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بررسی چالش‌های حق بر سلامت در قوانین تأمین اجتماعی Examining the Challenges of the Right to Health in Social Security Laws 1 1 حق بر سلامت، از جمله حقوق بنیادین بشر بوده که در اسلام نیز همواره مورد تأکید قرار گرفته است. که دسترسی به بالاترین سطح سلامت جسمی و روانی را برای هر فرد تضمین می‌کند. بدین معنا که هر انسانی مستحق بهره‌مندی از خدمات پزشکی، بهداشت عمومی، غذای کافی، مسکن مناسب و محیط کار سالم است و این مهم در اسناد حقوق بشری و قوانین تأمین اجتماعی مورد حمایت ویژه قرار دارد. نظام تأمین اجتماعی ایران، مشتمل بر دو بخش بیمه‌ای و حمایتی، خدمات درمانی و بهداشتی گسترده‌ای ارائه می‌دهد. دسترسی عادلانه و مقرون‌به‌صرفه به این خدمات، به‌ویژه برای گروه‌های آسیب‌پذیر، امری ضروری است. ارتقای سلامت اجتماعی مستلزم فراهم‌سازی پیش‌نیازهای اساسی نظیر آموزش، مسکن، غذا و اشتغال است. اگرچه قوانین تأمین اجتماعی بر حق سلامت تأکید دارند، چالش‌هایی نظیر کمبود منابع و دسترسی محدود به خدمات با کیفیت، مانع تحقق کامل این حق است. از طرفی، نهادهای دولتی موظف به تأمین مراقبت‌های بهداشتی و حفاظت از سلامت جامعه بر اساس قوانین ملی و بین‌المللی هستند. بنابراین، تحقق کامل این حق مستلزم شناسایی چالش‌ها و ارائه راهکارهایی جهت بهبود نظام تأمین اجتماعی و خدمات درمانی است. این راهکارها می‌تواند شامل افزایش دسترسی به آموزش، تحقق عدالت در توزیع منابع و بهبود شرایط زیست‌محیطی باشد. 2 The right to health is among the fundamental human rights and has always been emphasized in Islam. It guarantees access to the highest level of physical and mental health for every individual. This means that every person is entitled to benefit from medical services, public health, adequate food, proper housing, and a healthy work environment, and this is given special support in human rights documents and social security laws. Iran's social security system, consisting of both insurance and support sectors, provides extensive medical and healthcare services. Fair and affordable access to these services, especially for vulnerable groups, is essential. Promoting social health requires providing basic prerequisites such as education, housing, food, and employment. Although social security laws emphasize the right to health, challenges such as resource shortages and limited access to quality services hinder the full realization of this right. On the other hand, government institutions are obligated to provide healthcare and protect public health in accordance with national and international laws. Therefore, fully realizing this right requires identifying challenges and offering solutions to improve the social security and healthcare system. These solutions may include increasing access to education, achieving equity in resource distribution, and improving environmental conditions. 181 192 2025/05/18 1404/2/28 2025/09/28 1404/7/6 آرزو ملکشاه Arezoo Malekshah گروه حقوق، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران a.malekshah@iau.ac.ir احمد امی Ahmad Ommi گروه حقوق، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران a_ommi@iau.ac.ir مرضیه ملکی Marzieh Maleki گروه آموزش معارف اسلامی، دانشگاه فرهنگیان، تهران، ایران m.maleki@cfu.ac.ir Health Equity Right to Health Social Security Healthcare Services Iran عدالت در سلامت حق بر سلامت تأمین اجتماعی خدمات درمانی ایران ##1.Motamani Tabatabaei, M, Public Freedoms and Human Rights, Fourth Edition, Tehran: University of Tehran, 2009, p. 40. ##2. Saberi, M, Asadian, Ahmad, Moradi, H and Al-Buyeh, A , Investigating the Position of Medical and Medical Services in the Context of Social Security Law, Journal of Medical Law, Vol. 15, No. 56, 2021, p. 2. ##3. Noormohammadan, F, Naeimi, O and Ghasemi, M, The Right to the Health of Iran's Social Security Retirement Legal System from the Perspective of Fundamental Human Rights, International Legal Research, Vol. 15, No. 55, 2022, p. 275.##4. Scott Leckie and Anne Gallagher. Economic, Social, and Cultural Rights: A Legal Resource Guide. University of Pennsylvania Press, 2006; P 375. https://doi.org/10.9783/9780812205381##5. Javid, E and Niavarani, S, The Commitment of Governments to Guarantee the Right to Health Services and Care in the Light of International Law with a Look at the Health System Transformation Plan in Iran, Legal Research Quarterly, No. 97, 2022, p. 344.##6. Willem Grosheide. Intellectual Property and Human Rights: A Paradox. Edward Elgar Publishing, 2010; P 126-127. https://doi.org/10.4337/9781849802048##7. Mousavi Bojnourdi, M, Davarzani, M, Family Physician, Realization of Justice in Health with an Approach to Imam Khomeini's Views, Matin Studies, No. 64, 2015, p. 124.##8. Hashemi, S M, Human Rights and Fundamental Freedoms, Mizan Publishing, First Edition, 2003, p. 74.##9. Seyed Naseri, M M and Teymouri, M, The Concept of the Right to Health of Children with Special Needs in the Light of the United Nations Convention on the Rights of the Child, Journal of Health Rights, Vol. 2, 2024, p. 65.##10.Feizadeh A, Madani S. Social Security and SocialWelfare. Indicators for Determining and Measuring, Social Security Quarterly. 2000;2(7):1441-1464.##11. Khaleghparast, H, Rasekh, Mohammad and Naeimi, O .Legal Analysis of Iranian Social Security in the Light of the Principles and Patterns of the Optimal Social Security System, Social Welfare Quarterly, Vol. 17, No. 64, 2017, p. 79.##12. Norouz Taleghani, A, Social Security Guide to Workers' Education, 2nd Edition, Social Security Research Institute, 1996, p. 18. ##13. Taleb, M, Social Security, Sixth Edition, Astan Quds Razavi Publications, 2002, p. 40.##14. Feizadeh A, Madani S. Social Security and SocialWelfare. Indicators for Determining and Measuring, Social Security Quarterly. 2000;2(7):1441-1464.##15. Panahi B. Functions of social security in Iran: the need to establish a comprehensive welfare and social security system. Tehran: Espid; 2006. ##16. Scheinin M. The Right to Social Security, In: Asbjorn Eide, Catarina Krause Allan Rosas (EDS), Economic. Dordrecht, Netherlands: Social and Cultural Rights, Martinus Nijhoff Publishers; 1995.##17. Rahmat Elahi, H and Mirzaei, Z, A Study of the Health System in Iranian and German Social Security Law, Religion and Law, No. 15, 2017, p. 76. ##18. Rahmat Elahi, H and Mirzaei, Z, A Study of the Health System in Social Security Law in Iran and Germany, Religion and Law Quarterly, No. 15, 2017, p. 76.##19. Saberi, M, Asadian, A, Moradi, H, Al-Buyeh, A, Investigating the Position of Medical and Medical Services in the Context of Iranian Social Security Law, Journal of Medical Law, Vol. 15, No. 56, 2021, p. 78.##20. Feizadeh A, Madani S. Social Security and SocialWelfare. Indicators for Determining and Measuring, Social Security Quarterly. 2000;2(7):1441-1464.##21. Social Security Organization. Introduction of Social Security Organization, Social Security Organization Website. Available at: WWW.tamin.ir/News/2352/2/2352.html.2011.##22. Shahbazinia, M, The Right to Social Security: Characteristics, Content and General Principles Governing It, Social Security Quarterly, Vol. 9, No. 30, 2007, p. 51. ##23. Social Security Organization. Introduction of Social Security Organization, Social Security Organization Website. Available at: WWW.tamin.ir/News/2352/2/2352.html.2011 .##24. Shoja, J, Research and Development of Nanotechnology from the Perspective of the Right to Health, Tehran, Journal of Legal Research, 7th Year, Autumn-Winter, No. 14, 2008, p. 74. ##25. Smith PC. Measuring health system performance. The European Journal of Health Economics. 2002 Sep;3(3):145-8.##26. Anesaki M, Munakata T. Health, illness, and health policy in Japan. The Blackwell companion to medical sociology. 2001 Jan 1:441-55.##27. Peykar Z, mohammadi A. Economic and Institutional Factors Affecting Self Curing and Self-medication in Shahrekord. Journal Health Breeze, 2015. 4(4);.7-14. ##28. Scott Leckie and Anne Gallagher. Economic, Social, and Cultural Rights: A Legal Resource Guide. University of Pennsylvania Press, 2006; P 375. https://doi.org/10.9783/9780812205381##29. Javid, E and Niavarani, S, The Commitment of Governments to Guarantee the Right to Health Services and Care in the Light of International Law with a Look at the Health System Transformation Plan in Iran, Legal Research Quarterly, No. 97, 2022, p. 344.##30. Badini, H . A Critical Inquiry into the Legal System of Social Security in Iran, Law Quarterly, Journal of the Faculty of Law and Political Science, Vol. 31, No. , 2008, p. 59.##31. 