Process mining in healthcare: a systematised literature review

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 IntroductionThe 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. 2Process mining is a broad area of literature that received eno...

Towards Goal-Oriented Process Mining

“…Our literature reviews [3,4] show that process mining has neglected the potential benefits of goal models so far. Accordingly, in this paper, the goal-oriented method GoPED is proposed.…”

“…We have conducted two systematic literature reviews to consider the state of the art in the domains that the research builds upon. The first review [4] provides an overview of process mining in general, and then an example of application to the healthcare domain in particular. We concluded that process mining is a growing research topic (with 2371 publications at the time), particularly in the recent ten years.…”

“…The first phase involves two systematic literature reviews related to the main concepts behind the proposed methods. In the first review [4], the status of process mining in general (and in healthcare in particular) was assessed and we concluded that process mining is a growing research topic that emerged in the last decade and that deserves to be better developed. In the second one [3], we focused on goal-oriented process mining.…”

Process Mining in Cardiology: A Literature Review

“…The review by [13] focus on process mining for clinical pathways and described four key trends for future research directions: (1) variants identification and analysis; (2) customization of clinical pathways; (3) self-learning improvement of clinical pathways; and (4) integrated medical process management. The review by [14] found increasing publications in process mining in healthcare and addressed validity issues in the previous review. The most detailed review is that conducted by Rojas et al [15].…”

What Requirements Engineering can Learn from Process Mining

“…The way in which those challenges can affect this approach is yet to be better considered and addressed. In particular, data quality, as the main challenge in process mining research and practice [25], deserves much attention in RE too.…”