BACKGROUND : Medical tourism for infertility care is expanding, but the relative contribution of health system and service factors to destination desirability remains uncertain. This study aimed to identify and rank the determinants of medical tourism for infertility care and predict “desirability” destination using an artificial neural network (ANN). METHODS : A cross-sectional study at the Research Institute for Reproductive Sciences, Yazd, Iran (study period 2021–2023). Consecutive consenting medical tourists completed the validated medical tourists attracting factors (MTAF-46) questionnaire consisting of 10 domains. The primary outcome was destination desirability. An ANN (feed-forward, supervised learning) was trained on a random split of the dataset and evaluated on held-out data. Performance was summarized by area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. Variable importance was used to characterize the type, direction, and relative strength of associations. RESULTS : A total of 430 respondents were analyzed. The evaluation set showed a strong discrimination (AUC: 95.2%) with overall accuracy 91.3%, sensitivity 57.1%, and specificity 98.1%. Higher scores across several domains were positively associated with desirability; the top contributors were: medical services, economic factors, advertising and marketing, administrative and financial services, and support services. Class proportions indicated that “desirable” cases were less frequent (11.0% in the evaluation set), and model performance favored specificity, consistent with conservative positive classification. CONCLUSIONS The development of infertility medical tourism in Yazd is mainly driven by the quality of core clinical services and economic factors. Effective marketing, transparency in administrative and financial processes, and efficient support services also enhance the destination’s attractiveness.
advertising ; Iran ; marketing ; medical services ; medical tourism ; medical tourists

Objectives: The purpose of this study was to evaluate the performance indicators for obstetrics and gynecology wards in Iran. Methods: This study was designed as a cross-sectional study and was carried out in obstetrics and gynecology wards of Afshar and Shahid Sadoughi hospitals in 2015. The information required for the performance indicators was gathered through questionnaires, statistical forms, and direct observation. In several tables, performance rating and performance status are presented using the Likert scale index based on the expected limits. Results: According to the results of the categories of input indicators, the bed occupancy rate of Afshar Hospital’s obstetrics and gynecology ward was, at 83%, higher than expected (79%), and that in Shahid Sadoughi Hospital (at 69%) was lower than expected. For medicinal methods and nonmedicinal methods of pain alleviation, the index process at Afshar Hospital was much lower than expected (40%). In Afshar Hospital, patient satisfaction at discharge was about 66.74%. Conclusion Effective steps can be taken to improve the input and output criteria: allocating appropriate physical space, examining the reasons for low bed occupancy rate by using complex analytical models, and in order to study the reasons for large number of cesarean section childbirth, it was recommended to place more emphasis on training of pregnant mothers and to inform them about the side effects of cesarean section and advantages of natural childbirth.