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اولویت‌دارترین عوامل دموگرافیک، بالینی و سبک زندگی مؤثر بر پیشگیری از سندرم متابولیک در بزرگسالان Priority Demographic, Clinical, and Lifestyle Factors Influencing the Prevention of Metabolic Syndrome in Adults 1 1 مقدمه: سندرم متابولیک به‌عنوان یک چالش عمده بهداشت عمومی، ارتباط قابل توجهی با بیماری‌های قلبی-عروقی، دیابت نوع ۲ و چاقی دارد. این مطالعه با هدف شناسایی عوامل مؤثر بر پیشگیری سندرم متابولیک از طریق مرور دامنه‌ای انجام شد. روش بررسی: بر اساس چارچوب آرکسی و اُمالی، پایگاه‌های داده PubMed، ProQuest، Google Scholar، SID و Magiran برای مقالات منتشرشده بین سال‌های ۲۰۱۰ تا ۲۰۲۵ جستجو شدند، و داده‌های کلیدی با استفاده از فرم استاندارد استخراج ثبت گردید. یافته‌ها: بر اساس معیارهای ورود و خروج، ۹۴ مقاله مورد تحلیل قرار گرفتند. عوامل شناسایی شده در حوزه های دموگرافیک، بالینی و سبک زندگی دسته‌بندی شدند. فشار خون بالا، افزایش وزن، چاقی شکمی، کم تحرکی، مصرف سیگار، الکل، الگوی غذایی ناسالم و سطح پایین HDL بیشترین تأثیر را بر بروز سندرم متابولیک داشتند. نتیجه‌گیری: کنترل فشار خون، قند خون و چاقی همراه با اصلاح سبک زندگی، مهمترین راهبردهای پیشگیرانه محسوب می‌شوند. نتایج بر ضرورت تدوین سیاست‌های چندبعدی بهداشتی، افزایش آگاهی عمومی، اصلاح الگوی تغذیه و بهبود دسترسی به خدمات سلامت تأکید دارد. اجرای مداخلات جامع در سطوح فردی و سیاستی می‌تواند به کاهش شیوع سندرم متابولیک و عوارض مرتبط با آن بینجامد. 2 Introduction: Metabolic syndrome represents a major public health challenge due to its strong association with cardiovascular disease, type 2 diabetes, and obesity. This scoping review aimed to identify the key factors influencing the prevention of metabolic syndrome. Methods: Guided by the Arksey and O’Malley framework, we conducted a comprehensive search of PubMed, ProQuest, Google Scholar, SID, and Magiran for studies published between 2010 and 2025. Relevant data were extracted using a standardized data extraction form. Results: A total of 94 articles met the inclusion criteria and were included in the final analysis. The identified determinants were classified into demographic, clinical, and lifestyle categories. Hypertension, weight gain, abdominal obesity, physical inactivity, smoking, alcohol, unhealthy dietary patterns, and low HDL levels were found to have the strongest impact on the incidence of metabolic syndrome. Conclusion: Controlling blood pressure, blood glucose, and obesity—together with lifestyle modifications—represents the most essential preventive strategies.The findings highlight the need for multidimensional health policies, improved public awareness, healthier dietary patterns, and expanded access to healthcare services. Implementing comprehensive interventions at both individual and policy levels may help reduce the prevalence of metabolic syndrome and its related complications. 193 214 2025/05/182025/05/13 1404/2/23 2025/09/282025/10/4 1404/7/12 محسن فربود Mohsen Farboud گروه مدیریت خدمات بهداشتی و درمانی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران m.farboud24@gmail.com سمیه حسام Somayeh Hessam گروه مدیریت خدمات بهداشتی و درمانی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران Shessam@iau.ac.ir شقایق وحدت Shaghayegh Vahdat گروه مدیریت خدمات بهداشتی و درمانی، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران Sha_vahdat@yahoo.com شهرام توفیقی Shahram Tofighi مرکز ملی تحقیقات بیمه سلامت، تهران، ایران Shr_tofighi@yahoo.com Metabolic Syndrome Prevention Risk Factor سندرم متابولیک پیشگیری عوامل خطر 1. Hosseini-Esfahani F, Alafchi B, Cheraghi Z, Doosti-Irani A, Mirmiran P, Khalili D, et al. 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ارتباط فعالیت بدنی با بیماری‌های مزمن بیمه‌شدگان سالمند بیمه سلامت ایران The Relationship Between Physical Activity and Chronic Diseases Among the Elderly Insured of the Iran Health Insurance Organization 1 1 مقدمه: بیماری‌های مزمن غیرواگیر از مهم‌ترین چالش‌های سلامت عمومی در ایران هستند و با افزایش جمعیت سالمندان بار این بیماری‌ها رو به رشد است. سبک زندگی کم‌تحرک یکی از عوامل مهم بروز این بیماری‌ها محسوب می‌شوند. فعالیت بدنی منظم می‌تواند نقش حفاظتی مهمی در پیشگیری و کنترل بیماری‌های مزمن ایفا کند. با توجه به نقش بیمه سلامت در پوشش هزینه‌های درمانی، بررسی ارتباط فعالیت بدنی با بیماری‌های مزمن اهمیت دارد. روش بررسی: این پژوهش یک مطالعه توصیفی–تحلیلی مقطعی بود که بر روی ۲۷۵ سالمند ۶۰ تا ۷۰ ساله تحت پوشش بیمه سلامت در تهران انجام شد. نمونه‌گیری به‌صورت خوشه‌ای چندمرحله‌ای انجام گرفت. ابزار گردآوری داده‌ها شامل پرسشنامه جمعیت‌شناختی، پرسشنامه بین‌المللی فعالیت بدنی (IPAQ) و چک‌لیست بیماری‌های مزمن بود. داده‌ها با نرم‌افزار SPSS و آزمون‌های کای-دو و رگرسیون لجستیک تحلیل شدند. یافته‌ها: یافته‌ها نشان داد بین سطح فعالیت بدنی و ابتلا به بیماری‌های مزمن ارتباط معناداری وجود دارد (۰.۰۰۰=P). سالمندانی که فعالیت بدنی پایین داشتند بیشترین شیوع بیماری مزمن را گزارش کردند، در حالی که بیش از نیمی از افراد با فعالیت بدنی بالا فاقد بیماری مزمن بودند. رگرسیون لجستیک نیز نشان داد که فعالیت بدنی به‌عنوان یک عامل مستقل، پس از کنترل سن و جنس، با کاهش احتمال ابتلا به بیماری‌های مزمن همراه است. نتیجه‌گیری: افزایش فعالیت بدنی سالمندان استراتژی مؤثری برای پیشگیری و کاهش بیماری‌های مزمن است. برنامه‌های آموزشی و مداخلات حمایتی با هدف ترویج فعالیت‌های ورزشی سبک و منظم، علاوه بر ارتقای کیفیت زندگی سالمندان، موجب کاهش هزینه‌های درمانی و بار مالی بر نظام سلامت خواهد شد. 2 Introduction: Chronic non-communicable diseases are major public health challenges in Iran and the burden of these diseases is growing with the increase in the elderly population. A sedentary lifestyle is a key factor in these diseases. Regular physical activity can play an important protective role in the prevention and control of chronic diseases. Given the role of health insurance in covering medical costs, examining the relationship between physical activity and chronic diseases is important. Methods: This was a cross-sectional descriptive-analytical study conducted on 275 elderly people aged 60–70 years covered by health insurance in Tehran. Sampling was done in a multi-stage cluster method. Data collection tools included a demographic questionnaire, the International Physical Activity Questionnaire (IPAQ) and a chronic disease checklist. Data were analyzed using SPSS software and Chi-square and logistic regression tests. Results: Findings indicated a significant association between physical activity levels and chronic disease incidence (P=0.000). Elderly with low physical activity reported the highest prevalence of chronic disease, while over half of those with high physical activity were disease-free. Logistic regression also showed that physical activity as an independent factor after controlling for age and gender, reduces the likelihood of chronic diseases. Conclusion: Promoting physical activity among the elderly is an effective strategy for preventing and reducing chronic diseases. 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Effectiveness of physical exercise for people with chronic diseases: the EFIKRONIK study protocol for a hybrid, clinical and implementation randomized trial. BMC Fam Pract. 2020 Nov 6; 21(1):227. Doi: 10.1186/s12875-020-01298-4. PMID: 33158422; PMCID: PMC7648284. ##31. Lachman S, Boekholdt SM, Luben RN, Sharp SJ, Brage S, Khaw KT, Peters RJ, Wareham NJ. Impact of physical activity on the risk of cardiovascular disease in middle-aged and older adults: EPIC Norfolk prospective population study. Eur J Prev Cardiol. 2018 Jan; 25(2):200-208. Doi: 10.1177/2047487317737628. Epub 2017 Nov 21. PMID: 29161890; PMCID: PMC5757406.##32. Olamazadeh MH and Faramarzi M. The role of physical activity and exercise in prevention of non-communicable chronic diseases in Iran. Journal of Isfahan Medical School. 2020; 38(582):477-488. Doi: 10.22122/jims.v38i582.12983. [Persian]##33. Huang Y, Lu Z. A cross-sectional study of physical activity and chronic diseases among middle-aged and elderly in China. Sci Rep 14, 30701. 2024. https://doi.org/10.1038/s41598-024-78360-z.##34. Szychowska A, Drygas W. Physical activity as a determinant of successful aging: a narrative review article. Aging Clin Exp Res. 2022; 34:1209–1214. https://doi.org/10.1007/s40520-021-02037-0##35. McMullan II, Bunting BP, Blackburn NE, Wilson JJ, Deidda M, Caserotti P, Smith L, Dallmeier D, Roque M, Weinmayr G, Gine-Garriga M, Coll-Planas L, & Tully MA. The mediating role of self-regulation and self-efficacy on physical activity change in community-dwelling older adults (≥65 years): An experimental cross-lagged analysis using data from SITLESS. Journal of Aging and Physical Activity. 2021; 29(6):931–940. DOI:https://doi.org/10.1123/japa.2020-0322##36. Gristwood J. Applying the health belief model to physical activity engagement among older adults. Illuminare. 2011; 9:59‑71. ISSN: 2158-9070 online##37. Zhou P, Hughes AK, Grady SC, et al. 