Niels Martin

• MSc, PhD
• Assistant Professor at Hasselt University

There are several open-source Process Mining tools available for research purposes. PMApp is an Interactive Process Mining toolkit developed to facilitate process discovery and analysis in healthcare. PMApp is designed to introduce healthcare professionals to Process Mining, simplifying the learning process by reducing the need for extensive coding...

Since its emergence over two decades ago, process mining has flourished as a discipline, with numerous contributions to its theory, widespread practical applications, and mature support by commercial tooling environments. However, its potential for significant organisational impact is hampered by poor quality event data. Process mining starts with...

Surgical process models support improving healthcare provision by facilitating communication and reasoning about processes in the medical domain. Modelling surgical processes is challenging as it requires integrating information that might be fragmented, scattered, and not process-oriented. These challenges can be faced by involving healthcare doma...

Healthcare organisations are becoming increasingly aware of the need to improve their care processes and to manage their scarce resources efficiently to secure high-quality care standards. As these processes are knowledge-intensive and heavily depend on human resources, a comprehensive understanding of the complex relationship between processes and...

The COVID-19 pandemic has highlighted some of the opportunities, problems and barriers facing the application of Artificial Intelligence to the medical domain. It is becoming increasingly important to determine how Artificial Intelligence will help healthcare providers understand and improve the daily practice of medicine. As a part of the Artifici...

This chapter introduces a specific application domain of process mining: healthcare. Healthcare is a very promising domain for process mining given the significant societal value that can be generated by supporting process improvement in a data-driven way. Within a healthcare organisation, a wide variety of processes is being executed, many of them...

Process Mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of Process Mining in organisations has been far more limited. In particular, there is limited understanding of the...

Healthcare managers are confronted with various Capacity Management decisions to determine appropriate levels of resources such as equipment and staff. Given the significant impact of these decisions, they should be taken with great care. The increasing amount of process execution data – i.e. event logs – stored in Hospital Information Systems (HIS...

Real-life event logs, reflecting the actual executions of complex business processes, are faced with numerous data quality issues. Extensive data sanity checks and pre-processing are usually needed before historical data can be used as input to obtain reliable data-driven insights. However, most of the existing algorithms in process mining, a field...

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by s...

Process mining is the research domain focusing on the development of innovative methods to gather insights from event logs. It has been used for various use cases within the healthcare domain with the ambition to instigate evidence-based process improvement. Over the past years, the research interest in process mining in healthcare has been increas...

Process mining is a research domain that enables businesses to analyse and improve their processes by extracting insights from event logs. While determining the root causes of, for example, a negative case outcome can provide valuable insights for business users, only limited research has been conducted to uncover true causal relations within the p...

Recent developments in causal machine learning open perspectives for new approaches that support decision-making in healthcare processes using causal models. In particular, Heterogeneous Treatment Effect (HTE) inference enables the estimation of causal treatment effects for individual cases, offering great potential in a process mining context. At...

Process mining can provide valuable insights in business processes using an event log containing process execution data. Despite the significant potential of process mining to support the analysis and improvement of processes, the reliability of process mining outcomes depends on the quality of the event log. Real-life logs typically suffer from va...

Process mining is a research domain that enables businesses to analyse and improve their processes by extracting insights from event logs. While determining the root causes of, for example, a negative case outcome can provide valuable insights for business users, only limited research has been conducted to uncover true causal relations within the p...

Process mining is an active research domain and has been applied to understand and improve business processes. While significant research has been conducted on the development and improvement of algorithms, evidence on the application of process mining in organizations has been far more limited. In particular, there is limited understanding of the...

Efficient resource management is a critical success factor for all businesses. Correct insights into actual resource profiles, i.e. groups of resources performing similar activity instances, is important for successful knowledge and (human) resource management. To this end, organisational mining, a subfield of Process Mining, focuses on techniques...

Due to the rise of IoT, event data becomes increasingly fine-grained. Faced with such data, process discovery often produces incomprehensible spaghetti-models expressed at a granularity level that doesn’t match the mental model of a business user. One approach is to use event abstraction patterns to transform the event log towards a more coarse-gra...

In healthcare, more and more process execution information is stored in Hospital Information Systems. This data, in conjunction with data-driven process simulation, can be used, e.g. to support hospital management with Capacity Management decisions. However, real-life event logs in healthcare often suffer from data quality issues, affecting the rel...

Since medical processes are hard to be designed by consensus of experts, the use of data available for creating medical processes is a recurrent idea in literature [3, 7, 8]. Data-driven paradigms are named to be a feasible solution in this field that can support medical experts in their daily decisions [20]. Behind this paradigm, there are framewo...

To cope with challenges such as tightening budgets and increased care needs, healthcare organizations are becoming increasingly aware of the need to understand their processes in order to improve them. In this respect, process mining has the unique potential to retrieve process-related insights from process execution data. Despite the wide range of...

Organizations carry out a variety of business processes in order to serve their clients. Usually supported by information technology and systems, process execution data is logged in an event log. Process mining uses this event log to discover the process' control-flow, its performance, information about the resources, etc. A common assumption is th...

In the age of Evidence-Based Medicine, Clinical Guidelines (CGs) are recognized to be an indispensable tool to support physicians in their daily clinical practice. Medical Informatics is expected to play a relevant role in facilitating diffusion and adoption of CGs. However, the past Int. pioneering approaches, often fragmented in many disciplines,...

Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process...

