Discovering role interaction models in the Emergency Room using Process Mining

Alvarez, Camilo; Rojas, Eric; Arias, Michael; Muñoz-Gama, Jorge; Sepúlveda, Marcos; Herskovic, Valeria; Capurro, Daniel

doi:10.1016/j.jbi.2017.12.015

Cited by 73 publications

(35 citation statements)

References 34 publications

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“…In [25], the control-flow perspective is analyzed, i.e., in which order patient care is performed in an emergency room. In [28], it is analyzed how different healthcare professionals interact to care for patients. In this article, these views are complemented, also taking into account the patient's perspective.…”

Section: Discussionmentioning

confidence: 99%

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Mapping the Patient’s Journey in Healthcare through Process Mining

Arias

Rojas

Aguirre

et al. 2020

IJERPH

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Nowadays, assessing and improving customer experience has become a priority, and has emerged as a key differentiator for business and organizations worldwide. A customer journey (CJ) is a strategic tool, a map of the steps customers follow when engaging with a company or organization to obtain a product or service. The increase of the need to obtain knowledge about customers’ perceptions and feelings when interacting with participants, touchpoints, and channels through different stages of the customer life cycle. This study aims to describe the application of process mining techniques in healthcare as a tool to asses customer journeys. The appropriateness of the approach presented is illustrated through a case study of a key healthcare process. Results depict how a healthcare process can be mapped through the CJ components, and its analysis can serve to understand and improve the patient’s experience.

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Section: Discussionmentioning

confidence: 99%

“…Journey Maps can be discovered from information stored in event logs. Moreover, a journey can be part of any healthcare process such as inpatient episodes [28]), outpatient visits, diagnostic test paths, telemedicine paths, and online patient portal paths [27].…”

Section: Process Mining In Healthcare As a Customer Journey Mapping Toolmentioning

confidence: 99%

Mapping the Patient’s Journey in Healthcare through Process Mining

Arias

Rojas

Aguirre

et al. 2020

IJERPH

Self Cite

View full text Add to dashboard Cite

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“…The process mining method is one of the important and useful among other methods that enable the processes analysis behavior for discovering, conformance checking and enhancing [35,36] However, the process mining approaches try to analyze the process based on the event log label strings, without considering the semantics behind the label. A semantic approach on the event logs could overcome this main problem and could enable the reuse and sharing of the knowledge [26,30,35,36].…”

Section: Discussionmentioning

confidence: 99%

Hospital Management Based On Semantic Process Mining: A Systematic Review

Jangi

Moghbeli

Ghaffari

et al. 2019

Front Health Inform

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Introduction: Semantic Process Mining is the extension field of process mining that is based on getting knowledge of conceptual event logs (based on ontologies) for analyzing frequent and rare processes. In the healthcare studies, semantic process mining has been used in different hospitals in order to improve processes.Material and Methods: A review of the usages of semantic process mining in hospitals is done. This review contains 65 articles from PubMed, dblp and Google scholar. It is searched from 2000 to 2017. One of them was duplicated and finally, we received 64 articles. Data were extracted according to PRISMA guidelines.Results: Out of 64 articles, 6 of them were related with inclusion and exclusion criteria. Most of them detect business process mining. In 80% of studies, the semantic process mining was useful and effective to improve hospital processes and improve its management.Conclusion: This review can show an overview the application of process mining in hospitals. It can help researchers to compare semantic process mining with other methods for improving processes in hospitals and finally, it shows the use of semantic process mining to enhance hospitals processes.

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“…There is a requirement not only to include health behaviour but also mental health, social determinants, and individual preferences to achieve a full precision medicine-based care [ 19 ]. Accordingly, there is a burden to stratify individuals built on their behaviour rather than in their disease [ 32 ]. In this regard, Process Mining technologies has been probed useful for creating individualised behaviour models [ 33 ].…”

Section: Related Workmentioning

confidence: 99%

Dynamic Models Supporting Personalised Chronic Disease Management through Healthcare Sensors with Interactive Process Mining

Valero-Ramón

Fernández-Llatas

Valdivieso

2020

Sensors

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Rich streams of continuous data are available through Smart Sensors representing a unique opportunity to develop and analyse risk models in healthcare and extract knowledge from data. There is a niche for developing new algorithms, and visualisation and decision support tools to assist health professionals in chronic disease management incorporating data generated through smart sensors in a more precise and personalised manner. However, current understanding of risk models relies on static snapshots of health variables or measures, rather than ongoing and dynamic feedback loops of behaviour, considering changes and different states of patients and diseases. The rationale of this work is to introduce a new method for discovering dynamic risk models for chronic diseases, based on patients’ dynamic behaviour provided by health sensors, using Process Mining techniques. Results show the viability of this method, three dynamic models have been discovered for the chronic diseases hypertension, obesity, and diabetes, based on the dynamic behaviour of metabolic risk factors associated. This information would support health professionals to translate a one-fits-all current approach to treatments and care, to a personalised medicine strategy, that fits treatments built on patients’ unique behaviour thanks to dynamic risk modelling taking advantage of the amount data generated by smart sensors.

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Discovering role interaction models in the Emergency Room using Process Mining

Abstract: This study allows the discovery of role interaction models through the use of real-life clinical data and process mining techniques. Results show a useful way of providing relevant insights about how healthcare professionals collaborate, uncovering opportunities for process improvement.

Cited by 73 publications

References 34 publications

Mapping the Patient’s Journey in Healthcare through Process Mining

Mapping the Patient’s Journey in Healthcare through Process Mining

Hospital Management Based On Semantic Process Mining: A Systematic Review

Dynamic Models Supporting Personalised Chronic Disease Management through Healthcare Sensors with Interactive Process Mining

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