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سنجش سواد بیمه‌ای و عوامل مؤثر بر بیمه‌شدگان سازمان بیمه سلامت شهر یزد Health Insurance Literacy and Its Determinants among Insured Individuals: A Study in Yazd, Iran 1 1 مقدمه: سواد بیمه سلامت به‌عنوان یکی از زیرمجموعه‌های سواد سلامت، نقش مؤثری در ارتقای توانایی افراد جهت استفاده مؤثر از خدمات بیمه‌ای دارد. درک دقیق از مفاهیم و فرآیندهای بیمه‌ای می‌تواند زمینه‌ساز تصمیم‌گیری آگاهانه‌تر در حوزه درمان و سلامت شود. با توجه به نقش تعیین‌کننده سواد بیمه‌ای در بهره‌مندی بهینه از خدمات بیمه سلامت، مطالعه حاضر با هدف بررسی سطح سواد بیمه‌ای و شناسایی عوامل مرتبط با آن در بین بیمه‌شدگان سازمان بیمه سلامت شهر یزد در سال ۱۴۰۴ انجام شد. روش بررسی: این پژوهش از نوع توصیفی–تحلیلی، کاربردی و مقطعی است که به‌صورت پیمایشی انجام شد. داده‌ها از نمونه‌ای ۲۴۹ نفری از بیمه‌شدگان مراجعه‌کننده به دفاتر پیشخوان طرف قرارداد بیمه سلامت در شهر یزد، به روش تصادفی و با استفاده از پرسشنامه استاندارد سواد بیمه‌ای جمع‌آوری شد. تحلیل داده‌ها با استفاده از آمار توصیفی و آزمون‌های من–ویتنی و کروسکال–والیس در نرم‌افزار SPSS نسخه ۲۷ انجام گرفت. یافته ها: یافته‌ها نشان داد که 8/63 درصد از بیمه‌شدگان دارای سواد بیمه‌ای در سطح بالا و بسیار بالا بودند. بالاترین میانگین نمره مربوط به بُعد «دستیابی به اطلاعات» و پایین‌ترین میانگین مربوط به بُعد «مهارت‌های عملکردی» بود. میانگین نمره سواد بیمه‌ای در مردان، افراد دارای تحصیلات بالاتر و با درآمد بیشتر، به‌طور معنی‌داری بالاتر بود. همچنین بین نمره کل سواد بیمه‌ای و وضعیت تأهل رابطه معنی‌داری مشاهده شد. نتیجه‌گیری: هرچند سطح سواد بیمه‌ای در جمعیت مورد مطالعه نسبتاً مطلوب ارزیابی شد. با توجه به اهمیت سواد بیمه‌ای بیمه‌شدگان در اتخا‌ذ بهترین تصمیم هنوز بخش‌هایی از جامعه، به‌ویژه افراد با تحصیلات و درآمد پایین و زنان نیازمند آموزش هستند. بهبود آموزش‌های عمومی برای این گروه‌ها می‌تواند نقش مهمی در ارتقاء بهره‌برداری صحیح از خدمات بیمه‌ای ایفا کند. 2 Introduction: Health insurance literacy, as a subset of health literacy, plays a crucial role in empowering individuals to effectively utilize insurance services. A sound understanding of insurance concepts and procedures enables more informed decision-making regarding health and medical care. Given its importance, the present study aimed to assess the level of insurance literacy and identify its determinants among the insured population of the Health Insurance Organization in Yazd in 2025. Methods: This descriptive-analytical, applied, cross-sectional study employed a survey design. Data were collected from a random sample of 249 insured individuals who visited the health insurance contracting offices in Yazd. A standardized insurance literacy questionnaire was used for data collection. Descriptive statistics and analytical tests, including the Mann–Whitney and Kruskal–Wallis tests, were applied using SPSS version 27. Results: Overall, 63.8% of participants demonstrated high or very high levels of insurance literacy. The highest mean score was observed in the “information access” domain, while the lowest pertained to “functional skills.” Men, individuals with higher education, and those with higher income showed significantly greater insurance literacy scores. A significant association was also found between total insurance literacy and marital status. Conclusion: Although the overall level of insurance literacy among the study population was relatively satisfactory, certain subgroups—particularly women and individuals with lower education and income levels—still require targeted educational interventions. Enhancing public education for these groups can substantially improve the effective utilization of health insurance services. 223 236 2025/05/182025/05/132025/09/212025/09/13 1404/6/22 2025/09/282025/10/42025/11/162025/11/24 1404/9/3 فائزه خالقی Faeze Khaleghi مرکز تحقیقات مدیریت و سیاست‌گذاری سلامت، گروه علوم مدیریت و اقتصاد سلامت، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران faezehkhaleghi22@gmail.com عطیه دهقان نیری Atiyeh Dehghan Niri مرکز تحقیقات مدیریت و سیاست‌گذاری سلامت، گروه علوم مدیریت و اقتصاد سلامت، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران atydgn82@gmail.com سید مسعود موسوی Seyed Masood Mousavi مرکز تحقیقات مدیریت و سیاست‌گذاری سلامت، گروه علوم مدیریت و اقتصاد سلامت، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران m.mousavihp93@gmail.com رضا والاگوهر Reza Valagohar مرکز ملی تحقیقات بیمه سلامت، تهران، ایران rvalagohar3@gmail.com نیما غزل Nima Ghazal گروه اپیدمیولوژی و آمار زیستی، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران nimaghazal77@gmail.com محمد رنجیر Mohammad Ranjbar مرکز تحقیقات مدیریت و سیاست‌گذاری سلامت، گروه علوم مدیریت و اقتصاد سلامت، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران ranjbar3079@gmail.com Insurance Literacy Health Insurance Insured سواد بیمه‌ای بیمه سلامت بیمه شده 1. Call KT, Conmy A, Alarcón G, Hagge SL, Simon AB. Health insurance literacy: how best to measure and does it matter to health care access and affordability? Research in Social and Administrative Pharmacy. 2021;17(6):1166-73.##2. Zarrinkolah A, Dashti F, Abedi H, Masoudi SM. A study of puberty health literacy level of the first 14-16 year girls grade high school students in the Eghlid city. Journal of health literacy. 2016;1(3):164-71.##3. Holst L, Rademakers JJ, Brabers AE, de Jong JD. Measuring health insurance literacy in the Netherlands–First results of the HILM-NL questionnaire. Health Policy. 2022;126(11):1157-62.##4. Paez KA, Mallery CJ, Noel H, Pugliese C, McSorley VE, Lucado JL, et al. Development of the Health Insurance Literacy Measure (HILM): conceptualizing and measuring consumer ability to choose and use private health insurance. Journal of health communication. 2014;19(sup2):225-39.##5. Bastani P, Samadbeik M, Dinarvand R, Kashefian-Naeeini S, Vatankhah S. Qualitative analysis of national documents on health care services and pharmaceuticalspurchasing challenges: evidence from Iran. BMC health services research. 2018;18:1-9.##6. Kim J, Braun B, Williams AD. Understanding health insurance literacy: A literature review. Family and Consumer Sciences Research Journal. 2013;42(1):3-13.##7. Urstad KH, Andersen MH, Larsen MH, Borge CR, Helseth S, Wahl AK. Definitions and measurement of health literacy in health and medicine research: a systematic review. BMJ open. 2022;12(2):e056294.##8. Koay K, Schofield P, Jefford M. Importance of health literacy in oncology. Asia‐Pacific Journal of Clinical Oncology. 2012;8(1):14-23.##9. Quincy L. Measuring health insurance literacy: A call to action. Yonkers: Consumers :union:. 2012.##10. Ho A. Health insurance. Encyclopedia of Global Bioethics. 2015:1-9.##11. Abdollahipour F, Rahimifroshani A, Jaafaripooyan E. Insurance Literacy and the Affecting Factors Related to the Insured of the Health Insurance Organization in Ilam. Iranian Journal of Health Insurance. 2020;3(3):210-21.##12. Khera N, Zhang N, Hilal T, Durani U, Lee M, Padman R, et al. Association of health insurance literacy with financial hardship in patients with cancer. JAMA Network Open. 2022;5(7):e2223141-e.##13. Mathur T, Das G, Gupta H. Examining the influence of health insurance literacy and perception on the people preference to purchase private voluntary health insurance. Health services management research. 2018;31(4):218-32.##14. Bagheri P, Abadi A, Zarei E. Health Insurance Literacy among the Insured person of the Health Insurance Organization in Tehran, Iran. Payesh (Health Monitor) Journal. 2024;23(6):865-74.##15. Sahrayi M, Panahi R, Kazemi S-s, Rostam Z-G, Rezaei H, Jorvand R. The study of Health Literacy of adults in Karaj. Journal of Health Literacy. 2017;1(4):230-8.##16. Vardell EJ. Health insurance literacy: how people understand and make health insurance purchase decisions: The University of North Carolina at Chapel Hill; 2017.##17. Borji M, Tarjoman A, Otaghi M, Salimi E, Naseri A. Health literacy level and its related factors among the elderlies in Ilam in 2015. Iran Journal of Nursing. 2017;30(108):33-43.##18. Tehrani Banihashemi S-A, Haghdoost AA, Amirkhani MA, Alavian S-M, Asgharifard H, Baradaran H, et al. Health literacy and the influencing factors: a study in five provinces of Iran. Strides in development of medical education. 2007;4(1):1-9.##19. Boes S, Liu Y. Do individuals with better health insurance system knowledge make better decisions about their health plans? Applied Economics. 2024;56(59):8867-83.##20. Holst L, Brabers AEM, Rademakers JJDJM, de Jong JD. The role of health insurance literacy in the process and outcomes of choosing a health insurance policy in the Netherlands. BMC Health Services Research. 2023;23(1):1002.##21. McCormack L, Bann C, Uhrig J, Berkman N, Rudd R. Health insurance literacy of older adults. Journal of Consumer Affairs. 2009;43(2):223-48.##22. Loewenstein G, Friedman JY, McGill B, Ahmad S, Linck S, Sinkula S, et al. Consumers’ misunderstanding of health insurance. Journal of Health Economics. 2013;32(5):850-62.##23. Norton M, Hamel L, Brodie M. Assessing Americans’ Familiarity with Health Insurance Terms and Concepts; The Henry J. Kaiser Family Foundation, KFF: San Francisco, CA, USA. 2014.##24. Ståhl C, Karlsson EA, Sandqvist J, Hensing G, Brouwer S, Friberg E, et al. Social insurance literacy: a scoping review on how to define and measure it. Disability and rehabilitation. 2021;43(12):1776-85.##25. Villagra VG, Bhuva B, Coman E, Smith DO, Fifield J. Health insurance literacy: disparities by race, ethnicity, and language preference. Am J Manag Care. 2019;25(3):e71-e5.