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High quality healthcare is important to all patients. If healthcare is felt to be high quality, then patients will be satisfied, and the relationship between patients and healthcare providers will improve. Patient satisfaction is among the most commonly used service quality indicators; however, it is not fully known which factors influence satisfaction. Therefore, it is necessary to pay attention to the elements that affect both healthcare quality and patient satisfaction. Nowadays, several methods are used in health economics to assess patient preferences, prioritize them and help health policy makers improve services. Discrete choice experiment (DCE) is one method that is useful to elicit patient preferences regarding healthcare services. The purpose of this paper is to apply DCE and elicit patient preferences in medical centers to rank certain healthcare quality factors.

The descriptive, analytical study used a cross-sectional questionnaire that the authors developed. In total, 12 scenarios were chosen after applying fractional factorials. The questionnaire was completed by patients who were admitted to Kerman General Teaching Hospitals, South-East Iran in 2015. Patient preferences were identified by calculating the characteristics’ marginal effects and prioritizing them. The generalized estimation equation (GEE) model was used to determine attribute effects on patient preferences.

In total, 167 patients completed the questionnaire. Prioritizing the attributes showed that “physical examination” was the most important attribute. Other key features included “cleanliness,” “training after discharging,” “medical staff attention,” “waiting for admission” and “staff attitude.” All attributes were statistically significant (p<0.05) except staff behavior. No demographic characteristic was significant.

To increase hospital patient satisfaction, health policy makers should develop programs to enhance healthcare quality and hospital safety by increasing physical examination quality and other services.

To estimate DCE independent variables, logistic regression models are usually used. The authors used the GEE model to estimate discrete choice experiment owing the explanatory variables’ dependency.