount of research done in the process mining area in general is presented in Section 4. Section 5 focuses on process mining in healthcare, with its main contributions categorised and summarised. Section 6 discusses several threats to the validity of the reviews, including this one. Finally, Section 7 provides our conclusions.
Ghasemi and Amyot REF conducted a systematised literature survey which provides an overview of the status of PM in healthcare, and provided initial results from the search process of the systematic review.
Process mining in healthcare: a systematised literature review
IJEH
IJEH
Medicine Computer Science