Abstract WMP51: Patients’ Social Networks Influence Timing of Hospital Arrival After Acute Ischemic Stroke: a Mixed Methods Study

Introduction: Delay in hospital arrival is a major reason for stroke patients’ exclusion from acute therapy. Risk factors for delay include older age, minor symptoms, and living alone. Personal social networks, consisting of the structure and content of relationships around a patient, are important and modifiable factors to health behavior. This study examined the role and mechanisms of patients’ social networks in prehospital delay. Hypothesis: Social network structure is an independent risk factor of prehospital delay through social influence mechanisms. Methods: Seventy consecutive patients with mild acute ischemic stroke were interviewed in the hospital. An established social network analysis instrument was used to assess personal network structure and composition. This was followed by semi-structured interviews in 14 patients focused on the arrival process. Fast arrival was defined as before 6 hours, and slow was after 6 hours. Results: There were 32 slow and 38 fast arrivers. The mean age (63) and NIHSS (3) did not differ between groups. Subcortical stroke location (53% versus 26%) and being unmarried (75% versus 44%) were more common in slow compared to fast arrivers (p<0.05). After controlling for known risk factors, social network structure was significantly associated with arrival time. As shown in figure 1, patients (A) who had networks with high constraint (e.g., strong ties among all network members) were slower to arrive than patients (B) with low constraint (e.g., weak or no ties among network members). Constraint had an adjusted OR=1.08 (95% CI 1.03-1.13, p<0.005) for slow arrival. Mechanisms revealed from qualitative analysis were social capital benefits in fast arrivers, and family members’ perceptual bias to minimize symptoms in slow arrivers. Conclusions: Patients’ social network structure is an independent risk factor for prehospital delay. These results may be used to develop network-tailored stroke education.