##26. Ali HS, Parisa S, Amir B. Investigating the role of insurance literacy level with the approach of people's preference for purchasing life insurance in order to improve insurance penetration rate: Islamic Azad University of Damavand; 2019.##27. Weedige SS, Ouyang H, Gao Y, Liu Y. Decision making in personal insurance: Impact of insurance literacy. Sustainability. 2019;11(23):6795.##28. Bardy TL. Assessing health insurance literacy in Switzerland: first results from a measurement tool. European Journal of Public Health. 2024;34(2):237-43.##29. Jafari A, Nejatian M, Momeniyan V, Barsalani FR, Tehrani H. Mental health literacy and quality of life in Iran: a cross-sectional study. BMC psychiatry. 2021;21(1):499.##30. Edward J, Wiggins A, Young MH, Rayens MK. Significant disparities exist in consumer health insurance literacy: implications for health care reform. HLRP: Health Literacy Research and Practice. 2019;3(4):e250-e8.##31. Furtado KS, Kaphingst KA, Perkins H, Politi MC. Health insurance information-seeking behaviors among the uninsured. Journal of health communication. 2016;21(2):148-58.##32. Politi MC, Kaphingst KA, Kreuter M, Shacham E, Lovell MC, McBride T. Knowledge of health insurance terminology and details among the uninsured. Medical Care Research and Review. 2014;71(1):85-98.##33. Akhavan Behbahani A, Alidoost S, Masoudi Asl I, Rahbari Bonab M. Investigating the performance of Iran’s health insurance organization and providing solutions for improvement: A mixed method study. Iran J Health Insur. 2018;1(3):39-47.##34. Bavandpour E, Azami Z, Bavandpour M, Afsordeh O, Delpisheh A. Survey Effective factors of people's health literacy Kermanshah city. Journal of Health Literacy. 2017;2(2):81-7.##35. Saatchi M, Panahi M, Mozafari AA, Sahebkar M, Azarpakan A, Baigi V, et al. Health literacy and its associated factors: a population-based study, Hormuz Island. 2017.##1. Call KT, Conmy A, Alarcón G, Hagge SL, Simon AB. Health insurance literacy: how best to measure and does it matter to health care access and affordability? Research in Social and Administrative Pharmacy. 2021;17(6):1166-73.##2. Zarrinkolah A, Dashti F, Abedi H, Masoudi SM. A study of puberty health literacy level of the first 14-16 year girls grade high school students in the Eghlid city. Journal of health literacy. 2016;1(3):164-71.##3. Holst L, Rademakers JJ, Brabers AE, de Jong JD. Measuring health insurance literacy in the Netherlands–First results of the HILM-NL questionnaire. Health Policy. 2022;126(11):1157-62.##4. Paez KA, Mallery CJ, Noel H, Pugliese C, McSorley VE, Lucado JL, et al. Development of the Health Insurance Literacy Measure (HILM): conceptualizing and measuring consumer ability to choose and use private health insurance. Journal of health communication. 2014;19(sup2):225-39.##5. Bastani P, Samadbeik M, Dinarvand R, Kashefian-Naeeini S, Vatankhah S. Qualitative analysis of national documents on health care services and pharmaceuticalspurchasing challenges: evidence from Iran. BMC health services research. 2018;18:1-9.##6. Kim J, Braun B, Williams AD. Understanding health insurance literacy: A literature review. Family and Consumer Sciences Research Journal. 2013;42(1):3-13.##7. Urstad KH, Andersen MH, Larsen MH, Borge CR, Helseth S, Wahl AK. Definitions and measurement of health literacy in health and medicine research: a systematic review. BMJ open. 2022;12(2):e056294.##8. Koay K, Schofield P, Jefford M. Importance of health literacy in oncology. Asia‐Pacific Journal of Clinical Oncology. 2012;8(1):14-23.##9. Quincy L. Measuring health insurance literacy: A call to action. Yonkers: Consumers :union:. 2012.##10. Ho A. Health insurance. Encyclopedia of Global Bioethics. 2015:1-9.##11. Abdollahipour F, Rahimifroshani A, Jaafaripooyan E. Insurance Literacy and the Affecting Factors Related to the Insured of the Health Insurance Organization in Ilam. Iranian Journal of Health Insurance. 2020;3(3):210-21.##12. Khera N, Zhang N, Hilal T, Durani U, Lee M, Padman R, et al. Association of health insurance literacy with financial hardship in patients with cancer. JAMA Network Open. 2022;5(7):e2223141-e.##13. Mathur T, Das G, Gupta H. Examining the influence of health insurance literacy and perception on the people preference to purchase private voluntary health insurance. Health services management research. 2018;31(4):218-32.##14. Bagheri P, Abadi A, Zarei E. Health Insurance Literacy among the Insured person of the Health Insurance Organization in Tehran, Iran. Payesh (Health Monitor) Journal. 2024;23(6):865-74.##15. Sahrayi M, Panahi R, Kazemi S-s, Rostam Z-G, Rezaei H, Jorvand R. The study of Health Literacy of adults in Karaj. Journal of Health Literacy. 2017;1(4):230-8.##16. Vardell EJ. Health insurance literacy: how people understand and make health insurance purchase decisions: The University of North Carolina at Chapel Hill; 2017.##17. Borji M, Tarjoman A, Otaghi M, Salimi E, Naseri A. Health literacy level and its related factors among the elderlies in Ilam in 2015. Iran Journal of Nursing. 2017;30(108):33-43.##18. Tehrani Banihashemi S-A, Haghdoost AA, Amirkhani MA, Alavian S-M, Asgharifard H, Baradaran H, et al. Health literacy and the influencing factors: a study in five provinces of Iran. Strides in development of medical education. 2007;4(1):1-9.##19. Boes S, Liu Y. Do individuals with better health insurance system knowledge make better decisions about their health plans? Applied Economics. 2024;56(59):8867-83.##20. Holst L, Brabers AEM, Rademakers JJDJM, de Jong JD. The role of health insurance literacy in the process and outcomes of choosing a health insurance policy in the Netherlands. BMC Health Services Research. 2023;23(1):1002.##21. McCormack L, Bann C, Uhrig J, Berkman N, Rudd R. Health insurance literacy of older adults. Journal of Consumer Affairs. 2009;43(2):223-48.##22. Loewenstein G, Friedman JY, McGill B, Ahmad S, Linck S, Sinkula S, et al. Consumers’ misunderstanding of health insurance. Journal of Health Economics. 2013;32(5):850-62.##23. Norton M, Hamel L, Brodie M. Assessing Americans’ Familiarity with Health Insurance Terms and Concepts; The Henry J. Kaiser Family Foundation, KFF: San Francisco, CA, USA. 2014.##24. Ståhl C, Karlsson EA, Sandqvist J, Hensing G, Brouwer S, Friberg E, et al. Social insurance literacy: a scoping review on how to define and measure it. Disability and rehabilitation. 2021;43(12):1776-85.##25. Villagra VG, Bhuva B, Coman E, Smith DO, Fifield J. Health insurance literacy: disparities by race, ethnicity, and language preference. Am J Manag Care. 2019;25(3):e71-e5.##26. Ali HS, Parisa S, Amir B. Investigating the role of insurance literacy level with the approach of people's preference for purchasing life insurance in order to improve insurance penetration rate: Islamic Azad University of Damavand; 2019.##27. Weedige SS, Ouyang H, Gao Y, Liu Y. Decision making in personal insurance: Impact of insurance literacy. Sustainability. 2019;11(23):6795.##28. Bardy TL. Assessing health insurance literacy in Switzerland: first results from a measurement tool. European Journal of Public Health. 2024;34(2):237-43.##29. Jafari A, Nejatian M, Momeniyan V, Barsalani FR, Tehrani H. Mental health literacy and quality of life in Iran: a cross-sectional study. BMC psychiatry. 2021;21(1):499.##30. Edward J, Wiggins A, Young MH, Rayens MK. Significant disparities exist in consumer health insurance literacy: implications for health care reform. HLRP: Health Literacy Research and Practice. 2019;3(4):e250-e8.##31. Furtado KS, Kaphingst KA, Perkins H, Politi MC. Health insurance information-seeking behaviors among the uninsured. Journal of health communication. 2016;21(2):148-58.##32. Politi MC, Kaphingst KA, Kreuter M, Shacham E, Lovell MC, McBride T. Knowledge of health insurance terminology and details among the uninsured. Medical Care Research and Review. 2014;71(1):85-98.##33. Akhavan Behbahani A, Alidoost S, Masoudi Asl I, Rahbari Bonab M. Investigating the performance of Iran’s health insurance organization and providing solutions for improvement: A mixed method study. Iran J Health Insur. 2018;1(3):39-47.##34. Bavandpour E, Azami Z, Bavandpour M, Afsordeh O, Delpisheh A. Survey Effective factors of people's health literacy Kermanshah city. Journal of Health Literacy. 2017;2(2):81-7.##35. Saatchi M, Panahi M, Mozafari AA, Sahebkar M, Azarpakan A, Baigi V, et al. Health literacy and its associated factors: a population-based study, Hormuz Island. 2017. ##

