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. 2023 Jan 17:9:20552076221144210.
doi: 10.1177/20552076221144210. eCollection 2023 Jan-Dec.

Assessment of distance to primary percutaneous coronary intervention centres in ST-segment elevation myocardial infarction: Overcoming inequalities with process mining tools

Affiliations

Assessment of distance to primary percutaneous coronary intervention centres in ST-segment elevation myocardial infarction: Overcoming inequalities with process mining tools

João Borges-Rosa et al. Digit Health. .

Abstract

Objectives: In ST-segment elevation myocardial infarction (STEMI), time delay between symptom onset and treatment is critical to improve outcome. The expected transport delay between patient location and percutaneous coronary intervention (PCI) centre is paramount for choosing the adequate reperfusion therapy. The "Centro" region of Portugal has heterogeneity in PCI assess due to geographical reasons. We aimed to explore time delays between regions using process mining tools.

Methods: Retrospective observational analysis of patients with STEMI from the Portuguese Registry of Acute Coronary Syndromes. We collected information on geographical area of symptom onset, reperfusion option, and in-hospital mortality. We built a national and a regional patient's flow models by using a process mining methodology based on parallel activity-based log inference algorithm.

Results: Totally, 8956 patients (75% male, 48% from 51 to 70 years) were included in the national model. Most patients (73%) had primary PCI, with the median time between admission and treatment <120 minutes in every region; "Centro" had the longest delay. In the regional model corresponding to the "Centro" region of Portugal divided by districts, only 61% had primary PCI, with "Guarda" (05:04) and "Castelo Branco" (06:50) showing longer delays between diagnosis and reperfusion than "Coimbra" (01:19). For both models, in-hospital mortality was higher for those without reperfusion therapy compared to PCI and fibrinolysis.

Conclusion: Process mining tools help to understand referencing networks visually, easily highlighting its inefficiencies and potential needs for improvement. A new PCI centre in the "Centro" region is critical to offer timely first-line treatment to their population.

Keywords: Big data analytics; ST-segment elevation myocardial infarction; clinical pathways; percutaneous coronary intervention; process mining tools.

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Conflict of interest statement

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Figures

Figure 1.
Figure 1.
Patient inclusion flowchart.
Figure 2.
Figure 2.
(A) The seven regions of Portugal, according to NUTS II (adapted with permission from: Instituto Nacional de Estatística, IP – Portugal); (B) the “Centro” region, with PCI centres identified by green dots (“Leiria’s” P-PCI centre not portrayed) and cities represented as black dots; locations distancing more than 60 km (yellow line) or 90 km (red line) from PCI centres (adapted with permission from “Proposta de atualização da Rede de Referenciação de Cardiologia, elaborada pelo Programa Nacional para as Doenças Cérebro-Cardiovasculares da Direção-Geral da Saúde e aprovada pelo Exmo Sr. Ministro da Saúde, Dr Fernando Leal da Costa em 02/11/2015”).
Figure 3.
Figure 3.
(A) National model: patients’ paths according to region of origin. Colour gradient (bottom, right) in nodes changes from green to red, representing the number of patients in each node, with green demonstrating lower number of patients, while red shows the opposite. Colour gradient in arrows changes from green to red, representing median time between two nodes, with red demonstrating higher duration, while green shows shorter median time delays. (B) Absolute and relative number of each region, regarding treatment option and its time delay. Letters from “a” to “s” represent arrows depicted in the panel (A), linking each region to the treatment chosen; for each one is mentioned the absolute and relative number of patients, as the time delay between nodes. Abbreviations: HH:MM: hours:minutes; NA: not applicable; P-PCI: primary percutaneous coronary intervention.
Figure 4.
Figure 4.
(A) Regional model: patients’ paths according to region of origin. Colour gradient (bottom, right) in nodes changes from green to red, representing the number of patients in each node, with green demonstrating lower number of patients, while red shows the opposite. Colour gradient in arrows changes from green to red, representing median time between two nodes, with red demonstrating higher duration, while green shows shorter median time delays. (B) Absolute and relative number of each region, regarding treatment option and its time delay. Letters from “a” to “o” represent arrows depicted in the panel (A), linking each region to the treatment chosen; for each one is mentioned the absolute and relative number of patients, as the time delay between nodes. Abbreviations: HH:MM: hours:minutes; NA: not applicable; P-PCI: primary percutaneous coronary intervention.

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