Monitoring and analyzing patients’ pathways by the application of Process Mining, SPC, and I-RTLS

Supporting capacity management decisions in healthcare using data-driven process simulation

“…best practices when visualising statistics for validation to domain experts and eliciting input to build, correct, and enhance data-driven simulation models. In parallel, data quality can be improved by facilitating accurate data registration using intuitive and straightforward information system interfaces or by using technologies that support data capturing, such as Real-Time Location Systems (RTLS), which can enrich and validate event logs [48,[87][88][89]. In a second stage, such tools could be refined and combined into an integrated simulation environment that allows domain experts to conduct DDPS analyses independently.…”

Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations

“…Cited research works location event log preparation and interpretation (Senderovich et al, 2016;Muzammal et al, 2018;Wan et al, 2017;Namaki Araghi et al, 2018a) Use of location data for extraction of knowledge (Hwang and Jang, 2017;Sztyler et al, 2016;Ertek et al, 2017;Mazimpaka and Timpf, 2016), (Rojas et al, 2017a;Zheng, 2015a;Tanuja and Govindarajulu, 2017;Ramos et al, 2017;Garaeva et al, 2017;Bao and Wang, 2017), (Zhenjiang et al, 2017;Aryal and Sujing Wang, 2017;Tanuja and Govindarajulu, 2016;Feng Ling et al, 2016), (Lamr and Skrbek, 2016;Blank et al, 2016;Fernandez-Llatas et al, 2015;Zheng, 2015b), (Liao et al, 2015;Tang et al, 2015;Miclo et al, 2015;Jin et al, 2015;Martinez-Millana et al, 2019), (Dogan et al, 2019;Namaki Araghi et al, 2019;Namaki Araghi et al, 2018a;Namaki Araghi et al, 2018b;Araghi et al, 2018) Figure 3: Analysis of the literature of process mining, indoor localization systems, and data mining relevant to the approaches in which the location data were used.…”

Interpretation of Patients’ Location Data to Support the Application of Process Mining Notations

“…(ii) a scale-adaptive method for refining the location of activities within outdoor and indoor environments. Cited research works location event log preparation and interpretation (Senderovich et al, 2016;Muzammal et al, 2018;Wan et al, 2017;Namaki Araghi et al, 2018a) Use of location data for extraction of knowledge (Hwang and Jang, 2017;Sztyler et al, 2016;Ertek et al, 2017;Mazimpaka and Timpf, 2016), (Rojas et al, 2017a;Zheng, 2015a;Tanuja and Govindarajulu, 2017;Ramos et al, 2017;Garaeva et al, 2017;Bao and Wang, 2017), (Zhenjiang et al, 2017;Aryal and Sujing Wang, 2017;Tanuja and Govindarajulu, 2016;Feng Ling et al, 2016), (Lamr and Skrbek, 2016;Blank et al, 2016;Fernandez-Llatas et al, 2015;Zheng, 2015b), (Liao et al, 2015;Tang et al, 2015;Miclo et al, 2015;Jin et al, 2015;Martinez-Millana et al, 2019), (Dogan et al, 2019;Namaki Araghi et al, 2019;Namaki Araghi et al, 2018a;Namaki Araghi et al, 2018b;Araghi et al, 2018) Figure 3: Analysis of the literature of process mining, indoor localization systems, and data mining relevant to the approaches in which the location data were used.…”