Document Type : Original Article
Authors
1
- Lecturer, Department of Health Services Management, School of Public Health, Ahvaz JundiShapur University of Medica Sciences, Ahvaz, Iran
2
Assistant Professor, Health Management and Economics Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran 3- Assistant Professor, Department of Health Services Management,
3
Assistant Professor, Health Services Management Research Center, Kerman University of Medical Sciences, Kerman, Iran
4
- MSc, Health Management and Economics Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
5
MSc, Health Management and Economics Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
Abstract
Background: Owing to the growing importance of medicines in treatment of diseases, as well as their role as alternatives for expensive and often unsafe procedures; economic examination of factors associated with their demand is necessary. Hence, this study aimed at exploring factors affecting the demand of specialty medicines. Methods: In this descriptive-analytic study, data was collected from questionnaires completed by 280 patients with multiple sclerosis, hemophilia, thalassemia, and chronic kidney disease. Then data was entered into Stata 12 and after estimating the model, by using the Probit model, their final effect was evaluated. Results: We found that patient need (ME=0.858), deterioration of patient health (ME =- 0.001), situation of house ownership (ME =-0.002), gender (ME =-0.048), income (ME =- 0.001), education (ME =-0.002) and job (ME =-0.001) are significant variables that affect demand for specialty drugs. Health insurance coverage (P =0.631) had no significant correlation with demand. Conclusion: Consideration of factors affecting patients’ need can help policy makers in anticipation of special patients’ need to specialty drugs. Also demand can be manipulated by working on some patients’ characteristics such as their education level.
Keywords
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