The Impact of Diagnostic Accuracy and Waiting Time on Diabetes Patients’ Satisfaction: An Applied Study at Benghazi Specialized Diabetes Treatment Center – Libya

Abstract

Patient satisfaction serves as a fundamental benchmark for measuring the quality of healthcare delivery, particularly for individuals managing chronic conditions like diabetes mellitus. This study aimed to investigate the specific impact of two critical factors—medical diagnostic accuracy and waiting time—on the overall satisfaction levels of patients at the Benghazi Specialized Diabetes Treatment Center in Libya. Additionally, the research explored the relationship between patient satisfaction and the likelihood of recommending the center to others. To achieve these objectives, a descriptive-analytical research design was employed, and data were collected through a structured questionnaire. The survey was distributed to a sample of 115 patients, resulting in 100 valid responses after the exclusion of incomplete or invalid entries. All multi-item measures were assessed using a five-point Likert scale. Statistical analysis, performed using R software, included descriptive statistics, Pearson correlation, and multiple linear regression. The results revealed a strong positive correlation between perceived diagnostic accuracy and patient satisfaction (r = 0.87, p < 0.001). Conversely, a strong negative correlation was found between waiting time and satisfaction levels (r = -0.74, p < 0.001). Multiple regression analysis indicated that diagnostic accuracy ( = 0.71, p < 0.001) and waiting time (  = -0.62, p < 0.001) collectively explained 79% of the variance in patient satisfaction (R² = 0.79). Furthermore, higher satisfaction was significantly associated with a greater likelihood of recommending the facility. These findings highlight the critical importance of balancing clinical precision with operational efficiency. The study concludes that healthcare providers must prioritize continuous medical training to enhance diagnostic accuracy while simultaneously optimizing administrative workflows to reduce patient wait times