| Literature DB >> 30127833 |
Sayed Hesam Aldin Sharifnia1, Mehdi Mohammadzadeh1, Gelareh Arzani2, Jamshid Salamzadeh3, Sayed Abolfazl Abolfazli1, Alireza Zali4, Ali Reza Khoshdel5.
Abstract
Prescription decision making is a complicated phenomenon influenced by many factors including drug strength, the patient's context, prescriber characteristics, health facilities, payment type, and pharmaceutical marketing. To evaluate the associations between each influenced factor and drug prescription method of Iranian physicians, we conducted an exploratory research, utilizing a questionnaire as quantitative research instrument. A sample of 460 physicians was asked to fill out the questionnaire, yielding 84% response rate. The statistical analysis from the collected data demonstrated that Iranian physicians mostly paid attention to the payment type, the patients' individual factors and the products' characteristics while prescribing a medicine. In addition, it was revealed that marketing expenditures did not have a high influence on the physicians' demand for pharmaceutical products in Iran. The obtained results may be useful for Iranian pharmaceutical companies' marketing strategy planners as well as the patients who are the exact consumers of the prescribed medicines.Entities:
Keywords: Environmental factors; Payers’ factors; Pharmaceutical Marketing; Consumer; Prescription behavior; Products’ factors
Year: 2018 PMID: 30127833 PMCID: PMC6094427
Source DB: PubMed Journal: Iran J Pharm Res ISSN: 1726-6882 Impact factor: 1.696
Figure 1Influenced Factors on Prescription as Decision Making.
Descriptive Analysis of Demographic Characteristics
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Descriptive Analysis of Research Variables and Kolmogorov-Smirnov Test Result
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| Patients Related Factors | 3.644 | 3.667 | 0.633 | 3.200 | 3.667 | 4.025 | 0.651 | 0.79 | Normal |
| Products’ Related Factors | 4.083 | 4.059 | 0.522 | 3.765 | 4.059 | 4.471 | 0.930 | 0.353 | Normal |
| Marketing and Pharmaceutical Companies’ Strategies | 2.252 | 2.233 | 0.685 | 1.733 | 2.233 | 2.667 | 1.099 | 0.179 | Normal |
| Environmental Factors | 2.619 | 2.571 | 0.754 | 2.000 | 2.571 | 3.000 | 1.001 | 0.171 | Normal |
| Payers’ Related Factors | 3.316 | 3.200 | 0.889 | 3.000 | 3.200 | 4.000 | 0.540 | 0.933 | Normal |
Sample Size = 385
Reliability Indexes of the Study
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| Prescription as decision making | 0.773 | 0.766 | 0.77 | 0.662 | 0.784 | 0.824 | 0.646 |
| Environmental factors | 0.512 | 0.826 | 0.762 | ||||
| Products’ related factors | 0.529 | 0.947 | 0.940 | ||||
| Marketing and Pharmaceutical companies’ strategies | 0.540 | 0.915 | 0.901 | ||||
| Patients’ related factors | 0.610 | 0.939 | 0.925 | ||||
| Payers’ related factors | 0.725 | 0.929 | 0.905 |
GOF = Goodness of Fit
Intercorrelations among the Measured Variables.
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| Prescription as decision making | 0.879 | |||||
| Environmental factors | 0.571 | 0.715 | ||||
| Products’ related factors | 0.580 | 0.478 | 0.728 | |||
| Marketing and Pharmaceutical companies’ strategies | 0.704 | 0.393 | 0.515 | 0.735 | ||
| Patients’ related factors | 0.595 | 0.473 | 0.548 | 0.378 | 0.781 | |
| Payers’ related factors | 0.397 | 0.248 | 0.383 | 0.223 | 0.388 | 0.851 |
Structural Equation Modeling Results.
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| Prescription as decision making | Environmental factors (H1) | 0.034 | 0.797 | 0.770 | Rejected | Non reasonable |
| Products’ related factors (H2) | 0.167 | 3.284 | Accepted | Direct | ||
| Marketing and Pharmaceutical companies’ strategies (H3) | 0.085 | 1.043 | Rejected | Non reasonable | ||
| Patients’ related factors (H4) | 0.351 | 5.614 | Accepted | Direct | ||
| Payers’ related factors (H5) | 0.500 | 6.346 | Accepted | Direct |
|t|>1.96 Significant at
< 0.05; |t|> 2.58 Significant at P < 0.01