نشریه مدیریت سلامت
پیاپی 100 (تابستان 1404)

The increasing need for organ transplantation has become a global challenge. A major obstacle to organ donation is the requirement for family consent, which is mandatory in more than 50 countries, including Iran. Changing family attitudes plays a crucial role in increasing organ donation rates. This study aimed to identify factors and effective touchpoints influencing family behavior in order to design social marketing interventions.

This scoping review investigated the role of the family in the organ donation process. A comprehensive search was conducted across major databases including PubMed, Scopus, Web of Science, ProQuest, Emerald, and SID, covering the period from 2020 to 2024. A total of 69 relevant studies were identified and included in the analysis. The collected data were analyzed using thematic analysis with Excel and MAXQDA software to identify key points of contact and influential factors in this domain.

A thorough review of 69 relevant articles identified three key areas: social, cultural, and psychological factors with six components; factors influencing family decision-making in organ donation with three components; and factors affecting effective family communication with four components.

Applying social marketing principles, with a focus on family needs and values, can enhance awareness and participation in organ donation. Despite identifying successful factors, a combined examination of these factors has been rarely conducted, representing a gap in the literature. It is suggested that long-term strategies be formulated and their effects monitored to improve family behavior.

Dental specialties play an important role in promoting oral health. This study investigated the factors influencing general dentistry students’ choice of specialty fields.

This was a cross-sectional survey. The study population included dentistry students affiliated with Isfahan University of Medical Sciences and Khorasgan University in 2021. A total of 301 students participated and completed the questionnaire developed based on the framework of discrete choice studies. The factors were extracted through literature review and qualitative interviews with professors and residents of dental specialties. Choice sets included two alternatives and data analysis was performed using conditional logit regression in Stata version 14.

The probability of choosing a dental specialty increased for those fields with high prestige and income (Coefficient= 0.98), those with a less difficult residency period (Coefficient= 0.20), and those with shorter residency duration (Coefficient= -0.12). Specialties associated with low (Coefficient= 0.43) or average (Coefficient= 0.41) levels of job stress were also more likely to be chosen. Higher tuition fees for residency programs reduced the probability of choosing a specialty (Coefficient= 0.24). Interest in the specialty increased the probability of choice (Coefficient= 0.83).

General dentistry students consider various financial and non-financial factors when selecting a dental specialty. To optimize the allocation of talents across dental specialties, policymakers should consider financial and non-financial incentives.

 Pseudoscience refere to claims that appear scientific but lack reliable research support, posing risks to public health and undermining trust in evidence-based medicine. This study aimed to identify key concepts of pseudoscience in healthcare and explore strategies to mitigate its influence. Its objectives are to clarify the conceptual and semantic relationships associated with health pseudoscience and propose methods to reduce its spread.

 This qualitative study employed conventional content analysis. Participants were recruited through purposive sampling and included physicians, medical faculty members, science experts, media professionals, patients, and individuals involved with pseudoscientific practices. Data were collected through semi-structured interviews and analyzed using qualitative content analysis.

 The research identified five primary categories: 1) definitions and concepts, 2) causes and mechanisms of occurrence and spread, 3) diagnostic methods, 4) consequences and complications, and 5) coping and management strategies. Analysis of perspectives revealed 19 subcategories.

 This study examines health pseudoscience as a complex challange affecting social, cognitive, and public health systems. The findings suggest that effectively addressing this phenomenon requires five essential steps: 1) defining the issue, 2) identifying causative factors, 3) ensuring timely diagnosis, 4) assessing its consequences, and 5) implementing integrated strategies.

Congestive heart failure (CHF) is a significant global challenge for healthcare systems, with its prevalence increasing due to an aging population. Accurate prediction of the length of stay (LOS) for CHF patients is critical for optimizing hospital resource management, reducing treatment costs, and improving the quality of medical care. This study aimed to develop a data mining-based predictive model to estimate the LOS of CHF patients and identify the most influential factors.

This cross-sectional study was conducted using the data of 3,421 CHF patients hospitalized at Seyed Al-Shohada and Ayatollah Taleghani hospitals in Urmia, Iran, between 2018 and 2020. Data from Seyed Al-Shohada Hospital were used for model training (80%) and testing (20%). The LOS was categorized into short-term and long-term classes using K-means clustering. Random forest, Decision tree (C5.0), Artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) were applied to classify LOS. Techniques such as oversampling, undersampling, and SMOTE were applied to balance the classes, and 10-fold cross-validation was used to ensure model reliability. The Apriori algorithm was also used to discover association rules.

