Background: Hospitals are required to continuously improve service quality and ensure patient safety. Surakarta Central General Hospital, as the only type C vertical hospital owned by the Ministry of Health in Surakarta, faces competition from other type C hospitals operated by local governments and private sectors. This study aimed to identify factors influencing patient satisfaction and loyalty among users of healthcare services at Surakarta Central General Hospital. Subjects and Methods: This was a quantitative cross-sectional study conducted at the Surakarta Central General Hospital, Central Java, Indonesia, from April to May 2025. A total of 270 respondents, including both inpatients and outpatients, were selected using simple random sampling. The dependent variables were service quality, patient satisfaction, and patient loyalty. The independent variables included hospital image, type of health financing, type of disease, and type of care. Results: Patient loyalty was positively and significantly influenced by satisfaction (b = 0.33; 95% CI = 0.26–0.41; p < 0.001) and hospital image (b = 0.41; 95% CI = 0.29–0.53; p < 0.001). Patient satisfaction was positively and significantly affected by service quality (b = 0.19; 95% CI = 0.13–0.24; p < 0.001), hospital image (b = 0.25; 95% CI = 0.08–0.43; p = 0.005), and type of financing (b = 0.51; 95% CI = 0.11–0.92; p = 0.013). Service quality was positively and significantly influenced by hospital image (b = 1.13; 95% CI = 0.77–1.48; p < 0.001) and type of financing (b = 0.91; 95% CI = 0.05–1.78; p = 0.039). The path analysis model demonstrated good model fit, as indicated by the following indices: p = 0.702; RMSEA = 0.00; CFI = 1.00; TLI = 1.05; SRMR = 0.00; and CD = 0.33. Conclusion: Patient loyalty is directly and significantly influenced by satisfaction and hospital image. Patient satisfaction is directly and significantly influenced by service quality, hospital image, and type of financing. Service quality is directly and significantly influenced by hospital image and type of financing. Overall, the path analysis model demonstrated a good fit.
Copyrights © 2026