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Building a new PCI centre with the help of process mining tools
Session:
Posters - N. E-Cardiology / Digital Health, Public Health, Health Economics, Research Methodology
Speaker:
João Borges Rosa
Congress:
CPC 2021
Topic:
N. E-Cardiology / Digital Health, Public Health, Health Economics, Research Methodology
Theme:
33. e-Cardiology / Digital Health
Subtheme:
33.4 Digital Health
Session Type:
Posters
FP Number:
---
Authors:
João Borges Rosa; Manuel Oliveira-Santos; Marco Simões; Paulo de Carvalho; Gema Ibanez-Sanchez; Carlos Fernandez-Llatas; Marco Costa; Sílvia Monteiro; Lino Gonçalves; on Behalf of The Portuguese Registry of Acute Coronary Syndromes
Abstract
<p style="margin-left:9px; text-align:justify"><span style="font-size:9pt"><span style="font-family:"Palatino Linotype",serif"><span style="color:black"><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">Introduction: 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. We aimed to explore time delays between regions using process mining (PM) tools. </span></span></span></span></span></p> <p style="margin-left:9px; text-align:justify"><span style="font-size:9pt"><span style="font-family:"Palatino Linotype",serif"><span style="color:black"><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">Methods: We retrospectively assessed the Portuguese Registry of Acute Coronary Syndromes for patients with STEMI </span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">from October 2010 to September 2019</span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">, 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.</span></span></span></span></span></p> <p style="margin-left:9px; text-align:justify"><span style="font-size:9pt"><span style="font-family:"Palatino Linotype",serif"><span style="color:black"><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">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). F</span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">ibrinolysis was performed in 4.5%, with a median time delay < 1 hour in every region</span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">. </span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">I</span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">n-hospital mortality was 5%, significantly higher for those without reperfusion therapy compared to PCI and fibrinolysis (10% vs. 4% vs. 4%, P<0.001). I</span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">n 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. F</span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">ibrinolysis </span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">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).</span></span></span></span></span></p> <p style="margin-left:9px; text-align:justify"><span style="font-size:9pt"><span style="font-family:"Palatino Linotype",serif"><span style="color:black"><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">Conclusion: Process mining tools help to understand referencing networks visually, easily highlighting inefficiencies and potential needs for improvement. </span></span><span style="font-size:12.0pt"><span style="font-family:"Calibri",sans-serif">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.</span></span></span></span></span></p>
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