Predictive criteria for the effective use of telemedicine in pre-hospital emergency care: a hypothetical ıntegration model approach

Aim: to identify objective criteria for determining the disease conditions under which telemedicine would be most effective, using hypothetical integration models. Research objectives: a) Analysis of risk fac tors; b) Determination of the effectiveness of telemedicine; c) Creation of a predictive model. Material and methods. The study involved a retrospective analysis of 1115 critically ill patients who either sustained in juries in highway accidents or experienced acute exacerbations of various diseases in remote areas, neces sitating emergency medical care. The primary outcome was the mortality rate within the first 24 hours after hospital admission. Risk factors were assessed based on patient age, Glasgow Coma Scale (GCS) scores, coma status, and other clinical indicators. The statistical analysis was conducted using Binary Logistic Regression, and the model›s quality was evaluated through the «Omnibus Tests of Model Coefficients» and «Hosmer and Lemeshow» tests. Results. The study found that the time taken for an ambulance to reach the scene after an emergency call significantly influences the risk of complications and mortality, with a longer delay correlating with a higher probability of death. Although age increases the risk of mortality, this increase is not statistically significant. Lower GCS scores are associated with higher mortality risk, and severe coma conditions. Patients with «Coma 1» have a very low survival rate, underscoring the need to consider such conditions critically in emergency medical decisions. The analysis of diagnoses revealed that certain conditions, such as hyperten sion and cerebrovascular disorders, significantly affect the probability of mortality. Other diagnoses, including pathological pregnancy and closed head trauma, did not show a statistically significant impact. These findings provide crucial insights for medical decision- making and the identification of high-risk groups for telemedicine intervention. Conclusion. This study offers important results that contribute to the identification of objective criteria for enhancing the effectiveness of telemedicine in emergency medical services. By predicting which patient conditions would benefit most from telemedicine, healthcare providers can make strategic decisions that improve service quality and increase the survival chances of critically ill patients.

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