نقش و کارکردهای هوش مصنوعی در بیمه سلامت؛ ارائه چارچوبی برای نظام بیمه سلامت ایران A systematic scoping review of Artificial Intelligence Role and Functions in Optimizing Health Insurance Processes; Presenting a Framework for Iran's Health Insurance System 1 1 مقدمه: با توجه به پیشرفت‌های چشمگیر هوش مصنوعی (AI) در حوزه سلامت و افزایش نیاز به بهینه‌سازی خدمات بیمه درمانی، استفاده از این فناوری می‌تواند منجر به بهبود فرآیندهای مدیریتی، کاهش تقلب، بهینه‌سازی هزینه‌ها و ارائه خدمات شخصی‌سازی‌شده به بیمه‌شدگان شود. این پژوهش با هدف بررسی نقش و کارکردهای هوش مصنوعی در بیمه سلامت و ارائه الگویی کاربردی برای استفاده از آن در سیستم بیمه‌ای ایران انجام شد. روش بررسی: این مطالعه کاربردی در سال ۱۴۰۳ به شیوه ترکیبی در دو فاز اصلی شامل: ۱. مرور حوزه ای نظام‌مند (systematic scoping review) جهت شناسایی کاربردهای هوش مصنوعی در بیمه های سلامت و ۲. برگزاری پانل خبرگان جهت تایید اعتبار مولفه های بدست آمده و ارائه الگویی برای بیمه سلامت ایران جهت استفاده از هوش مصنوعی انجام شد. یافته ها: مرور حوزه‌ای نظام‌مند منجر به شناسایی ۳۰ مطالعه واجد شرایط شد. اعتبارسنجی توسط پانل خبرگان به ارائه چارچوب نهایی متشکل از پنج حوزه اصلی و ۱۴ زیرحوزه برای کاربرد هوش مصنوعی در نظام بیمه سلامت ایران انجامید. حوزه‌های کلیدی عبارت‌اند از: مدیریت سلامت جمعیت، تشخیص و پیشگیری از تقلب، افزایش بهره‌وری عملیاتی، بهینه‌سازی هزینه‌ها و سیاست‌گذاری. نتیجه‌گیری: هوش مصنوعی با توانایی تحلیل حجم عظیمی از داده‌های سلامت، پیش‌بینی هزینه‌های درمان، تشخیص تقلب و خودکارسازی فرآیندهای اداری، نقش کلیدی در افزایش کارایی و کاهش هزینه‌های بیمه‌های سلامت دارد. با این حال، پیاده‌سازی این فناوری نیازمند توسعه زیرساخت‌های لازم، تدوین سیاست‌های حمایتی، و افزایش آگاهی مدیران و کارکنان بیمه است. الگوی پیشنهادی ارائه‌شده در این پژوهش می‌تواند راهنمایی عملی برای سازمان‌های بیمه‌گر در مسیر استفاده بهینه از هوش مصنوعی باشد. 2 Introduction: Given the significant advancements in Artificial Intelligence (AI) in the health sector and the growing need to optimize health insurance services, leveraging this technology can lead to improved management processes, reduced fraud, optimized costs, and the provision of personalized services for policyholders. This research aimed to investigate the role and functions of AI in health insurance and to present a practical framework for its use in the Iranian health insurance system. Methods: This applied study was conducted in 2024 using a mixed-methods approach in two main phases: 1) A systematic scoping review to identify the applications of AI in health insurance, and 2) An expert panel to validate the identified components and propose a framework for utilizing AI in Iran's health insurance system. Results: The systematic scoping review identified 30 eligible studies. Expert panel validation yielded a final framework comprising five main domains and 14 sub-domains for AI application in Iran's health insurance system. The key domains are population health management, fraud detection and prevention, operational productivity enhancement, cost optimization, and policymaking. Conclusion: Artificial Intelligence plays a pivotal role in enhancing the efficiency and reducing the costs of health insurance systems by leveraging its capacity to analyze vast amounts of health data, predict treatment costs, detect fraud, and automate administrative processes. However, the implementation of this technology necessitates the development of appropriate infrastructure, the formulation of supportive policies, and enhancing awareness among insurance managers and staff. The framework proposed in this study can serve as a practical guide for insurance organizations on the path to optimally utilizing AI. 237 250 2025/05/182025/05/132025/09/212025/09/132025/08/20 1404/5/29 2025/09/282025/10/42025/11/162025/11/242025/12/1 1404/9/10 رضا والاگهر Reza Valagohar مرکز ملی تحقیقات بیمه سلامت، تهران، ایران rvalagohar3@gmail.com مرضیه هادیان Marziyeh Hadian مرکز تحقیقات مرکز تحقیقات علوم مدیریت و اقتصاد سلامت، پژوهشکده مدیریت سلامت، دانشگاه علوم پزشکی ایران، تهران، ایران m.hadian68@gmail.com محمد رنجبر Mohammad Ranjbar مرکز تحقیقات مدیریت و سیاستگذاری سلامت، گروه علوم مدیریت و اقتصاد سلامت، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران ranjbar3079@gmail.com طاهره شفقت Tahereh Shafaghat مرکز تحقیقات مدیریت و سیاستگذاری سلامت، گروه علوم مدیریت و اقتصاد سلامت، دانشکده بهداشت، دانشگاه علوم پزشکی شهید صدوقی یزد، یزد، ایران sara.shafaghat@gmail.com Artificial Intelligence Health Insurance Role Iran هوش مصنوعی بیمه سلامت نقش ایران 1. 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Development of an Artificial Intelligence-Based Automated Recommendation System for Clinical Laboratory Tests: Retrospective Analysis of the National Health Insurance Database. JMIR medical informatics. 2020;8(11).##18. Kaushik K, Bhardwaj A, Dwivedi AD, Singh R. Machine Learning-Based Regression Framework to Predict Health Insurance Premiums. International journal of environmental research and public health. 2022;19(13).##19. Orji U, Ukwandu E. Machine learning for an explainable cost prediction of medical insurance. Machine Learning with Applications. 2024;15.##20. Amerirad B, Cattaneo M, Kenett RS, Luciano E. Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies. Risks. 2023;11(1).##21. Choi Y, An J, Ryu S, Kim J. Development and Evaluation of Machine Learning-Based High-Cost Prediction Model Using Health Check-Up Data by the National Health Insurance Service of Korea. International journal of environmental research and public health. 2022;19(20).##22. Johnson M, Albizri A, Harfouche A. Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers. 2023;25(6):2179-95.##23. Mishra Y, Shaw A. Artificial intelligence in the health insurance sector: Sustainable or unsustainable from the lens of ethical- legal and socio-economic standards. The Impact of Climate Change and Sustainability Standards on the Insurance Market: wiley; 2023. p. 57-74.##24. Kapadiya K, Patel U, Gupta R, Alshehri MD, Tanwar S, Sharma G, et al. Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: an Analysis, Architecture, and Future Prospects. Ieee Access. 2022;10:79606-27.##25. Kose I, Gokturk M, Kilic K. An interactive machine-learning-based electronic fraud and abuse detection system in healthcare insurance. Appl Soft Comput J. 2015;36:283-99.##26. 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Artificial Intelligence in Health Insurance: A Bibliometric Review. Proceedings - 2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023; 2023: Institute of Electrical and Electronics Engineers Inc.##31. Yamana H, Okada A, Ono S, Michihata N, Jo T, Yasunaga H. Machine Learning-based Models for Outpatient Prescription of Kampo Formulations: An Analysis of a Health Insurance Claims Database. Journal of epidemiology. 2024;34(1):8-15.##32. Hajialiasgari F, Khanahmadi A, Atashi A. Artificial Intelligence Chatbot in Iran Health Insurance Organization: A New Era in Service Providing. The Iranian Journal of Health Insurance. 2023;6(2):91-102 [In Persian].##33. Imam M, Soliman HY, Abdel-Atty HM. Future Applications of Artificial Intelligence for the Egyptian Universal Health Insurance System. Journal of Health Management. 2023;25(4):709-14.##34. Liu J, Glied S, Yakusheva O, Bevin C, Schlak AE, Yoon S, et al. Using machine-learning methods to predict in-hospital mortality through the Elixhauser index: A Medicare data analysis. Research in nursing & health. 2023;46(4):411-24.##35. Molaei MM, Fatehi M. Digital transformation in health insurance beyond AI and chatbots. Iranian Journal of Health Insurance. 2024;7(3):149-60.##36. TajaddodiNodehi M, HosseiniKhatibani S, Yazdinejad M, Zolfi S. Predicting people’s health insurance costs using machine learning and ensemble learning methods. Iran J Insur Res. 2024;13(1):1-14 [In Persian].##37. Nayak B, Bhattacharyya SS, Krishnamoorthy B. Integrating wearable technology products and big data analytics in business strategy. Journal of Systems and Information Technology. 2019;21(2):255-75.##38. Arab M, Fathian M, AliahmadiJeshfaghani H. Forecast of Medical Expenses of Iran Health Insurance Organization Using Machine Learning Based Methods. The Iranian Journal of Health Insurance. 2022;4(4):269-79 [In Persian].##39. 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Development of an Artificial Intelligence-Based Automated Recommendation System for Clinical Laboratory Tests: Retrospective Analysis of the National Health Insurance Database. JMIR medical informatics. 2020;8(11).##18. Kaushik K, Bhardwaj A, Dwivedi AD, Singh R. Machine Learning-Based Regression Framework to Predict Health Insurance Premiums. International journal of environmental research and public health. 2022;19(13).##19. Orji U, Ukwandu E. Machine learning for an explainable cost prediction of medical insurance. Machine Learning with Applications. 2024;15.##20. Amerirad B, Cattaneo M, Kenett RS, Luciano E. Adversarial Artificial Intelligence in Insurance: From an Example to Some Potential Remedies. Risks. 2023;11(1).##21. Choi Y, An J, Ryu S, Kim J. Development and Evaluation of Machine Learning-Based High-Cost Prediction Model Using Health Check-Up Data by the National Health Insurance Service of Korea. International journal of environmental research and public health. 2022;19(20).##22. Johnson M, Albizri A, Harfouche A. Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing. Information Systems Frontiers. 2023;25(6):2179-95.