Process mining tools: where should we build another PCI centre to reduce STEMI mortality?

Author:

Borges-Rosa J1,Oliveira-Santos M1,Simoes M2,Teixeira C3,Ibanez-Sanchez G4,Fernandez-Llatas C4,Monteiro S1,Carvalho P5,Goncalves L1

Affiliation:

1. University Hospitals of Coimbra, Coimbra, Portugal

2. Coimbra Institute for Biomedical Imaging and Translational Research, Coimbra, Portugal

3. Centre for Informatics and Systems of the University of Coimbra, Coimbra, Portugal

4. Universitat Politècnica de València, Valencia, Spain

5. University of Coimbra, Coimbra, Portugal

Abstract

Abstract Introduction The expected delay of transport between patient location and percutaneous coronary intervention (PCI) centre is paramount for choosing the adequate reperfusion therapy in ST-segment elevation myocardial infarction (STEMI). The central region of Portugal has heterogeneity in PCI assess due to geographical reasons. However, this data is usually presented numerically without providing a visual distribution of patients. Purpose We aimed to analyse the impact of distance to PCI centres on mortality in patients with STEMI through visual maps of patients' flow by using an experimental process mining tool, integrated in EIT Health's project PATHWAYS. Methods Using the Portuguese Registry of Acute Coronary Syndromes (ProACS), we retrospectively assessed patients with an established diagnosis of STEMI, geographical presentation specified, reperfusion option identified (PCI, fibrinolysis or no reperfusion), short-term outcomes defined as discharge or in-hospital death. With the 2 317 patients that fulfilled the criteria, we used a process mining tool to build national and regional models that represent the flow of patients in a healthcare system, enhancing differences between groups. Results Colour gradient in nodes and arrows changes from green to red, with green representing a lower number of patients as opposed to red. In the national model, most patients from all regions had PCI. Mortality was similar between PCI and fibrinolysis groups (4%) but higher in those without reperfusion (9%). In the central region model, one third of the patients were more than 120 minutes away from a PCI centre. Despite that, almost one third of these patients had PCI instead of fibrinolysis. In this model, fibrinolytic therapy had higher in-hospital survival rate than PCI (98% vs. 94%). Overall mortality was higher in the central model compared with the national model (6.92% vs. 5%). Central region had less PCI (53% vs. 73%), more fibrinolysis (15% vs. 7%) and more patients with no reperfusion (32% vs. 20%). Conclusion In the ProACS registry, mortality was higher in the central region compared with national data. Even though global interpretation of these findings is limited by underrepresentation from certain central areas, process mining offers an easily understandable view of patients flow. With its statistical upgrade and continuous development, this tool will facilitate the analysis of big data and comparison between groups. Funding Acknowledgement Type of funding source: Public grant(s) – EU funding. Main funding source(s): EIT Health

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine

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