The random forest achieved the best performance with an accuracy of 87.14%, a sensitivity of 97.56%, and an AUC of 85.40%. Key predictors of LOS included elevated creatinine levels, low hemoglobin, male gender, and underlying comorbidities. The Apriori algorithm also revealed significant clinical and meaningful associations among variables.

The proposed model can serve as an effective tool for predicting LOS in CHF patients and support clinical and administrative decision-making in hospital settings.

Assessing the altmetric status of Iranian researchers' scientific outputs in the field of transplantation is highly important. The aim of this study was to investigate the visibility of Iranian researchers’ scientific outputs in this field on social media.

To conduct this research, scientometric and altmetrics indicators were employed. The study population included all scientific outputs in the field of transplantation that listed Iran as their affiliated country and were indexed in the Web of Science (WOS) at the time of data collection. Data were collected from WOS and Altmetric Explorer. Moreover, the data were analyzed using SPSS (version 23) and Microsoft Excel, applying descriptive and analytical statistics.

Out of 1267 papers with unique DOIs published in this field, 415 were mentioned at least once on social media platforms. These publications were marked and read 11,902 times on Mendeley. Moreover, the highest rate of mentions occurred on X, followed by patents, and news outlets. The Spearman correlation revealed statistically significant positive relationship between articles' citation counts in the WOS and their altmetric attention score (AAS), and Mendeley readership counts.

Altmetric indicators have the potential to complement traditional citation indicators in assessing the scientific impact of research findings. Researchers should become more aware of these indicators and their importance in research evaluation.

Drug pricing plays a crucial role in healthcare delivery, affecting patients' access to essential medicines and determining the financial sustainability of healthcare systems worldwide. High drug prices lead to inequality in access, while strict price control may discourage investment in this industry and reduce progress and innovation in medicines. The aim of this study was to compare the drug pricing system in Iran with that of selected countries including France, Turkey, and Spain.

This  comparative study used  printed and non-printed books and articles identified through scientific databases. The collected data were qualitatively compared.

In Turkey, both foreign and domestic reference pricing systems, along with negotiations with manufacturers, serve as the main drug pricing strategies. In Spain, the pricing system combines mark-up, negotiated pricing, reference pricing, and value-based pricing. In France, negotiated and value-based pricing system are the main strategies, with reference pricing as a complementary approach. In Iran, the foreign reference pricing system, similar to the other three countries, is the basis for pricing along with manufacturer proposals, though for some drug categories, pricing is still based on cost and mark-up.

It seems that in Iran, as in leading countries in this industry, greater attention should be paid to value-based drug pricing.

Mobile-based medication management applications play a significant role in improving medication safety, providing medication reminders, and facilitating access to drug-related information. However, the quality and effectiveness of these applications depend on their functional and non-functional requirements. This study aimed to identify and compare the functional and non-functional requirements of medication management applications developed in Iran.

This study was conducted in 2024. Initially, key requirements were identified through a scoping review. Then, an evaluation checklist containing nine functional and eight non-functional requirements was developed, and its content validity was confirmed by experts. Eleven free applications were selected from two Iranian app stores and Google Play. The reliabilty was evaluated by three experts in health information technology and medical informatics using Kappa coefficient (K = 0.81).

Among functional requirements, features such as medication information and medication management were observed in all 11 applications. By contrast, features such as clinical data entry was found in only one app, and no applications allowed user profile creation. Regarding non-functional requirements, the most frequent ones were usability (n=11), reliability (n=10), accessibility (n=10), security (n=4), scalability (n=5), and privacy (n=3).

While several key requirements were included in most medication management applications, there remains a need for improvement in areas such as clinical data recording, scalability, and security. Incorporating validated standards and engaging healthcare professionals in the design process are recommended to improve the quality of medication management applications.

Health information systems that incorporate decision-support systems (DSS) can operate effectively for diagnostic and therapeutic services, and follow-up reminders. Choice architecture can be applied in the design of DSSs. Based on ​​choice architecture, nudges offer policymakers a non-mandatory strategy to improve individuals' decisions. A nudge, a concept in behavioral economics, subtly alters the environment or context to influence their behavior without restricting freedom of choice. Therefore, we suggest that integrating intelligent nudges into the design of DSS. Nudge-based DSSs can pave the way for increasing the efficiency of health information systems. More studies are needed to design effective nudge-driven models of health information systems.