##23. Mishra Y, Shaw A. Artificial intelligence in the health insurance sector: Sustainable or unsustainable from the lens of ethical- legal and socio-economic standards. The Impact of Climate Change and Sustainability Standards on the Insurance Market: wiley; 2023. p. 57-74.##24. Kapadiya K, Patel U, Gupta R, Alshehri MD, Tanwar S, Sharma G, et al. Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: an Analysis, Architecture, and Future Prospects. Ieee Access. 2022;10:79606-27.##25. Kose I, Gokturk M, Kilic K. An interactive machine-learning-based electronic fraud and abuse detection system in healthcare insurance. Appl Soft Comput J. 2015;36:283-99.##26. Martinez-Millana A, Saez-Saez A, Tornero-Costa R, Azzopardi-Muscat N, Traver V, Novillo-Ortiz D. Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews. Int J Med Inform. 2022;166.##27. Secinaro S, Calandra D, Secinaro A, Muthurangu V, Biancone P. The role of artificial intelligence in healthcare: a structured literature review. BMC medical informatics and decision making. 2021;21(1):125.##28. Ho CWL, Ali J, Caals K. Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance. Bulletin of the World Health Organization. 2020;98(4):263-9.##29. Smith H, Fotheringham K. Exploring remedies for defective artificial intelligence aids in clinical decision-making in post-Brexit England and Wales. Med Law Int. 2022;22(1):33-51.##30. Tiwari R, Kaur H, Sharma S, Kargeti H, Prakash N, Sharma S, editors. Artificial Intelligence in Health Insurance: A Bibliometric Review. Proceedings - 2023 International Conference on Advanced Computing and Communication Technologies, ICACCTech 2023; 2023: Institute of Electrical and Electronics Engineers Inc.##31. Yamana H, Okada A, Ono S, Michihata N, Jo T, Yasunaga H. Machine Learning-based Models for Outpatient Prescription of Kampo Formulations: An Analysis of a Health Insurance Claims Database. Journal of epidemiology. 2024;34(1):8-15.##32. Hajialiasgari F, Khanahmadi A, Atashi A. Artificial Intelligence Chatbot in Iran Health Insurance Organization: A New Era in Service Providing. The Iranian Journal of Health Insurance. 2023;6(2):91-102 [In Persian].##33. Imam M, Soliman HY, Abdel-Atty HM. Future Applications of Artificial Intelligence for the Egyptian Universal Health Insurance System. Journal of Health Management. 2023;25(4):709-14.##34. Liu J, Glied S, Yakusheva O, Bevin C, Schlak AE, Yoon S, et al. Using machine-learning methods to predict in-hospital mortality through the Elixhauser index: A Medicare data analysis. Research in nursing & health. 2023;46(4):411-24.##35. Molaei MM, Fatehi M. Digital transformation in health insurance beyond AI and chatbots. Iranian Journal of Health Insurance. 2024;7(3):149-60.##36. TajaddodiNodehi M, HosseiniKhatibani S, Yazdinejad M, Zolfi S. Predicting people’s health insurance costs using machine learning and ensemble learning methods. Iran J Insur Res. 2024;13(1):1-14 [In Persian].##37. Nayak B, Bhattacharyya SS, Krishnamoorthy B. Integrating wearable technology products and big data analytics in business strategy. Journal of Systems and Information Technology. 2019;21(2):255-75.##38. Arab M, Fathian M, AliahmadiJeshfaghani H. Forecast of Medical Expenses of Iran Health Insurance Organization Using Machine Learning Based Methods. The Iranian Journal of Health Insurance. 2022;4(4):269-79 [In Persian].##39. 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Artificial Intelligence Chatbot in Iran Health Insurance Organization: A New Era in Service Providing. 2023;6(2):91-102 [In persian].##46. Ramezani M, Takian A, Bakhtiari A, Rabiee HR, Fazaeli AA, Sazgarnejad S. The application of artificial intelligence in health financing: a scoping review. Cost Effectiveness and Resource Allocation. 2023;21(1):83.##47. Chen H, Xing J, Yang X, Zhan K. Heterogeneous Effects of Health Insurance on Rural Children's Health in China: A Causal Machine Learning Approach. International journal of environmental research and public health. 2021;18(18).##48. Ramezani M, Takian A, Bakhtiari A, Rabiee HR, Ghazanfari S, Mostafavi H. The application of artificial intelligence in health policy: a scoping review. BMC health services research. 2023;23(1):1416.##49. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthcare Journal. 2019;6(2):94-8. ##

شناسایی عوامل موثر در برنامه‌ریزی درسی مبتنی بر مسئولیت‌پذیری اجتماعی؛ مورد مطالعه: کارکنان سازمان بیمه سلامت ایران Identifying Effective Factors in Curriculum Planning Based on Social Responsibility; Case Study: Iranian Health Insurance Organization Employees 1 1 مقدمه: در سال‌های اخیر، مفهوم مسئولیت‌پذیری اجتماعی به یکی از پایه‌های مهم عملکرد سازمان‌ها، به‌خصوص نهادهای عمومی و خدماتی همچون سازمان بیمه سلامت ایران، تبدیل شده است. بر همین اساس، بسیاری از کشورها تلاش می‌کنند برنامه‌های آموزشی گسترده‌ای برای تقویت مسئولیت‌پذیری اجتماعی در سازمان‌های عمومی تدوین و اجرا کنند. هدف پژوهش حاضر، شناسایی عوامل موثر در برنامه‌ریزی درسی مبتنی بر مسئولیت‌پذیری اجتماعی در میان کارکنان سازمان بیمه سلامت ایران بود. روش بررسی: روش انجام پژوهش از نظر هدف، کاربردی؛ از نظر نوع داده، کیفی؛ و از نظر طراحی، مبتنی بر مصاحبه با خبرگان در نظر گرفته شد. جامعه آماری شامل خبرگان نظری یعنی اعضای هیأت علمی حوزه علوم تربیتی و نیز خبرگان تجربی شامل مسئولان مرتبط با بیمه سلامت ایران بود. بر اساس اصل اشباع نظری و با بهره‌گیری از نمونه‌گیری هدفمند غیرتصادفی، تعداد ۲۰ متخصص به‌عنوان نمونه تحقیق انتخاب شدند. برای جمع‌آوری داده‌ها از مصاحبه‌های نیمه‌ساختاریافته استفاده شد و اعتبار و پایایی ابزار مورد بررسی و تأیید قرار گرفت. در نهایت، داده‌ها با روش تحلیل محتوای کیفی و رویکرد تحلیل تم، و با استفاده از نرم‌افزار MaxQDA نسخه ۲۰۱۸ تحلیل شدند. یافته‌ها:  عوامل موثر در برنامه ریزی درسی مبتنی بر مسئولیت پذیری اجتماعی در سازمان بیمه سلامت عبارتند از هدف شامل مؤلفه‌­های توسعه فردی، توسعه سازمانی، توسعه اجتماعی؛ محتوا شامل مؤلفه‌های آموزش‌های لازم در راستای توسعه فردی، آموزش‌های لازم در راستای توسعه سازمانی، آموزش‌های لازم در راستای توسعه اجتماعی؛ روش شامل مؤلفه‌­های آموزش‌های لازم در راستای توسعه فردی، آموزش‌های لازم در راستای توسعه سازمانی، آموزش‌های لازم در راستای توسعه اجتماعی و ارزشیابی شامل مؤلفه‌­های توسعه فردی، توسعه سازمانی، توسعه اجتماعی. نتیجه‌گیری: مولفه‌های بررسی شده در این پژوهش، نشان می‌دهند که  محتوا، هدف، روش و ارزشیابی ۴ عامل اثرگذار در موفقیت برنامه‌ریزی درسی مبتنی بر مسئولیت‌پذیری اجتماعی در سازمان بیمه سلامت ایران هستند.  2 Introduction: Today, social responsibility has gained special importance as a key principle in organizations, especially in public institutions and services such as the Iranian Health Insurance Organization. Accordingly, many countries are seeking to create comprehensive educational programs to promote social responsibility in public institutions. The aim of the present study was to identify the effective factors in curriculum planning based on social responsibility among the employees of the Iranian Health Insurance Organization. Methods: The research method was applied in terms of purpose; qualitative in terms of data type; and interviewing experts in terms of design (nature). The statistical population included theoretical experts (professors of educational sciences universities) and empirical experts (relevant officials of the Iranian Health Insurance), who were selected as a sample using the saturation principle and a purposeful non-random method, 20 experts. In order to collect data, a semi-structured interview was used, and the validity and reliability of the instrument were examined and confirmed. The data analysis method was qualitative content analysis with a thematic analysis approach using MaxQDA-2018 software. Results: The findings showed that the effective factors in curriculum planning based on social responsibility in the Health Insurance Organization are: the goal includes the components of personal development, organizational development, and social development; the content includes the components of necessary training for personal development, necessary training for organizational development, and necessary training for social development; the method includes the components of necessary training for personal development, necessary training for organizational development, necessary training for social development, and evaluation includes the components of personal development, organizational development, and social development. Conclusion: The components examined in this study show that content, goal, method, and evaluation are the four effective factors in the success of curriculum planning based on social responsibility in the Iranian Health Insurance Organization.  