Knowing the availability of human resources for a business process is required, e.g., when allocating resources to work items, or when analyzing the process using a simulation model. In this respect, it should be taken into account that staff members are not permanently available and that they can be involved in multiple processes within the compan...

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 dat...

Batch processing refers to an organization of work in which cases are synchronized such that they can be processed as a group. Prior research has studied batch processing mainly from a deductive angle, trying to identify optimal rules for composing batches. As a consequence, we lack methodological support to investigate according to which rules hum...

Hospitals are becoming more and more aware of the need to manage their business processes. In this respect, process mining is increasingly used to gain insight in healthcare processes, requiring the analysis of event logs originating from the hospital information system. Process mining research mainly focuses on the development of new techniques or...

Operations research techniques are widely used to analyse and optimise emergency department operations. The complex and stochastic nature of an emergency department makes simulation a suitable and frequently used technique. Simulation can provide valuable insights to hospital managers on how to improve the efficiency of an emergency department. How...

When a company wants to use business process simulation to support decision-making, a simulation study needs to be conducted. Using a clear stepwise method can avoid overlooking key activities during the simulation study and improves the study’s credibility towards decision-makers or project sponsors. In this tutorial, a method to perform a simulat...

Business process simulation can support the analysis and improvement of business processes and, hence, is a valuable technique to teach to students. Consequently, introductory simulation courses are included in a multitude of study programs. Besides providing students with theoretical knowledge and getting them acquainted with simulation software,...

Logistics service providers become increasingly aware of the need to collaborate to face challenges such as globalization and the heightened expectations of customers. This paper focuses on horizontal cooperation between logistics service providers in road transportation and introduces two novel conceptual models. Firstly, a decision framework for...

A common phenomenon in operational business processes is batch processing. Batching is used to reduce cost or time by collectively executing several cases at specific activities in a business process. Recently, approaches were developed to explicitly design and execute batch activities in business process models, and to mine batch work from histori...

Learning analytics (LA) has emerged as a field that offers promising new ways to prevent drop-out and aid retention. However, other research suggests that large datasets of learner activity can be used to understand online learning behaviour and improve pedagogy. While the use of LA in language learning has received little attention to date, availa...

My dissertation focuses on the use of event log knowledge, i.e. process mining, to support the development of business process simulation models. Despite the fact that the Process Mining Manifesto highlights this topic as a key research challenge, prior research efforts tend to have a proof-of-concept nature. To this end, this dissertation contribu...

Background: As an emergency department (ED) is a complex adaptive system, the analysis of continuously gathered data is valuable to gain insight in the real-time patient flow. To support the analysis and management of ED operations, relevant data should be provided in an intuitive way. Aim: Within this context, this paper outlines the developmen...

Resources can organise their work in batches, i.e. perform activities on multiple cases simultaneously, concurrently or intentionally defer activity execution to handle multiple cases (quasi-) sequentially. As batching behaviour influences process performance, efforts to gain insight on this matter are valuable. In this respect, this paper uses eve...

Process mining mainly focuses on the retrieval of process models from event logs. As these discovery algorithms make assumptions, performance analyses based on these models can present a biased view. In literature, algorithm-agnostic process metrics have been introduced. Given the critical importance of resources in the light of continuous process...

Resources are a critical component of a business process as they execute the activities. These resources, especially human resources, are not permanently available and tend to be involved in multiple processes. However, a company might wish to analyze or model a single process. To this end, insights need to be gathered on the availability of a reso...

This paper examines the interactions between clients of the Dutch Employee Insurance Agency UWV and their website werk.nl. The interactions taken into account are visits to the website, messages sent, questions asked and complaints filed. The analysis includes a characterization of clients based on their demographic aspects as well as their behavio...

The paper focuses on the use of process mining (PM) to support the construction of business process simulation (BPS) models. Given the useful BPS insights that are available in event logs, further research on this topic is required. To provide a solid basis for future work, this paper presents a structured overview of BPS modeling tasks and how PM...

A resource typically executes a particular activity on a series of cases. When a resource performs an activity on several cases simultaneously, (quasi-) sequentially or concurrently, this is referred to as batch processing. Given its influence on process performance, batch processing needs to be taken into account when modeling business processes f...

Accurately modeling the interarrival times (IAT) is important when constructing a business process simulation model given its influence on process performance metrics such as the average flow time. To this end, the use of real data from information systems is highly relevant as it becomes more readily available. This paper considers event logs, a p...

Similar to other service processes, the process for handling building permit applications is rather unstructured and complex. The goal of this report is to gain insight in the real-life event logs that are provided by five Dutch municipalities as part of the Business Process Intelligence Challenge 2015. Due to the absence of metadata or access to e...

The construction of a business process simulation (BPS) model requires significant modeling efforts. This paper focuses on modeling the interarrival time (IAT) of entities, i.e. the time between the arrival of consecutive entities. Accurately modeling entity arrival is crucial as it influences process performance metrics such as the average waiting...

This paper focuses on the potential of process mining to support the construction of business process simulation (BPS) models. To date, research efforts are scarce and have a rather conceptual nature. Moreover, publications fail to explicit the complex internal structure of a simulation model. The current paper outlines the general structure of a B...

Business process simulation models are typically built using model construction inputs such as documentation, interviews and observations. Due to issues with these information sources, efforts to further improve the realism of simulation models are valuable. Within this context, the present paper focuses on the use of process execution data in simu...