Declarative process mining in healthcare

Rovani, Marcella; Maggi, Fabrizio Maria; Leoni, Massimiliano de; Aalst, Wil M. P. van der

doi:10.1016/j.eswa.2015.07.040

Cited by 121 publications

(83 citation statements)

References 54 publications

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“…Although imperative process modeling languages can also support the flexibility by design principle, declarative process modeling languages are better suited for modeling loosely framed processes as they do not require enumerating the potentially large number of valid process variations (Rovani et al, 2015). Generally, given the large number of allowed process variations in loosely framed processes, less effort will be required to describe the properties that make variations valid or invalid compared to enumerating all the valid process variations explicitly like imperative languages (Goedertier et al, 2015;van der Aalst, 2013).…”

Section: Declare As a Foundationmentioning

confidence: 99%

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Mertens

Gailly

Poels

2017

Expert Systems with Applications

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Abstract. Modeling loosely framed and knowledge-intensive business processes with the currently available process modeling languages is very challenging. Some lack the flexibility to model this type of processes, while others are missing one or more perspectives needed to add the necessary level of detail to the models. In this paper we have composed a list of requirements that a modeling language should fulfil in order to adequately support the modeling of this type of processes. Based on these requirements, a metamodel for a new modeling language was developed that satisfies them all. The new language, called DeciClare, incorporates parts of several existing modeling languages, integrating them with new solutions to requirements thathad not yet been met. Deciclare is a declarative modeling language at its core, and therefore, can inherently deal with the flexibility required to model loosely framed processes. The complementary resource and data perspectives add the capability to reason about, respectively, resources and data values. The latter makes it possible to encapsulate the knowledge that governs the process flow by offering support for decision modeling. The abstract syntax of DeciClare has been implemented in the form of an Ecore model. Based on this implementation, the language-domain appropriateness of the language was validated by domain experts using the arm fracture case as application scenario.

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Section: Declare As a Foundationmentioning

confidence: 99%

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Mertens

Gailly

Poels

2017

Expert Systems with Applications

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“…Seven papers used declarative process mining and its enhancements [26]- [32]. Declarative process mining involves identifying possible execution paths for bridging event data reflecting the clinical reality and clinical guidelines describing best-practice.…”

Section: Resultsmentioning

confidence: 99%

Process mining in oncology: A literature review

Kurniati

Johnson

Hogg³

et al. 2016

2016 6th International Conference on Information Communication and Management (ICICM)

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Abstract-Process mining, an emerging data analytics method, has been used effectively in various healthcare contexts including oncology, the study of cancer. Cancer is a complex disease with many complicated care requirements and there is an urgent need to improve the cost and clinical effectiveness of cancer care pathways. Process mining of the e-health records of cancer patients may play an important future role and this paper presents a literature review of process mining in oncology as a contribution to this research. The search produced 758 articles which were manually reviewed by title, abstract, and full paper text review to develop the original pool of papers. An in-depth ancestor search was used to gather additional articles from the references of the original pool. These steps resulted in 37 papers. Through a thematic review process, the papers were analysed and five themes emerged. These were: 1) process and data types; 2) research questions; 3) techniques, perspectives and tools; 4) methodologies; 5) limitations and future work. This review can: (i) highlight the potential value of process mining for improving cancer care processes (ii) provide a useful overview of the current work undertaken; (iii) help researchers to choose process mining algorithms, techniques, tools, methodologies and approaches; and (iv) identify research opportunities in this new field of study.

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“…Pathways are a distinctive type of clinical guidelines, which specify each step in the care process, rather than stating broad principles that practitioners should follow [17]. Nevertheless, it was observed that there is a gap between these recommendations and actual practices since healthcare processes have large healthcare facilities, multidisciplinary and highly complicated structures, and flexible patient flows [18,19].…”

Section: Evidence-based Medicinementioning

confidence: 99%

A Goal-Driven Evaluation Method Based On Process Mining for Healthcare Processes

Erdogan

Tarhan

2018

Applied Sciences

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As a business processes management technique, process mining (PM) has been applied in many domains in the last decade. In healthcare, where most processes are complex, variable, dynamic, and multi-disciplinary in nature, application of this technique is growing, yet challenging. Therefore, this study aims to introduce a goal-driven process evaluation method based on PM for healthcare processes. The proposed method comprises the following steps: defining goals and questions, data extraction, data preprocessing, log and pattern inspection, PM analysis and generating answers to questions, evaluating results, and initiating proposals for process improvements. The proposed method was applied in a case study on the surgery process of a university hospital in Turkey, which revealed for quantitative insights into the process. Bottlenecks and deviations that were crucial for determining measures (e.g., data and performance information) were identified to improve the efficiency of the surgery process. Our initial experience using the proposed method shows that it has potential for initiating process improvements by guiding the use of PM techniques in the healthcare domain.

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Declarative process mining in healthcare

Cited by 121 publications

References 54 publications

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Towards a decision-aware declarative process modeling language for knowledge-intensive processes

Process mining in oncology: A literature review

A Goal-Driven Evaluation Method Based On Process Mining for Healthcare Processes

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