251 262 2025/05/182025/05/132025/09/212025/09/132025/08/202025/08/19 1404/5/28 2025/09/282025/10/42025/11/162025/11/242025/12/12025/08/26 1404/6/4 مسعود بادکوبه Masoud Badkoobeh گروه برنامه‌ریزی درسی، دانشکده علوم تربیتی و مشاوره، واحد رودهن، دانشگاه آزاد اسلامی، تهران، ایران رضا والا Reza Vala گروه برنامه‌ریزی درسی، دانشکده علوم تربیتی و مشاوره، واحد رودهن، دانشگاه آزاد اسلامی، تهران، ایران r.vala@iau.ac.ir ذوالفقار رشیدی Zolfaghar Rashidi گروه مدیریت آموزشی، واحد رودهن، دانشگاه آزاد اسلامی، تهران، ایران zo.rashidi@iau.ac.ir Curriculum Social Responsibility Insurance Health Iran Health Insurance Organization برنامه درسی مسئولیت اجتماعی بیمه سلامت سازمان بیمه سلامت ایران Al Frijat, Y. S., Albawwat, I. E., & Elamer, A. A. (2024). 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طراحی پرسشنامه آموزش سنجش ادراک و رفتار کارکنان سازمان بیمه سلامت ایران Designing a Training Effectiveness Questionnaire to Assess Perception and Behavior of Employees in Iranian Health Insurance Organization 1 1 مقدمه: توانمندسازی کارکنان از ارکان بنیادین توسعه سازمانی است و آموزش، به‌عنوان مؤثرترین شاخص آن، نقش حیاتی در ارتقاء شناخت، رفتار و مشارکت کارکنان ایفا می‌کند. پژوهش حاضر با هدف طراحی و اعتبارسنجی پرسشنامه‌ای برای سنجش اثربخشی آموزش در سطح سوم (رفتاری-شناختی) در سازمان بیمه سلامت ایران انجام شده است. این سطح بر ادراک و کاربرد عملی آموخته‌ها توسط کارآموزان تمرکز دارد و از اصول گشتالت در طراحی تجربه یادگیری بهره می‌گیرد. روش بررسی: مطالعه حاضر از نوع کیفی-توصیفی با رویکرد ابزاری-توسعه‌ای بوده و از تحلیل محتوای جهت‌دار برای استخراج مؤلفه‌های نظری استفاده شد. یافته‌ها: در مرحله اول، گویه‌های اولیه از منابع معتبر استخراج و توسط پنج داور خبره از نظر سه بُعد «تناسب موضوع»، «وضوح» و «اهمیت» بررسی شدند. در مرحله دوم، پرسشنامه در پیش‌آزمون برای ۴۳ نفر از مسئولان آموزش استان‌ها ارسال شد. برای سنجش روایی محتوا، از ضریب لاشه استفاده شد که نشان داد بیش از ۸۵ درصد گویه‌ها دارای اعتبار بالا (ضریب ≥ ۰.۸۰) هستند. پایایی پرسشنامه نیز با آلفای کرونباخ ۰.۹۸۱ تأیید شد که نشان‌دهنده همبستگی بالا و عدم نیاز به حذف گویه‌هاست. تحلیل‌های توصیفی نیز پراکندگی مناسب و استفاده متعادل از مقیاس را نشان دادند. نتیجه‌گیری: نتایج پژوهش حاکی از آن است که پرسشنامه طراحی‌شده از اعتبار و پایایی مطلوبی برخوردار بوده و می‌تواند به‌عنوان ابزاری معتبر برای سنجش اثربخشی آموزش در سطح ۳ (رفتاری) کارکنان سازمان بیمه سلامت مورد استفاده قرار گیرد. 2 Introduction: Employee empowerment is a fundamental pillar of organizational development, with training recognized as its most influential component. Effective training plays a vital role in enhancing employees’ awareness, behavior, and participation. This study aimed to design and validate a questionnaire for assessing training effectiveness at Level 3 (behavioral–cognitive) within the Iranian Health Insurance Organization. This level focuses on learners’ perception and practical application of acquired knowledge and draws upon Gestalt principles in learning experience design. Methods: The research employed a qualitative–descriptive methodology with an instrumental–developmental approach, using directed content analysis to extract theoretical components. Results: In the first phase, initial items were derived from credible sources and reviewed by five expert evaluators across three dimensions: “topic relevance,” “clarity,” and “importance.” In the second phase, the questionnaire was pilot-tested with 43 provincial training officers. Content validity was assessed using Lashé’s coefficient, revealing that over 85% of items held high validity (coefficient ≥ 0.80). Reliability was confirmed through Cronbach’s alpha (α = 0.981), indicating strong internal consistency and no need for item elimination. Descriptive statistics further demonstrated appropriate item dispersion and balanced scale usage. Conclusion: The findings confirm that the developed questionnaire possesses strong validity and reliability, making it a suitable instrument for evaluating Level 3 (behavioral) training effectiveness among employees of the Health Insurance Organization. 263 276 2025/05/182025/05/132025/09/212025/09/132025/08/202025/08/192025/08/20 1404/5/29 2025/09/282025/10/42025/11/162025/11/242025/12/12025/08/262025/11/25 1404/9/4 محمدرضا حسینی Mohammadreza Hosseini گروه جامعه‌شناسی، دانشکده علوم انسانی، دانشگاه آیت‌الله بروجردی، بروجرد، ایران m.hosseini@abru.ac.ir ابوالفضل بوجاری Abolfazl Boujari سازمان بیمه سلامت ایران، تهران، ایران dr.boojari@gmail.com هادی زمانی Hadi Zamani دانشگاه تهران، پردیس بین المللی کیش، کیش، ایران hadizamani1404@yahoo.com Employee Empowerment Training Effectiveness Questionnaire Assessment Tool Design Level 3 Learning توانمندسازی کارکنان پرسشنامه اثربخشی آموزشی طراحی ابزار سنجش یادگیری سطح سوم 1. jay, shani(2025). Measuring Training Effectiveness: A Practical Guide. Published https://www.aihr.com/blog/measuring-training-effectiveness##2. Zaraket,Wael , Garios,Robert , Abdel Malek,Layla.(2018). The Impact of Employee Empowerment on the Organizational Commitment. International Journal of Human Resource##3. Atkinson, Rita L. and Atkinson, Richard C. and Smith, Edward E. and Bem, Dale J. and Nolen Hoeksma, Susan (2010). The complete text of Hilgard's Psychology. Translated by Dr. Mohammad Taghi Baraheni and colleagues. Thirteenth edition, Tehran: Roshd Publications.##4. Santos,Amalia & Stuart,Mark. )2003( .Employee perceptions and their influence on training effectiveness. 13 .27-45. published:https://doi.org/10.1111/j.1748-8583.2003.tb00082.x##5. Rye,Marta, Torres, Elisa M., Friborg ,Oddgeir, Skre, Ingunn & Aarons ,Gregory A(2017). The Evidence-based Practice Attitude Scale-36 (EBPAS-36): a brief and pragmatic measure of attitudes to evidence-based practice validated in US and Norwegian samples. Implementation Science.12(44)##6.LXD (2025). Gestalt Theory of Learning.published: https://B2n.ir/em6371##7. Landsverk, Nils Gunnar & Olsen, Nina R , Brovold ,Th .(2023).Instruments measuring -evidence-based practice behavior, attitudes, and self-efficacy among healthcare professionals: a systematic review of measurement properties. Implementation Science.Volume 18(42)##8. Myrna Goddess & Elois &Washington. (.Gestalt Psychology,Studies: 8(3),284-299##9. Phillips, M. (1976). The Application of Gestalt Principles in Classroom Teaching. Group & Organization Studies, 1(1), 82-98: https://doi.org/10.1177/105960117600100108##10. DiGennaro Reed, Florence D & Novak, Matthew D& Erath, Tyler G&Brand, Denys & Henley,AmyJ.(2020).Pinpointing-and-Measuring-Employee-Behavior.publeshed: https://B2n.ir/rn7365##11. jay, shani(2025). Measuring Training Effectiveness: A Practical Guide. Published https://www.aihr.com/blog/measuring-training-effectiveness##12. Lukes, Martin& Stephan, Ute.(2017). Measuring employee innovation: A review of existing scales and the development of the innovative behavior and innovation support inventories across cultures. International Journal of Entrepreneurial Behavior & Research 23 (1): 136–158.##13. cali, carmelo. (2020). Gestalt/Gestalt Theory.publesded: https://B2n.ir/bq4805##14. Rye,Marta, Torres, Elisa M., Friborg ,Oddgeir, Skre, Ingunn & Aarons ,Gregory A(2017). The Evidence-based Practice Attitude Scale-36 (EBPAS-36): a brief and pragmatic measure of attitudes to evidence-based practice validated in US and Norwegian samples. Implementation Science.12(44)##15. Cohen, L.T., Corrigan, J.M., and Donaldson, M.S. (1999). To err is human. Washington, DC: National Academy Press.##1. jay, shani(2025). Measuring Training Effectiveness: A Practical Guide. Published https://www.aihr.com/blog/measuring-training-effectiveness##2. Zaraket,Wael , Garios,Robert , Abdel Malek,Layla.(2018). The Impact of Employee Empowerment on the Organizational Commitment. International Journal of Human Resource##3. Atkinson, Rita L. and Atkinson, Richard C. and Smith, Edward E. and Bem, Dale J. and Nolen Hoeksma, Susan (2010). The complete text of Hilgard's Psychology. Translated by Dr. Mohammad Taghi Baraheni and colleagues. Thirteenth edition, Tehran: Roshd Publications.##4. Santos,Amalia & Stuart,Mark. )2003( .Employee perceptions and their influence on training effectiveness. 13 .27-45. published:https://doi.org/10.1111/j.1748-8583.2003.tb00082.x##5. Rye,Marta, Torres, Elisa M., Friborg ,Oddgeir, Skre, Ingunn & Aarons ,Gregory A(2017). The Evidence-based Practice Attitude Scale-36 (EBPAS-36): a brief and pragmatic measure of attitudes to evidence-based practice validated in US and Norwegian samples. Implementation Science.12(44)##6.LXD (2025). Gestalt Theory of Learning.published: https://B2n.ir/em6371##7. Landsverk, Nils Gunnar & Olsen, Nina R , Brovold ,Th .(2023).Instruments measuring -evidence-based practice behavior, attitudes, and self-efficacy among healthcare professionals: a systematic review of measurement properties. Implementation Science.Volume 18(42)##8. Myrna Goddess & Elois &Washington. (.Gestalt Psychology,Studies: 8(3),284-299##9. Phillips, M. (1976). The Application of Gestalt Principles in Classroom Teaching. Group & Organization Studies, 1(1), 82-98: https://doi.org/10.1177/105960117600100108##10. DiGennaro Reed, Florence D & Novak, Matthew D& Erath, Tyler G&Brand, Denys & Henley,AmyJ.(2020).Pinpointing-and-Measuring-Employee-Behavior.publeshed: https://B2n.ir/rn7365##11. jay, shani(2025). Measuring Training Effectiveness: A Practical Guide. Published https://www.aihr.com/blog/measuring-training-effectiveness##12. Lukes, Martin& Stephan, Ute.(2017). Measuring employee innovation: A review of existing scales and the development of the innovative behavior and innovation support inventories across cultures. International Journal of Entrepreneurial Behavior & Research 23 (1): 136–158.##13. cali, carmelo. (2020). Gestalt/Gestalt Theory.publesded: https://B2n.ir/bq4805##14. Rye,Marta, Torres, Elisa M., Friborg ,Oddgeir, Skre, Ingunn & Aarons ,Gregory A(2017). The Evidence-based Practice Attitude Scale-36 (EBPAS-36): a brief and pragmatic measure of attitudes to evidence-based practice validated in US and Norwegian samples. Implementation Science.12(44)##15. Cohen, L.T., Corrigan, J.M., and Donaldson, M.S. (1999). To err is human. Washington, DC: National Academy Press ##

