Abstract
Background/Objectives: Patients in medically underserved regions often seek cross-regional healthcare for high-quality medical services but face significant barriers due to limited information about providers. Internet hospitals address this gap by offering online consultations, remote diagnoses, and public service information. This study examines how such information shapes patients' cross-regional healthcare choices. Methods: A binary logistic regression model using signaling theory was employed to evaluate the impact of platform-generated signals (e.g., hospital ratings) and patient-generated signals (e.g., review quantity and polarity) on patients' cross-regional healthcare choices. The experimental data were sourced from a leading Chinese online medical platform, comprising 1901 hospitals and 273,884 patient feedback records. Among these, 216,793 patients (79.16%) sought cross-regional treatment, while 57,091 patients (20.84%) opted for local treatment. Results: Platform-generated signals, such as hospital ratings (B = 0.406, p < 0.01) and patient-generated signals, including review quantity (B = 0.089, p < 0.01) and polarity (B = 0.634, p < 0.01), significantly and positively influence patients' cross-regional healthcare choices. Disease severity and local medical resource availability moderated these effects: Patients with severe conditions rely less on hospital ratings (B = -0.365, p < 0.01), while those in resource-limited areas depend more on hospital ratings (B = -0.138, p < 0.01) and review quantity (B = -0.029, p < 0.01) but less on review polarity (B = 0.273, p < 0.01). Conclusions: These findings offer actionable insights for policymakers and platform developers to optimize online healthcare services, facilitating informed cross-regional healthcare decisions and advancing healthcare equity in the digital era.