Process Mining in Cardiology: A Literature Review

Kusuma, G. D. V.; Hall, Marlous; Gale, Chris P; Johnson, Owen

doi:10.17706/ijbbb.2018.8.4.226-236

Cited by 20 publications

(16 citation statements)

References 43 publications

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“…Event log analyses using the descriptors show pathway differences between stroke, infarctus, amputation and TKCD. Indeed, the first two complications are characterized by shorter traces (|σ| q1,m,q3 : (1,3,4) and (2,3,5) vs. (3,5,8) and (4,6,9)), that is to say short and unstructured pathways compared to the other two. This difference between complications is also highlighted by the best final replayability scores: amputation and TCKD have lower scores (R T G : 0.75 and 0.70) compared with those of stroke and infarctus (0.87 and 0.86) because longer and more complex pathways are less easily replayed in a graph than shorter ones.…”

Section: Resultsmentioning

confidence: 99%

“…Since the later systematic review on healthcare, new process mining contributions applied to healthcare have been proposed. Kusuma et al compiled a literature review of process mining in cardiology [5]. Promising opportunities to assist medical experts in care analysis were shown, although few formal process mining methodologies were included.…”

Section: Literature Reviewmentioning

confidence: 99%

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Optimal process mining of timed event logs

Oliveira

Augusto

Jouaneton³

et al. 2020

Information Sciences

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The problem of determining the optimal process model of an event log of traces of events with temporal information is presented. A formal description of the event log and relevant complexity measures are detailed. Then the process model and its replayability score that measures model fitness with respect to the event log are defined. Two process models are formulated, taking into account temporal information. The first, called grid process model, is reminiscent of Petri net unfolding and is a graph with multiple layers of labeled nodes and arcs connecting lower to upper layer nodes. Our second model is an extension of the first. Denoted the time grid process model, it associates a time interval to each arc. Subsequently, a Tabu search algorithm is constructed to determine the optimal process model that maximizes the replayability score subject to the constraints of the maximal number of nodes and arcs. Numerical experiments are conducted to assess the performance of the proposed Tabu search algorithm. Lastly, a healthcare case study was conducted to demonstrate the applicability of our approach for clinical pathway modeling. Special attention was paid on readability, so that final users could beneficially use the process mining results.

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Section: Resultsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Optimal process mining of timed event logs

Oliveira

Augusto

Jouaneton³

et al. 2020

Information Sciences

View full text Add to dashboard Cite

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“…The first stage covered the search of papers from medicine, technology and engineering databases; PubMed, Medline, British Medical Journal Open, ACM DL, Elsevier, ScienceDirect, database systems and logic programming (DBLP), Web of Science and Google Scholar. Keywords for process mining replicated those used in previous literature reviews (Kurniati et al, 2016;Kusuma et al, 2018). To ensure the search obtained papers that cover all relevant conditions related to older people a broad selection of keyword terms was applied following the Medical Subject Headings (MeSH) terms used in the PubMed and Medline databases.…”

Section: Search Processmentioning

confidence: 99%

“…There are a number of recent literature reviews of process mining in healthcare (Rojas, 2016;Erdogan and Tarhan, 2018;Williams et al, 2018) and other reviews which focus on specific healthcare specialties such as cancer (Kurniati et al, 2016) and cardiovascular disease (Kusuma et al, 2018). However, until now there has been no literature review specifically examining process mining for the care of the frail elderly.…”

Section: Introductionmentioning

confidence: 99%

Process Mining in Frail Elderly Care: A Literature Review

Farid

Kamps

Johnson

2019

Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies

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Process mining has proved to be a valuable technique for extracting process knowledge from data within information systems. Much work has been conducted in applying process mining to domains such as logistics, banking, transportation and many areas of the government, including healthcare. Frail elderly people who have an increased risk of adverse outcomes are amongst the main users of healthcare services and understanding healthcare processes for the frail elderly is challenging because of their diverse and complex needs combined with an often high number of co-morbidities. This paper aims to provide an overview of work applying process mining techniques to improving the care of frail elderly people. We conducted a literature search using broad criteria to identify 1,047 potential papers followed by a review of titles, abstract and content which identified eight papers where process mining techniques have been successfully applied to the care of frail elderly people. Our review shows that, to date, there has been limited application of process mining to support this important segment of the population. We summarise the results based on five themes that emerged: types of source data and process; geographical location; analysis methodology; medical domain; and challenges. Our paper concludes with a discussion on the issues and opportunities for process mining to improve the care pathways for frail elderly people.

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“…In Australia, process mining techniques have been used to conduct a comparative analysis of patients' care pathways in four South Australian Hospitals [2], and to undertake performance analysis of patients' length of stay [3]. Insights from these studies and many others [4][5][6] showed potential benefits of utilising process mining techniques in the healthcare domain while also highlighting many challenges associated with varying quality of healthcare data [4,7,8] and the complexity of modelling healthcare processes where variations are the norm rather than the exception. There are several novel and challenging aspects to this study.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Process Mining Analysis of Road Trauma Patient Pathways

Andrews

Wynn

Vallmuur

et al. 2020

IJERPH

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In this paper we report on key findings and lessons from a process mining case study conducted to analyse transport pathways discovered across the time-critical phase of pre-hospital care for persons involved in road traffic crashes in Queensland (Australia). In this study, a case is defined as being an individual patient’s journey from roadside to definitive care. We describe challenges in constructing an event log from source data provided by emergency services and hospitals, including record linkage (no standard patient identifier), and constructing a unified view of response, retrieval, transport and pre-hospital care from interleaving processes of the individual service providers. We analyse three separate cohorts of patients according to their degree of interaction with Queensland Health’s hospital system (C1: no transport required, C2: transported but no Queensland Health hospital, C3: transported and hospitalisation). Variant analysis and subsequent process modelling show high levels of variance in each cohort resulting from a combination of data collection, data linkage and actual differences in process execution. For Cohort 3, automated process modelling generated ’spaghetti’ models. Expert-guided editing resulted in readable models with acceptable fitness, which were used for process analysis. We also conduct a comparative performance analysis of transport segment based on hospital ‘remoteness’. With regard to the field of process mining, we reach various conclusions including (i) in a complex domain, the current crop of automated process algorithms do not generate readable models, however, (ii) such models provide a starting point for expert-guided editing of models (where the tool allows) which can yield models that have acceptable quality and are readable by domain experts, (iii) process improvement opportunities were largely suggested by domain experts (after reviewing analysis results) rather than being directly derived by process mining tools, meaning that the field needs to become more prescriptive (automated derivation of improvement opportunities).

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Process Mining in Cardiology: A Literature Review

Cited by 20 publications

References 43 publications

Optimal process mining of timed event logs

Optimal process mining of timed event logs

Process Mining in Frail Elderly Care: A Literature Review

A Comparative Process Mining Analysis of Road Trauma Patient Pathways

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