تباهندگی مالی: رویکردی سیاستی به کاهش اثرات مالی بر بیماران در نظام بیمه سلامت ایران Financial Toxicity: A Policy Approach to Reducing Financial Impacts on Patients in the Iranian Health Insurance System 1 1 تباهندگی مالی به‌عنوان بار اقتصادی و فشار روانی ناشی از هزینه‌های درمان سرطان و بیماری‌های مزمن، به یکی از چالش‌های رو‌به‌افزایش نظام سلامت ایران تبدیل شده است و بیماران را در معرض پیامدهایی همچون بدهی، کاهش کیفیت زندگی و حتی ترک یا ناتمام‌ماندن درمان قرار می‌دهد. با وجود استقرار پوشش همگانی بیمه سلامت، محدودیت منابع، سهم بالای پرداخت از جیب و پوشش ناکافی داروها و فناوری‌های نوین درمانی، همچنان فشار مالی قابل توجهی بر بیماران وارد می‌شود. مرور شواهد بین‌المللی نشان می‌دهد که اقداماتی نظیر ناوبری مالی بیمار، حمایت‌های مالی مستقیم، تعمیق و گسترش پوشش بیمه‌ای، کاهش سهم پرداخت از جیب، بهبود شفافیت هزینه‌ها و یکپارچه‌سازی کارکردی سازمان‌های بیمه‌گر، می‌تواند نقش مؤثری در کاهش بار مالی بیماران و ارتقای عدالت در دسترسی به خدمات سلامت داشته باشد. این خلاصه سیاستی با مرور چالش‌های موجود و ارائه توصیه‌های عملی مبتنی بر شواهد، بر ضرورت اتخاذ سیاست‌های یکپارچه، پایدار و چندبعدی برای کاهش تباهندگی مالی در نظام بیمه سلامت ایران تأکید می‌کند. 2 Financial Toxicity, defined as the economic burden and psychological distress caused by the costs of treating cancer and chronic diseases, has become an increasing challenge in Iran’s health system, placing patients at risk of debt, reduced quality of life, and even treatment discontinuation or incompletion. Despite the implementation of universal health insurance coverage, limited resources, high out-of-pocket payments, and insufficient coverage of drugs and advanced therapies continue to impose substantial financial pressure on patients. A review of international evidence indicates that interventions such as patient financial navigation, direct financial support, expanded and deeper insurance coverage, reduction of out-of-pocket payments, improved cost transparency, and functional integration of insurance organizations can effectively reduce patients’ financial burden and enhance equity in access to health services. This policy brief reviews current challenges and provides practical, evidence-based recommendations, emphasizing the need to adopt comprehensive, sustainable, and multi-dimensional policies to reduce financial toxicity within Iran’s health insurance system. 277 284 2025/05/182025/05/132025/09/212025/09/132025/08/202025/08/192025/08/202025/09/28 1404/7/6 2025/09/282025/10/42025/11/162025/11/242025/12/12025/08/262025/11/252025/11/18 1404/8/27 مریم سیدنژاد Maryam Seyed-Nezhad مرکز ملی تحقیقات بیمه سلامت، تهران، ایران mseyednezhad@atiyehsazan.ir محمد مرادی‌جو Mohammad Moradi-Joo مرکز تحقیقات عوامل اجتماعی موثر بر سلامت، دانشگاه علوم پزشکی یاسوج، یاسوج، ایران moradi2011@yahoo.com Financial Toxicity Health Insurance Financial Protection Out-of-Pocket Payment Health Policy Universal Health Coverage (UHC) تباهندگی مالی بیمه سلامت حمایت مالی پرداخت از جیب سیاست‌گذاری سلامت پوشش همگانی سلامت ##1. Carrera PM, Kantarjian HM, Blinder VS. The financial burden and distress of patients with cancer: Understanding and stepping-up action on the financial toxicity of cancer treatment. CA Cancer J Clin. 2018;68(2):153-65.##2. Abrams HR, Durbin S, Huang CX, Johnson SF, Nayak RK, Zahner GJ, Peppercorn J. Financial toxicity in cancer care: origins, impact, and solutions. Translational behavioral medicine. 2021 Nov 1;11(11):2043-54.##3. Collado L, Brownell I. The crippling financial toxicity of cancer in the United States. Cancer biology & therapy. 2019 Oct 3;20(10):1301-3.##4. Kitaw TA, Tilahun BD, Zemariam AB, Getie A, Bizuayehu MA, Haile RN. The financial toxicity of cancer: unveiling global burden and risk factors–a systematic review and meta-analysis. BMJ Global Health. 2025 Feb 10;10(2).##5. Wang S, Wang J, Kang H, Zeng L, Liu G, Qiu Y, Wei M. Assessment of the prevalence and related factors of financial toxicity in cancer patients based on the COST scale: A systematic review and meta-analysis. European Journal of Oncology Nursing. 2024 Feb 1;68:102489.##6. Davari M, Haycox A, Walley T. The Iranian health insurance system; past experiences, present challenges and future strategies. Iranian journal of public health. 2012 Sep 1;41(9):1.##7. Khatooni E, Ahmadnezhad E, Olyaeemanesh A, Majdzadeh R. The Dilemma of Underutilized Health Insurance: A Matched Case-Control Study Investigating Reasons in Iran’s Free Universal Health Insurance. Iranian Journal of Public Health. 2023 Dec;52(12):2643.##8. Piroozi B, Zarei B, Ghaderi B, Safari H, Moradi G, Rezaei S, Ghaderi M, Amirhosseini S, Mohamadi-Bolbanabad A. Catastrophic health expenditure and its determinants in households with gastrointestinal cancer patients: evidence from new health system reform in Iran. International Journal of Human Rights in Healthcare. 2019 Jul 19;12(4):249-57.##9. Ahmadi F, Farrokh-Eslamlou H, Yusefzadeh H, Alinia C. Incidence of household catastrophic and impoverishing health expenditures among patients with Breast Cancer in Iran. BMC Health Services Research. 2021 Apr 9;21(1):327.##10. Doshmangir L, Rashidian A, Kouhi F, Gordeev VS. Setting health care services tariffs in Iran: half a century quest for a window of opportunity. International Journal for Equity in Health. 2020 Jul 6;19(1):112.##11. Sajadi HS, Ehsani-Chimeh E, Majdzadeh R. Universal health coverage in Iran: where we stand and how we can move forward. Medical journal of the Islamic Republic of Iran. 2019 Feb 22;33:9.##12. Haghjou L, Mounesan L, Shamsi A, Nazari M, Bahmanziari N, Shirkhoda M, Amanpour S, Abdollahi A, Zendehdel K, Rashidian H. The impact of economic sanctions on cancer diagnosis and treatment in Iran: a qualitative study. International Journal for Equity in Health. 2024 Nov 30;23(1):258.##13. Nazari M, Haghjou L, Rashidian H, Zendehdel K, Bahmanziari N, Haghjoo A, Shamsi A, Mounesan L. Effects of economic sanctions on cancer care for patients in Iran: a qualitative study. BMC Health Services Research. 2025 Mar 11;25(1):361.##14. Lentz R, Benson III AB, Kircher S. Financial toxicity in cancer care: prevalence, causes, consequences, and reduction strategies. Journal of surgical oncology. 2019 Jul;120(1):85-92.##15. Meisenberg BR, Varner A, Ellis E, Ebner S, Moxley J, Siegrist E, et al. Patient Attitudes Regarding the Cost of Illness in Cancer Care. Oncologist. 2015;20(10):1199-204.##16. Zafar SY, Abernethy AP. Financial toxicity, Part I: a new name for a growing problem. Oncology (Williston Park). 2013;27(2):80-1, 149.##17. Shankaran V, Leahy T, Steelquist J, Watabayashi K, Linden H, Ramsey S, et al. Pilot Feasibility Study of an Oncology Financial Navigation Program. J Oncol Pract. 2018;14(2):e122-e129.##18. Witte J, Mehlis K, Surmann B, Lingnau R, Damm O, Greiner W, et al. Methods for measuring financial toxicity after cancer diagnosis and treatment: a systematic review and its implications. Ann Oncol. 2019;30(7):1061-70.##19. Ubel PA, Abernethy AP, Zafar SY. Full disclosure - out-of-pocket costs as side effects. N Engl J Med. 2013;369(16):1484-6.##20. Wagstaff A, Dmytraczenko T, Almeida G, Buisman L, Hoang-Vu Eozenou P, Bredenkamp C, et al. Assessing Latin America's Progress Toward Achieving Universal Health Coverage. Health Aff (Millwood). 2015;34(10):1704-12.##21. Kutzin J. Health financing for universal coverage and health system performance: concepts and implications for policy. Bull World Health Organ. 2013;91(8):602-11.##22. Mathauer I, Torres L, Kutzin J, Jakab M, Hanson K. Pooling financial resources for universal health coverage: options for reform. Bull World Health Organ. 2020;98(2):132-9.##23. Lagomarsino G, Garabrant A, Adyas A, Muga R, Otoo N. Moving towards universal health coverage: health insurance reforms in nine developing countries in Africa and Asia. Lancet. 2012;380(9845):933-43.##24. Kutzin J, Cashin C, Jakab M. Implementing health financing reform: lessons from countries in transition. Copenhagen: World Health Organization Regional Office for Europe; 2010. ##