Impact of a Prehospital Chest Pain Alert App-Mediated Prehospital-in-Hospital Coordination Model on Treatment Delays and Clinical Outcomes in Patients With ST-Elevation Myocardial Infarction: Protocol for a 4-Year Retrospective Real-World Cohort Study.

Background: The effectiveness of ST-elevation myocardial infarction (STEMI) treatment is highly time-dependent, and the information barrier between prehospital and in-hospital settings remains a key driver of treatment delays. Existing digital coordination tools either have a single function or lack long-term real-world evidence, making it difficult to meet clinical needs. This study adopts a prehospital chest pain alert app developed by the Fengxian District Medical Emergency Center. Mediated through a WeChat-based chest pain center group, the app enables prehospital information synchronization, real-time alerts, multidisciplinary coordination, and feedback on treatment outcomes to form a closed-loop model, overcoming the information barrier. Objective: This protocol aims to evaluate the impact of the app-mediated prehospital-in-hospital coordination model on treatment delays (eg, time from first electrocardiogram to catheterization laboratory preactivation and door-to-wire time) and clinical outcomes (eg, 30-day major adverse cardiovascular events, and 1-year and 4-year all-cause mortality) in patients with STEMI, and to assess its generalizability in high-risk subgroups. Methods: This is a single-center retrospective cohort study. Patients with STEMI admitted to Fengxian District Central Hospital from January 1, 2019, to December 31, 2024, will be enrolled and categorized into 3 groups: baseline group (January 1, 2019, to December 31, 2020, without app use), intervention group (January 1, 2021, to December 31, 2024, with app-mediated coordination), and concurrent control group (patients with STEMI who came to the hospital independently without calling an ambulance or were transported by ambulance but not reported via the app during the same period). The primary outcome is door-to-wire time. Secondary outcomes include other treatment delay indicators, clinical prognosis, and app operational efficiency. We will use propensity score matching to control for baseline confounding, segmented linear regression to analyze intervention trend effects, and subgroup analysis to assess generalizability in high-risk populations. Results: This study is based on 4 years of real-world data from the Department of Cardiology and the STEMI database of Fengxian District Central Hospital. As of April 2026, all 2019-2021 data have been collected; a sample size of 944 or more is expected. Data cleaning and statistical analysis are scheduled from May 2026 to June 2026. Conclusions: Based on 4 years of real-world data, combined with propensity score matching and interrupted time series analysis, this study aims to provide high-quality observational evidence for the app-mediated prehospital-in-hospital coordination model. The findings are anticipated to offer preliminary references for optimizing regional STEMI care systems and to inform the potential application of digital health technologies in acute coronary syndrome management.