The role of process mining tools in STEMI networks: where should we build a new primary PCI centre?. (14th October 2021)

• Record Type: Journal Article
• Authors: Borges-Rosa, J; Oliveira-Santos, M; Simoes, M; Carvalho, P; Ibanez-Sanchez, G; Fernandez-Llatas, C; Costa, M; Monteiro, S; Goncalves, L
• Is Part Of: European heart journal. Volume 42(2021)Supplement 1
• Publication Date: 2021-10-14
• Subjects: Big Data Analysis; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/eurheartj/ehab724.3160
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Background: 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 "Centre" region of Portugal has heterogeneity in PCI assess due to geographical reasons. Purpose: We aimed to explore time delays between regions using process mining (PM) tools. Methods: We retrospectively assessed the Portuguese Registry of Acute Coronary Syndromes for patients with STEMI from October 2010 to September 2019, collecting information on geographical area of symptom onset, reperfusion option, and in-hospital mortality. We used a PM toolkit (PM4H – PMApp Version) to build two models (one national and one regional) that represent the flow of patients in a healthcare system, enhancing time differences between groups. One-way analysis of variance was employed for the global comparison of study variables between groups and post hoc analysis with Bonferroni correction was used for multiple comparisons. Results: Overall, 8956 patients (75% male, 48% from 51 to 70 years) were included in the national model (Fig. 1A), in which primary PCI was the treatment of choice (73%), with the median time between admission and primary PCI <120 minutes in every region; "Lisboa" and "Centro" had the longest delays, (orange arrows). Fibrinolysis was performed in 4.5%, with a median time delay <1 hour in every region. In-hospital mortality was 5%, significantly higher for those without reperfusion therapy compared to PCI and fibrinolysis (10% vs. 4% vs. 4%, P<0.001). In the regional model (Fig. 1B) corresponding to the "Centre" region of Portugal divided by districts (n=773, 74% male, 47% from 51 to 70 years), only 61% had primary PCI, with "Guarda" (05:04) and "Castelo Branco" (06:50) showing significant longer delays between diagnosis and reperfusion treatment (orange and red arrows, respectively) than "Coimbra" (01:19) (green arrow); only 15% of patients from "Castelo Branco" had primary PCI. Fibrinolysis was chosen in 10% of patients, mostly in "Castelo Branco" (53%), followed by "Guarda" (30%), with a median time delay of 39 and 48 minutes, respectively. Regarding mortality, PCI and fibrinolysis groups had similar death rates while those patients without reperfusion had higher mortality (5% vs. 3% vs. 13%, P=0.001). Conclusion: Process mining tools help to understand referencing networks visually, easily highlighting inefficiencies and potential needs for improvement. The "Centre" region of Portugal has lower rates and longer delay to primary PCI partially due to the geographical reasons, with worse outcomes in remote regions. The implementation of a new PCI centre in one of these districts, is critical to offer timely first-line treatment to their population. Funding Acknowledgement: Type of funding sources: None.