Assessment of distance to primary percutaneous coronary intervention centres in ST-segment elevation myocardial infarction: Overcoming inequalities with process mining tools.
Digit Health
; 9: 20552076221144210, 2023.
Article
in En
| MEDLINE
| ID: mdl-36698425
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" (0504) and "Castelo Branco" (0650) showing longer delays between diagnosis and reperfusion than "Coimbra" (0119). 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.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Aspects:
Determinantes_sociais_saude
/
Equity_inequality
Language:
En
Journal:
Digit Health
Year:
2023
Document type:
Article
Affiliation country: