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روند پژوهش‌های اقتصاد و بیمه سلامت Research Trends in Economics and Health Insurance 1 145 148 2024/12/23 1403/10/3 2024/12/17 1403/9/27 شهرام توفیقی Shahram Tofighi مرکز ملی تحقیقات بیمه سلامت، تهران، ایران ## ##

تحول دیجیتال در بیمه سلامت فراتر از هوش مصنوعی و چت‌بات‌ها Digital Transformation in Health Insurance Beyond AI and Chatbots 1 1 بیمه سلامت در حال تجربه یک تغییر اساسی  با بهره‌گیری از فناوری‌های دیجیتال است که روش‌های جدیدی را برای ارتقای کیفیت خدمات و کاهش هزینه‌ها فراهم می‌کند. این مطالعه به بررسی چگونگی تحول آینده بیمه سلامت با استفاده از راهکارهای مدرن نظیر هوش مصنوعی، داده‌های کلان، اینترنت اشیاء و سیستم‌های سلامت می‌پردازد.این فناوری‌ها تاکنون پتانسیل خود را نشان داده‌ وتوانسته اند به بیمه‌گران کمک ‌کنند تا ارزیابی ریسک را بهبود بخشند، مراقبت‌های شخصی‌سازی‌شده ارائه دهند و هزینه‌های بیمارستانی را به‌ویژه با بهره‌گیری از یک استراتژی دیجیتال کاهش دهند. اما این مسیر بدون چالش نیست و در این بین امنیت داده‌ها، انطباق با مقررات جهانی و سوگیری الگوریتمی از جمله چالش‌های مهم مطرح شده‌ میباشند. در ایران نیز با وجود پیشرفت‌های صورت گرفته در این حوزه،همچنان مشکلاتی وجود دارد. چالش‌هایی مانند محدودیت زیرساخت‌های فناوری اطلاعات، ضعف در سیستم‌های ارجاع و دسترسی محدود به اینترنت از جمله موانع اصلی در این موضوع هستند. برای رفع این مشکلات، نیاز به تقویت زیرساخت‌های دیجیتال فعلی، بازبینی چارچوب‌های قانونی موجود و آموزش نیروی انسانی آشنا و توانمند در این حوزه،احساس می‌شود.دستیابی موفقیت در تحول دیجیتال به تعادلی کامل در نظام سلامت وابسته است؛ به این معنا که ترکیب مناسبی از فناوری‌های پیشرفته و توانایی ارائه مراقبت با کیفیت و هزینه مقرون‌به‌صرفه برای همه فراهم شود. در نهایت، این تلاش‌ها می‌تواند به توسعه سیستمی منجر شود که نیازهای تمامی ذینفعان در نظام سلامت را برآورده سازد. 2 The health insurance sector is undergoing a revolution with the help of digital technologies that are creating new ways of improving the quality of services and reducing costs. This study explores how modern solutions such as artificial intelligence, big data, the Internet of Things, and health informatic systems can transform health insurance's future.  These technologies have already demonstrated their potential. They are assisting the insurers in enhancing the risk appraisal, providing individualized care, and minimizing the hospital expenses—especially when integrated with a digital strategy. But the journey is not simple. Data security, global compliance, and algorithmic bias are a few of the significant challenges that have been highlighted. In Iran, the development has been made, but there are still some issues. Challenges include; limited IT infrastructure, poor referral systems, and limited internet access. To address these challenges, there is the need to enhance the current inadequate digital infrastructure, to review the existing legal framework and to train a workforce that will be conversant with these technologies.  The final success of digital transformation will depend on the perfect balance, meaning the right combination of advanced technologies and the ability to provide quality care at an affordable cost for all. Ultimately, these efforts can lead to development of a healthcare system that works for all stakeholders. 149 160 2024/12/232024/06/30 1403/4/10 2024/12/172024/11/30 1403/9/10 محمدمهدی مولائی‎ Mohammad Mahdi Molaei مرکز ملی تحقیقات بیمه سلامت، تهران، ایران molaei.mahdi78@gmail.com منصور فاتحی Mansoor Fatehi کمیته گسترش جهانی، انجمن انفورماتیک تصویربرداری در پزشکی (SIIM)، ویرجینیا، ایالات متحده آمریکا Digital Health Health Insurances Big Data Internet of Things Health Information Systems سلامت دیجیتال بیمه‌های سلامت داده‌های بزرگ اینترنت اشیا سیستم‌های اطلاعات سلامت ## ##

مفهوم‌سازی حکمرانی پژوهش در حوزه سلامت: مرور اجمالی Conceptualizing Research Governance in the Health Field: A Review 1 1 حکمرانی پژوهش چارچوبی حیاتی است که یکپارچگی، کیفیت و انجام اخلاقی پژوهش‌های علمی در رشته‌های مختلف را تضمین می‌کند و شامل مجموعه‌ای از اصول، دستورالعمل‌ها و شیوه‌های کاری طراحی شده برای حفظ استانداردهای بالا در سراسر فرآیند پژوهش، از مفهوم‌سازی تا انتشار نتایج و از نظارت اخلاقی به‌ویژه در مطالعات بالینی انسانی یا حیوانات تا تضمین کیفیت و پاسخگویی یعنی ایجاد خطوط مسئولیت روشن بین پژوهشگران، مؤسسات و نهادهای تأمین مالی و انطباق یعنی تضمین پایبندی به الزامات قانونی و مقرراتی، از جمله حفاظت از داده‌ها و حقوق مالکیت معنوی همچنین شفافیت در ارتباطات، گردش اطلاعات، یافته‌ها و تضاد منافع. حکمرانی پژوهشی مؤثر شامل ذینفعان مختلفی از جمله پژوهشگران و تیم‌های آنها، هیأت‌های ارزیابی یا کمیته‌های اخلاق، موسسات تأمین مالی، نهادهای نظارتی، سردبیران و داوران همتا است. همانطور که عمیق‌تر به این موضوع می‌پردازیم، بررسی خواهیم کرد که چگونه حکمرانی پژوهش، چشم‌انداز پژوهش‌های علمی مدرن و تأثیر آن  بر جامعه را به‌طور کلی شکل می‌دهد. این پژوهش به مرور روایتی 80 مقاله مرتبط با حکمرانی پژوهش پرداخته است. بدین منظور و برای جستجوی کامل و جامع مقالات از پایگاه‌های داده گوگل اسکولار و اسکوپوس استفاده گردید. چندین عبارت برای جستجوی مقالات اصلی و مرتبط استفاده شد که شامل حکمرانی پژوهش، مدل‌های حکمرانی پژوهش، حکمرانی پژوهش در حوزه سلامت و تنظیم‌گری پژوهش بود. این مرور می‌تواند ضمن آشنا نمودن سیاستگذاران و مدیران ارشد و میانی حوزه پژوهش سلامت با اصطلاح حکمرانی و انواع آن، مدل‌های مختلف استفاده شده در این زمینه را تبیین نماید. 2 Research governance is a critical framework that ensures the integrity, quality, and ethical conduct of scientific research in various disciplines and includes a set of principles, guidelines, and working practices designed to maintain high standards throughout the research process, from conceptualization to publication of results and from ethical oversight, especially in human or animal clinical studies, to quality assurance and accountability, i.e., establishing clear lines of responsibility between researchers, institutions, and funding bodies, and compliance, i.e., ensuring adherence to legal and regulatory requirements, including data protection and intellectual property rights, as well as transparency in communications, information flow, findings, and conflicts of interest. This study conducted a narrative review of 80 articles related to research governance. For this purpose, and for a complete and comprehensive search of articles, the Google Scholar and Scopus databases were used. This review can familiarize policymakers and senior and middle managers in the field of health research with the term governance and its types, and explain the different models used in this field. 161 176 2024/12/232024/06/302024/09/23 1403/7/2 2024/12/172024/11/302024/12/4 1403/9/14 جهان‌آرا ممی‌خانی Jahanara Mamikhani گروه اقتصاد سلامت، واحد خمینی‌شهر، دانشگاه آزاد اسلامی، خمینی‌شهر، ایران mamikhani@gmail.com سیدعباس متولیان Seyed Abbas Motevalian گروه اپیدمیولوژی، دانشکده بهداشت، دانشگاه علوم پزشکی ایران، تهران، ایران motevalian@tums.ir حسن حق‌پرست بیدگلی Hassan Haghparast-Bidgoli موسسه بهداشت جهانی، دانشگاه کالج لندن، لندن، انگلستان s.shojaei137023@yahoo.com Governance Research Governance Health Sector Research Governance Models Researcher Independence ﺣﻜﻤﺮﺍﻧﻲ حکمرانی پژوهش حوزه سلامت مدل های حکمرانی پژوهش استقلال پژوهشگران - Godin B. Defining R&D: Is research always systematic? Project on the History and Sociology of S&T Statistics 7: 2001.## - OECD. 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طراحی سیستم اطلاعات مدیریت مالی یکپارچه در سازمان بیمه سلامت ایران با رویکرد سلسله مراتبی Designing an Integrated Financial Management Information System in the Iranian Health Insurance Organization With a Hierarchical Approach 1 1 مقدمه: سیستم اطلاعات مدیریت مالی نقشی حیاتی در تصمیم‌گیری مدیران سازمان‌ها ایفا می‌کند. این سیستم‌، داده‌ها و اطلاعات مربوط به سازمان را جمع‌آوری، سازماندهی و پردازش می‌کند و آن‌ها را به شکلی قابل استفاده در اختیار مدیران قرار می‌دهد. البته این سیستم ها برای اثربخشی مطلوب تاچار به حرکت به سوی یکپارچگی هستند. روش بررسی: در این پژوهش از روش آمیخته (کیفی-کمی) برای گردآوری داده‌ها استفاده شد. در بخش کیفی پس از انجام مصاحبه با 18 خبره و تحلیل داده‌های حاصل از مصاحبه، 19 مؤلفه شناسایی و استخراج شد. سپس، در بخش کمی، برای مدلسازی از روش ترکیبی مدلسازی ساختاری تفسیری فازی بهره گرفته شد. داده‌های این بخش نیز با کمک ماتریس خودتعاملی گردآوری و سپس با کمک نرم‌افزار متلب مورد تحلیل قرار گرفت. یافته‌ها: پس از تحلیل داده‌های حاصل مدلی چهار سطحی حاصل شد که مؤلفه به‌روزرسانی یکپارچه زیرسیستم‌ها تأثیرگذارترین مؤلفه و هشت مؤلفه سرعت گردش اطلاعات مالی، کاهش یا حذف بروکراسی مالی و ادرای، مدیریت هزینه‌ها، مدیریت زمان و اقدام، گزارش‌گیری مالی و مدیریتی پیشرفته، مدیریت رویه‌ها و فرآیندهای حسابداری، مدیریت نقدینگی و مدلسازی مالی تأثیرپذیرترین مؤلفه‌های مدل بودند. نتیجه‌گیری: یکپارچگی سیستم‌های اطلاعات مدیریت مالی در سازمان بیمه سلامت تا حد زیادی به به‌روزرسانی یکپارچه زیرسیستم‌های وابسته نظیر: برنامه حسابرسی کامل، تعاملات مالی و عملیاتی سیستمی، سیستم حسابداری مالی پیشرفته، سیستم پشتیبان تصمیم‌گیری، تضمین امنیت داده‌ها و یکپارچگی داده‌های مالی بستگی دارد. 2 Introduction: The financial management information system plays a vital role in the decision-making of managers of organizations. This system collects, organizes, and processes data and information related to the organization and provides them to managers in a usable form. Of course, these systems are in need of integration for optimal effectiveness. Methods: In this study, a mixed method (qualitative-quantitative) was used to collect data. In the qualitative part, after conducting interviews with 18 experts and analyzing the data obtained from the interviews, 19 components were identified and extracted. Then, in the quantitative part, a mixed method of fuzzy interpretive structural modeling was used for modeling. The data in this part was also collected with the help of a self-interaction matrix and then analyzed with the help of MATLAB software. Results: After analyzing the data, a four-level model was obtained, in which the component of integrated updating of subsystems was the most effective component, and the eight components of speed of financial information circulation, reduction or elimination of financial and administrative bureaucracy, cost management, time and action management, advanced financial and management reporting, management of accounting procedures and processes, liquidity management, and financial modeling were the most effective components of the model. Conclusion: The integration of financial management information systems in the health insurance organization depends largely on the integrated updating of its dependent subsystems. Subsystems such as: complete audit program, financial and operational system interactions, advanced financial accounting system, decision support system, ensuring data security, and financial data integrity. 177 188 2024/12/232024/06/302024/09/232024/08/4 1403/5/14 2024/12/172024/11/302024/12/42024/11/14 1403/8/24 بهروز یاری Behrouz Yari گروه حسابداری، دانشکده علوم انسانی، واحد ایلام، دانشگاه آزاد اسلامی، ایلام، ایران Yari_behroz@yahoo.com فاطمه احمدی Fatemeh Ahmadi گروه حسابداری، دانشکده علوم انسانی، واحد ایلام، دانشگاه آزاد اسلامی، ایلام، ایران fatemehahmady60@gmail.com مجتبی مرادپور Mojtaba Moradpour گروه حسابداری، دانشکده علوم انسانی، واحد ایلام، دانشگاه آزاد اسلامی، ایلام، ایران Moradpour.mo@gmail.com رحمت‌اله محمدی‌پور Rahmatollah Mohammadipour گروه حسابداری، دانشکده علوم انسانی، واحد ایلام، دانشگاه آزاد اسلامی، ایلام، ایران mohammadipourrahmatollah@gmail.com Information System Financial Management Integration سیستم اطلاعات مدیریت مالی یکپارچه‌سازی 1)رضایی، اکبر، علی اکبری، مهناز. روش تحقیق در روان شناسی، تهران: انتشارات دانشگاه پیام نور، 1395;ص 83. ##2)زنجیردار، مجید، ستایش، محمدرضا، بررسی مدل های ارزشیابی سیستم های مالی، فصلنامه علمی پژوهشی دانش سرمایه گذاری، 1401; شماره 37. 144-129.##3-Berzal F, Cubero J. C, Jiménez , A, The design and use of the Miner component-based data mining framework. J Expert Systems with Applications, 2023; 36:192-208.##4-Courtney J.F, Decision making and knowledge management in inquiring organizations: toward a new decision-making paradigm for DSS,J Decision Support Systems, 2023; 31: 17–38.##5-Corbin J., Strauss A., & Strauss A. L, Basics of qualitative research. Sage Publications, Inc,2014.##6-Damart S, Dias L, Mousseau V, Supporting groups in sorting decisions: Methodology and use of a multi-criteria aggregation/disaggregation DSS,J Decision Support Systems,2023; 43: 146–165.##7-Evers M, An analysis of the requirements for DSS on integrated river basin management, J I Management of Environmental Quality, 2020;19: 37-53.##8-Feng, Y, Teng T, Tan A, Modelling situation awareness for Context-aware Decision Support, J Expert Systems with Applications, 2023; 36: 455–463. ##9-Goul M, Corral K, Enterprise model management and next generation decision support, J Decision Support Systems, 2021; 43: 915– 932. ##10-Kwon, O., Kim, K. and Lee, K.C., MM-DSS: Integrating multimedia and decision-making knowledge in decision support systems, Expert Systems with Applications,2023: 32:441–457.##11-Lau, H., Ning, A., Ip, W., & Choy, K, A decision support system to facilitate resources allocation: an OLAP-based neural network approach. Journal of Manufacturing Technology Management, 2022:15(8), 771-778.##12-Mantena, Koen and van Dijk, Hans, Linking Belgian employee financial management system characteristics with performance management system effectiveness: exploring the mediating role of fairness, The International Journal of Financial Resource Management,2023: 24(4):806-825p.##13-Shanab Tib,Reno, Wibisono, Dermawan& Basri, Mursyid Hasan,(2015), Building a Model of Suitable Information systems Performance Management Framework, International Journal of financial Management, Vol. 8, No. 1,627-643.##14-Tekin, V, HRD standards and standardization: where now for financial system development?. Financial Resource Development International, 2020: 20(4), 327-345.##15-Uadiale, Olayinka, Pawan, Adhikari and Pinar, Guven-Uslu, Constraints on the applicability financial performance management systems framework, Journal of Management Studies,2019: 38 (5): 651–674.##1)رضایی، اکبر، علی اکبری، مهناز. روش تحقیق در روان شناسی، تهران: انتشارات دانشگاه پیام نور، 1395;ص 83. ##2)زنجیردار، مجید، ستایش، محمدرضا، بررسی مدل های ارزشیابی سیستم های مالی، فصلنامه علمی پژوهشی دانش سرمایه گذاری، 1401; شماره 37. 144-129.##3-Berzal F, Cubero J. C, Jiménez , A, The design and use of the Miner component-based data mining framework. J Expert Systems with Applications, 2023; 36:192-208.##4-Courtney J.F, Decision making and knowledge management in inquiring organizations: toward a new decision-making paradigm for DSS,J Decision Support Systems, 2023; 31: 17–38.##5-Corbin J., Strauss A., & Strauss A. L, Basics of qualitative research. Sage Publications, Inc,2014.##6-Damart S, Dias L, Mousseau V, Supporting groups in sorting decisions: Methodology and use of a multi-criteria aggregation/disaggregation DSS,J Decision Support Systems,2023; 43: 146–165.##7-Evers M, An analysis of the requirements for DSS on integrated river basin management, J I Management of Environmental Quality, 2020;19: 37-53.##8-Feng, Y, Teng T, Tan A, Modelling situation awareness for Context-aware Decision Support, J Expert Systems with Applications, 2023; 36: 455–463. ##9-Goul M, Corral K, Enterprise model management and next generation decision support, J Decision Support Systems, 2021; 43: 915– 932. ##10-Kwon, O., Kim, K. and Lee, K.C., MM-DSS: Integrating multimedia and decision-making knowledge in decision support systems, Expert Systems with Applications,2023: 32:441–457.##11-Lau, H., Ning, A., Ip, W., & Choy, K, A decision support system to facilitate resources allocation: an OLAP-based neural network approach. Journal of Manufacturing Technology Management, 2022:15(8), 771-778.##12-Mantena, Koen and van Dijk, Hans, Linking Belgian employee financial management system characteristics with performance management system effectiveness: exploring the mediating role of fairness, The International Journal of Financial Resource Management,2023: 24(4):806-825p.##13-Shanab Tib,Reno, Wibisono, Dermawan& Basri, Mursyid Hasan,(2015), Building a Model of Suitable Information systems Performance Management Framework, International Journal of financial Management, Vol. 8, No. 1,627-643.##14-Tekin, V, HRD standards and standardization: where now for financial system development?. Financial Resource Development International, 2020: 20(4), 327-345.##15-Uadiale, Olayinka, Pawan, Adhikari and Pinar, Guven-Uslu, Constraints on the applicability financial performance management systems framework, Journal of Management Studies,2019: 38 (5): 651–674. ##

مطالعه جامعه شناختی کیفیت زندگی زنان مبتلا به سرطان سینه شهر تهران: یک نظریۀ زمینه‌ای Sociological Study on the Quality of Life of Women With Breast Cancer in Tehran: A Grounded Theory 1 1 مقدمه: پژوهش حاضر با هدف واکاوی کیفیت زندگی زنان مبتلا به سرطان سینه شهر تهران انجام شده تا زمینه‌های لازم برای فهم موضوع در بستر شرایط و بافت اجتماعی و اقتصادی را فراهم سازد. روش بررسی: پژوهش حاضر از نوع مطالعات کیفی و روش به‌­کارگرفته شده، نظریه زمینه­ای است. روش نمونه­‌گیری، هدفمند و قضاوتی بود که با تعداد ۱۸ نفر از زنان مبتلا به سرطان پستان مصاحبه عمیق صورت گرفت. نمونه‌­گیری تا زمانی که تمام مقوله‌ها اشباع شدند و دیگر داده تازه و مهمی به­‌دست نیامد تداوم یافت. یافته‌ها: مهم­ترین راهبردهایی که در پژوهش حاضر مورد نتیجه بوده سازگاری با بیماری، آموزش و اطلاع‌رسانی مناسب و مبارزه با بیماری است. در بحث از شرایط زمینه‌­ای مؤلفه‌­های مهمی چون: از دست دادن منزلت اجتماعی، احساس طرد و انزوای اجتماعی و غوطه‌وری در درد و رنج مورد تأکید بوده است. هم­چنین مؤلفه‌­هایی چون فقدان حمایت اجتماعی و اقتصادی، ناکارآمدی و بی‌کیفیتی خدمات درمانی و بیمه‌ای، فقدان سلامت جسمی و روانی به‌­عنوان شرایط علّی مورد توجه هستند. بنابر یافته‌­های پژوهش حاضر دو مقوله اصلی کاهش اعتماد به نفس و خوداتکایی و اختلال در تصویر ذهنی از خود به ­عنوان شرایط مداخله‌گر مطرح شده­‌اند. تکمیل‌­کننده زنجیره مدل پارادایمی پژوهش حاضر مبتنی بر روش نظریه داده بنیاد پیامدها هستند که کیفیت زندگی را در سه بخش عمده کاهش رضایت از زندگی، احساس بی قدرتی اجتماعی و فقدان هدفمندی و معنای زندگی مورد واکاوی قرار گرفته است. نتیجه‌گیری: در اثر بروز زمینه هایی چون فقدان حمایت اجتماعی و اقتصادی، ناکارآمدی و بی کیفیتی خدمات درمانی و بیمه‌ای و فقدان سلامت روانی و اجتماعی زنان مبتلا به سرطان سینه، دچار بی کیفیت شدن زندگی می‌شوند. 2 Introduction: This present study aimed to investigate the quality of life for women with breast cancer in Tehran to provide the necessary background for understanding the subject in the context of social and economic conditions and context. Methods: The current research is a qualitative study and the method used is grounded theory. The sampling method was purposive and judgmental, with in-depth interviews conducted with 18 women with breast cancer. Sampling continued until all categories were saturated and no new and important data were obtained. Results: The most important strategies that were concluded in the present study are adaptation to the disease, appropriate education and information, and fighting the disease. In discussing the underlying conditions, important components such as: loss of social status, feeling of rejection and social isolation, and immersion in pain and suffering have been emphasized. Also, components such as lack of social and economic support, inefficiency and poor quality of medical and insurance services, and lack of physical and mental health are considered as causal conditions. According to the findings of the present study, two main categories of reduced self-confidence and self-reliance and impaired self-image have been proposed as intervening conditions. Completing the paradigmatic model chain of the present study based on the grounded theory method are the consequences, which have analyzed the quality of life in three major parts: reduced life satisfaction, feeling of social powerlessness, and lack of purpose and meaning in life. Conclusion: Women with breast cancer experience poor quality of life due to factors such as lack of social and economic support, inefficiency and poor quality of medical and insurance services, and lack of mental and social health. 189 198 2024/12/232024/06/302024/09/232024/08/42024/05/12 1403/2/23 2024/12/172024/11/302024/12/42024/11/142024/10/2 1403/7/11 افروز خانی Afrooz Khani گروه جامعه‌شناسی، دانشکده علوم اجتماعی، ارتباطات و رسانه، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران afroozkhani@ymail.com محمدباقر تاج‌الدین Mohammadbagher Tajeddin گروه جامعه‌شناسی، دانشکده علوم اجتماعی، ارتباطات و رسانه، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران mb_tajeddin@yahoo.com سعید معدنی Saied Maadani گروه جامعه‌شناسی، دانشکده علوم اجتماعی، ارتباطات و رسانه، دانشگاه آزاد اسلامی واحد تهران مرکزی، تهران، ایران maadani25@yahoo.com Quality of life social exclusion reduction of social satisfaction lack of social dignity social powerlessness. کیفیت زندگی طرد اجتماعی کاهش رضایت اجتماعی فقدان منزلت اجتماعی بی قدرتی اجتماعی. 1.Hornoquist, JO. “The Concept of Quality of Life Scandinavian”, Journal of Social Medicice, 1982,10(2):57-61.##2. Lee, Y. J. “Subjective Quality of Life Measurement in Taipei”, Building and Environment. 2008,43(7):1205-1215.##3. Ryff, C. D. & Singer, B. H. “The Contours of Positive Human Health”. Psychological Inquiry, 1998, 9:1–28.##4. Kamp, I. Van, K. Leidelmeijer, K. Marsman, G. and de Hollander, A. “Urban Environmental Quality and Human Well-Being: Towards A Conceptual Framework and Demarcation of Concepts; A Literature Study”, Landscape and Urban Planning, 2003, 65(1-2):5-18.##5.Ghaffari, Gholamreza & Reza Omidi, Life quality, Index of social development, Tehran, Shirazeh, 2008(Persian).##6. Fraans.c., Development of a scholary, conceptual model of quality of life inquiry for nursing practice, international journal:1996, no 10:151-158.##7.Zahediasl, Mohammad & Javad Farrokhi, the study for relationship between social capital and life quality of household Heads of Tehran, social sciences journal, 2008, 49,1-29(Persian).##8. Poorkiani M, Hazrati M, Abbaszadeh A, Jafari P, Sadeghi M, Dejbakhsh T, MohammadianPanah M. Does a rehabilitation program improve quality of life in breast cancer patients? Payesh; 2018, 9(1):8-61(Persian).##9. Cui Y, Shu X-O, Gao Y, Cai H, Wen W, Ruan Z-X, et al, The long-term impact of medical and socio-demographic factors on the quality of life of breast cancer survivors among Chinese women. Breast cancer research and treatment; 2019, 87(2):47-135.##10.Ghodrati & Et al. Variables that determine health-related quality of life in people with HIV, 2020, 26(2). 118-127(persain).##11. Donald A. What is quality of life? (2018). Availableat: www.jr2.ox.ac.uk.##12.garousi, Saiedeh & Ali Naghavi. Social capital and life quality in Kerman, social welfare journal, 2007, 8(30 %31), 61-83(Persian).##13.Fasihi Harandi, Tayyebeh & et al. Quality of life for women with breast cancer: a qualitative study. Payesh journal, 2012, 11(1), 73-81(persian).##14. Bartoces MG, Severson RK, Rusin BA, Schwartz KL, Ruterbusch JJ, et al (2018). Quality of life and self-esteem of long-term survivors ofinvasive and noninvasive cervical cancer. J Womens Health (Larchmt);18(5):655-61.##15. Parker, sl and others (2019). Cancer statistics, cancer76: 819.##16.Maraashi, Tayyebeh. Investigating the quality of life of women with breast cancer referred to hospitals covered by Shahid Beheshti University of Medical Sciences. Health journal,2019, 6(1),1-8(persian).##17.Mohammadpour A. Qualitative research method, anti-method. Tehran: Sociologists Publications; 1392.##18.Creswell JA. Standards of quality and verification. Qualitative inquiry and research design. Choosing Among Five Traditions. 1998:193-218.##19.Strauss A, Corbin J. Basics of qualitative research. Sage publications; 1990.##20.Giddens A. The third way: The renewal of social democracy. John Wiley & Sons; 2013 May 29.##1.Hornoquist, JO. “The Concept of Quality of Life Scandinavian”, Journal of Social Medicice, 1982,10(2):57-61.##2. Lee, Y. J. “Subjective Quality of Life Measurement in Taipei”, Building and Environment. 2008,43(7):1205-1215.##3. Ryff, C. D. & Singer, B. H. “The Contours of Positive Human Health”. Psychological Inquiry, 1998, 9:1–28.##4. Kamp, I. Van, K. Leidelmeijer, K. Marsman, G. and de Hollander, A. “Urban Environmental Quality and Human Well-Being: Towards A Conceptual Framework and Demarcation of Concepts; A Literature Study”, Landscape and Urban Planning, 2003, 65(1-2):5-18.##5.Ghaffari, Gholamreza & Reza Omidi, Life quality, Index of social development, Tehran, Shirazeh, 2008(Persian).##6. Fraans.c., Development of a scholary, conceptual model of quality of life inquiry for nursing practice, international journal:1996, no 10:151-158.##7.Zahediasl, Mohammad & Javad Farrokhi, the study for relationship between social capital and life quality of household Heads of Tehran, social sciences journal, 2008, 49,1-29(Persian).##8. Poorkiani M, Hazrati M, Abbaszadeh A, Jafari P, Sadeghi M, Dejbakhsh T, MohammadianPanah M. Does a rehabilitation program improve quality of life in breast cancer patients? Payesh; 2018, 9(1):8-61(Persian).##9. Cui Y, Shu X-O, Gao Y, Cai H, Wen W, Ruan Z-X, et al, The long-term impact of medical and socio-demographic factors on the quality of life of breast cancer survivors among Chinese women. Breast cancer research and treatment; 2019, 87(2):47-135.##10.Ghodrati & Et al. Variables that determine health-related quality of life in people with HIV, 2020, 26(2). 118-127(persain).##11. Donald A. What is quality of life? (2018). Availableat: www.jr2.ox.ac.uk.##12.garousi, Saiedeh & Ali Naghavi. Social capital and life quality in Kerman, social welfare journal, 2007, 8(30 %31), 61-83(Persian).##13.Fasihi Harandi, Tayyebeh & et al. Quality of life for women with breast cancer: a qualitative study. Payesh journal, 2012, 11(1), 73-81(persian).##14. Bartoces MG, Severson RK, Rusin BA, Schwartz KL, Ruterbusch JJ, et al (2018). Quality of life and self-esteem of long-term survivors ofinvasive and noninvasive cervical cancer. J Womens Health (Larchmt);18(5):655-61.##15. Parker, sl and others (2019). Cancer statistics, cancer76: 819.##16.Maraashi, Tayyebeh. Investigating the quality of life of women with breast cancer referred to hospitals covered by Shahid Beheshti University of Medical Sciences. Health journal,2019, 6(1),1-8(persian).##17.Mohammadpour A. Qualitative research method, anti-method. Tehran: Sociologists Publications; 1392.##18.Creswell JA. Standards of quality and verification. Qualitative inquiry and research design. Choosing Among Five Traditions. 1998:193-218.##19.Strauss A, Corbin J. Basics of qualitative research. Sage publications; 1990.##20.Giddens A. The third way: The renewal of social democracy. John Wiley & Sons; 2013 May 29. ##

تشخیص زودهنگام اختلال طیف اوتیسم با استفاده از یادگیری ماشین Early Detection of Autism Spectrum Disorder Using Machine Learning 1 1 مقدمه: اوتیسم نوعی اختلال رشدی است که در درجه اول تعاملات و ارتباطات اجتماعی را مختل می‌سازد. این اختلال درمان قطعی ندارد بنابراین تشخیص زودهنگام برای کاهش این اثرات مهم است. هدف از این مطالعه شناسایی افراد مبتلا به اوتیسم براساس اطلاعات ثبت شده از الگوی راه رفتن آن‌ها به وسیله حسگر کینکت است. روش بررسی: در این پژوهش با استفاده از روش یادگیری ماشین مبتنی بر اطلاعات ثبت شده از موقعیت قرارگیری مفاصل هنگام راه رفتن توسط حسگر کینکت، افراد مبتلا به اوتیسم شناسایی شدند. ابتدا، گروه ویژگی‌های آماری از دادگان کینکت استخراج شد که شامل موقعیت مفاصل و زوایای بین آن‌ها است. سپس ویژگی‌های استخراج شده با استفاده از آزمون آماری تحلیل واریانس بررسی و ویژگی‌های بهینه انتخاب شدند. در نهایت با استفاده از طبقه‌بند درخت تصمیم طبقه‌بندی انجام شد. یافته‌ها: در این مقاله با استفاده از طبقه بند درخت تصمیم و ۴۲ ویژگی‌ بهینه انتخاب شده مبتنی بر تحلیل آماری، طبقه‌بندی گروه سالم و بیمار انجام شد و صحت ۸۵ درصد به‌دست آمد. میزان حساسیت و ویژه‌بودن به‌دست آمده در این طبقه‌بندی، به ترتیب ۸۸ و ۸۲ درصد است. نتیجه‌گیری: با توجه به نتایج طبقه‌بندی انجام شده، مشاهده می‌شود که این پژوهش توانست با استفاده از بردار ویژگی با بعد کم که به‌وسیله تحلیل آماری به‌دست آمده بود، به صحت قابل قبولی دست یابد. در این پژوهش نشان داده شد که تنها با داشتن موقعیت قرارگیری چند مفصل می‌توان افراد مبتلا به اوتیسم را از افراد سالم طبقه‌بندی کرد. پیشنهاد می‌گردد در پژوهش‌های آتی با استفاده از این روش میزان بهبودی یا کنترل اوتیسم در افراد را پس از انجام روش‌های درمانی اندازه‌گیری کنند. 2 Introduction: Autism is classified as a developmental disorder and primarily disrupts social interactions and communication. This disorder has no definitive treatment, making early diagnosis crucial for mitigating its effects. The purpose of this study is to identify autistic individuals based on the recorded information of their walking pattern by Kinect sensor. Methods: In this research, the machine learning method was employed to identify autistic individuals based on recorded joint position data during walking, recorded by the Kinect sensor. First, a group of statistical features was extracted from the Kinect data, which included joint positions and the angles between them. Then, the extracted features were evaluated using the statistical test of analysis of variance, and the optimal features were selected. Finally, classification was performed by decision tree classifier. Results: In this research, the classification of healthy and autistic individuals was done by the decision tree classification and 42 optimal features selected based on statistical analysis, and the accuracy of classification was 85%. The sensitivity and specificity obtained in this classification are 88 and 82%, respectively. Conclusion: According to the classification results, this research was able to achieve acceptable accuracy by using the low dimension feature vector obtained by statistical analysis. This research, shows autistic individuals can be classified from healthy people only by having the position of several joints. It is suggested researches in future, using this method for measurement the recovery rate or control autism in patient after performing treatment methods. 199 208 2024/12/232024/06/302024/09/232024/08/42024/05/122024/08/15 1403/5/25 2024/12/172024/11/302024/12/42024/11/142024/10/22024/10/15 1403/7/24 شبنم آخوندی یزدی Shabnam Akhoundi Yazdi مرکز ملی تحقیقات بیمه سلامت، تهران، ایران Sh.akhoondi17@gmail.com امین جانقربانی پوده Amin Janghorbani Poudeh گروه بیوتکنولوژی، پردیس علم و فناوری‌های نوین، دانشگاه سمنان، سمنان، ایران a.janghorbani@semnan.ac.ir علی مالکی Ali Maleki گروه مهندسی پزشکی، دانشکده مهندسی برق و کامپیوتر، دانشگاه سمنان، سمنان، ایران amaleki@semnan.ac.ir Joints Autism Kinect Sensor Statistical Features Decision Tree Classification مفاصل اوتیسم حسگر کینکت ویژگی‌های آماری درخت تصمیم طبقه‌بندی 1. E. G. Cohn, “How Will DSM-5 Affect Autism Diagnosis ? A Systematic Literature Review and Meta-analysis,” 2014, doi: 10.1007/s10803-014-2065-2.##2. Y. Hus and O. Segal, “Challenges surrounding the diagnosis of autism in children,” Neuropsychiatr. Dis. Treat., vol. 17, pp. 3509–3529, 2021, doi: 10.2147/NDT.S282569.##3. A. Abdulrahman and I. Hadi, “Generating 3D Dataset of Gait and Full Body Movement of Children With Autism Spectrum Disorders Collected By Kinect V2 Camera Generating 3D Dataset of Gait and Full Body Movement of Children With Autism Spectrum Disorders Collected By Kinect V2 Camera,” vol. 9, no. September, pp. 3791–3797, 2020.##4. S. Schjølberg et al., “What are we optimizing for in autism screening? Examination of algorithmic changes in the M-CHAT,” Autism Res., vol. 15, no. 2, pp. 296–304, 2022, doi: 10.1002/aur.2643.##5. A. Stathopoulou, D. Loukeris, Z. Karabatzaki, E. Politi, Y. Salapata, and A. Drigas, “Evaluation of Mobile Apps Effectiveness in Children with Autism Social Training via Digital Social Stories,” Int. J. Interact. Mob. Technol., vol. 14, no. 03, p. 4, 2020, doi: 10.3991/ijim.v14i03.10281.##6. K. I. Valijonovna, “GOSPODARKA I INNOWACJE Volume : 22 | 2022 ISSN : 2545-0573 THE CONCEPT OF ENVIRONMENTAL COMPETENCE AND ITS,” pp. 29–35, 2022.##7. G. T. Baranek, L. M. Little, L. D. Parham, K. K. Ausderau, and M. G. Sabatos‐DeVito, “Sensory features in autism spectrum disorders,” Handb. Autism Pervasive Dev. Disord. Fourth Ed., no. c, pp. 378–407, 2014, [Online]. Available: http://www.rheapaul.com/Files/Sensory ASD.pdf.##8. L. Crane, L. M. Lui, J. Davies, and E. Pellicano, “Autistic parents’ views and experiences of talking about autism with their autistic children,” Autism, vol. 25, no. 4, pp. 1161–1167, 2021, doi: 10.1177/1362361320981317.##9. J. R. Steinbrenner et al., “Evidence-based practices for children, youth, and young adults with autism,” Evidence-based Pract. Child. youth, young adults with Autism. Univ. North Carolina Chapel Hill, Frank Porter Graham Child Dev. Institute, Natl. Clear. Autism Evid. Pract. Rev. Team., pp. 1–140, 2020.##10. N. Fauziyah, “Cognition Processes of ASD Students : Recommendations for Mathematics Teaching and Learning Process,” vol. 15, no. 3, pp. 805–830, 2022.##11. P. L. Howard and F. Sedgewick, “‘Anything but the phone!’: Communication mode preferences in the autism community,” Autism, vol. 25, no. 8, pp. 2265–2278, 2021, doi: 10.1177/13623613211014995.##12. A. Learning, “brain sciences What Is Social about Autism ? The Role of,” 2021.##13. J. A. G. Lum et al., “Meta‐Analysis Reveals Gait Anomalies in Autism,” Autism Res., vol. 14, no. 4, pp. 733–747, 2021.##14. M. Calhoun, M. Longworth, and V. L. Chester, “Gait patterns in children with autism,” Clin. Biomech., vol. 26, no. 2, pp. 200–206, 2011, doi: 10.1016/j.clinbiomech.2010.09.013.##15. M. K. Marko, D. Crocetti, T. Hulst, O. Donchin, R. Shadmehr, and S. H. Mostofsky, “Behavioural and neural basis of anomalous motor learning in children with autism,” Brain, vol. 138, no. 3, pp. 784–797, 2015.##16. L. Gong, Y. Liu, L. Yi, J. Fang, Y. 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مقایسه شاخص سلامت عمومی ایران با کشورهای حوزه منا در شاخص رفاه لگاتوم Comparison of Iran's Public Health Index With MENA Region Countries in Legatum Prosperity Index 1 1 مقدمه: در سطح جامعه، یکی از ویژگی‌های مهم رفاه اجتماعی آن است که فرد از احساس سلامت، امنیت و شادمانی بالایی برخوردار باشد. این مطالعه با هدف بررسی وضعیت سلامت ایران در مقایسه با سایر کشورهای حوزه منا در شاخص رفاه لگاتوم انجام شد. روش بررسی: روش پژوهش حاضر توصیفی- مقایسه‌ای بود. جامعه پژوهش این مطالعه کلیه کشورهای حوزه منا شامل منطقه خاورمیانه و شمال آفریقا بود. داده‌های سلامت از منظر شاخص رفاه لگاتوم از سال ۲۰۱۳ تا ۲۰۲۳ کشورهای مورد مطالعه جمع‌آوری گردید. از آزمون آماری پارامتریک تی تک‌نمونه‌ای برای تحلیل داده‌ها و از نرم افزار SPSS نسخه ۲۰ استفاده شد. یافته‌ها: با توجه به نتایج آزمون آماری، یافته‌های مطالعه بیانگر این بود که بر اساس گزارش موسسه لگاتوم، بین امتیاز سلامت ایران و سایر کشورهای حوزه منا تفاوت معنی‌داری مشاهده شد و امتیاز سلامت ایران به‌طور معنی‌داری از میانگین امتیاز کشورهای حوزه منا بالاتر بود. نتیجه‌گیری: ارزیابی شاخص‌های سلامت ایران بر اساس مستندات جهانی، می‌تواند در زمینه سیاسگذاری‌های حوزه سلامت راهگشا باشد. در حوزه سلامت، وضعیت ایران در مقایسه با میانگین سایر کشورهای حوزه منا در وضعیت نسبتاً مطلوب قرار دارد، ولی در سایر حوزه‌ها برای رسیدن به سطح بـالای رفـاه، فاصله زیادی را باید طی کند. 2 Introduction: At the level of society, one of the important features of social prosperity is that a person has a high sense of health, security and happiness. This study was conducted with the aim of investigating the health status of Iran compared to other MENA countries in the Legatum prosperity index. Methods: The present research method was descriptive-comparative. The research population of this study was all the countries of the MENA region, including the Middle East and North Africa region. Health data were collected from the perspective of the Legatum prosperity index from 2013 to 2023 of the studied countries. One-sample parametric statistical test was used for data analysis and SPSS version 20 software. Results: According to the results of the statistical test, the findings of the research indicated that according to the report of the Legatum Institute, a significant difference was observed between the health score of Iran and other MENA countries, and Iran's health score was significantly higher than the average score of the MENA countries. Conclusion: The evaluation of Iran's health indicators based on international documents can be helpful in the field of health policies. In the field of health, Iran's situation is relatively favorable compared to the average of other MENA countries, but in other fields, it has to go a long way to reach a high level of well-being. 209 216 2024/12/232024/06/302024/09/232024/08/42024/05/122024/08/152024/09/1 1403/6/11 2024/12/172024/11/302024/12/42024/11/142024/10/22024/10/152024/12/1 1403/9/11 معصومه فغفوری‌آذر Masoumeh Faghfouriazar گروه تربیت بدنی، دانشکده علوم انسانی، واحد گرمسار، دانشگاه آزاد اسلامی، گرمسار، ایران m.faghfouriazar@yahoo.com Health Legatum Prosperity Index MENA Region سلامت شاخص رفاه لگاتوم حوزه منا 1. Azizi F, Hatami H, Janghorbani M. Epidemiology and control of common diseases in Iran. Tehran: Eshtiagh Publications. 2000. [Persian]##2. Mohammadi Zeidi I, Pakpour Hajiagha A, Mohammadi Zeidi B. 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کلاس‌بندی و نرخ‌گذاری بیمه‌شدگان درمان با استفاده از رویکرد ماتریس ریسک Classification and Rating of Health Insureds Using Risk Matrix Approach 1 1 مقدمه: یکی از مهم‌ترین ارکان بهبود خدمات بهداشت و درمان، وضعیت بیمه‌های درمان تکمیلی است که باعث افزایش دسترسی مردم به مراقبت‌های بهداشتی می‌شود. ارزیابی دقیق و علمی ریسک صدور بیمه‌نامه درمان یکی از حساس‌ترین و مهم‌ترین مراحل ارزیابی ریسک است و انجام آن باعث شناسایی مشتریان پرریسک و تعیین نرخ بیمه سلامت، متناسب با ریسک مشتریان می‌شود؛ لذا مطالعه حاضر با هدف کلاس‌بندی و نرخ‌گذاری بیمه‌شدگان درمان با استفاده از رویکرد ماتریس ریسک انجام گرفت. روش بررسی: برای ارزیابی ریسک بیمه‌شده‌ها، یک مدل دومرحله‌ای همراه با رویکرد ماتریس ارزیابی ریسک ارائه شده است که با استفاده از آن بتوان بیمه‌شده‌ها را در کلاس‌های مختلف ریسک طبقه‌بندی کرد. برای این منظور ابتدا در گام اول احتمال ادعای خسارت را با استفاده از رگرسیون لجستیک براساس ریسک‌فاکتورهای سن، جنسیت و موقعیت جغرافیایی پیش‌بینی کرده و در گام بعد شدت خسارت با استفاده از رگرسیون چندکی پیش‌‌‌‌ بینی شد. یافته‌ها: در این مطالعه، مدل ارزیابی ریسک با رویکرد ماتریس ریسک ارائه شد که با به‌کارگیری آن می‌توان برای بیمه‌نامه‌ها سه کلاس ریسک بحرانی ( ) متوسط ( ) و قابل قبول ( ) ارائه کرد. نتیجه‌گیری: با استفاده از نتایج رویکرد ماتریس ریسک می‌توان برای بیمه‌نامه‌ها حق بیمه‌ای متناسب با کلاس ریسکی آنها تعیین نمود. این موضوع می‌تواند به افزایش سطح رضایتمندی مردم، حرکت کردن در مسیر عدالت، رسیدن به حق‌بیمه منصفانه، گسترش یافتن فضای امنیت و نگاه علمی کردن به صنعت بیمه کشور کمک کند. 2 Introduction: One of the most important pillars of improving healthcare services is the state of supplementary medical insurances, which increase people's access to healthcare. The accurate and scientific assessment of the risks of issuing a medical insurance policy is one of the most sensitive and important stages of risk assessment, and performing it leads to the identification of high-risk customers and the determination of the health insurance policy rate, in accordance with the customers' risk. Therefore, the present study aimed to classify and rate health insurance beneficiaries using a risk matrix approach. Methods: In order to assess the risk of insured persons, a two-step model has been presented along with the risk assessment matrix approach, which can be used to classify the insureds into different risk classes. For this purpose, in the first step, the probability of claiming damages using logistic regression based on age, gender and geographical location risk factors are predicted and in the next step the severity of the damage is predicted using quantile regression. Results: Finally a risk assessment model is presented with a risk matrix approach, which presents three risk class; critical (R_1), moderate (R_2) and acceptable (R_3) risk class. Conclusion: Using the results of the risk matrix approach, insurance premiums have been determined for the insurance policies according to their risk class. This can help increase people's satisfaction, move towards justice, achieve fair insurance premiums, expand the security environment, and take a scientific look at the country's insurance industry. 217 226 2024/12/232024/06/302024/09/232024/08/42024/05/122024/08/152024/09/12024/09/3 1403/6/13 2024/12/172024/11/302024/12/42024/11/142024/10/22024/10/152024/12/12024/11/19 1403/8/29 مجتبی عابد Mojtaba Abed گروه بیم‌سنجی، دانشکده علوم ریاضی، دانشگاه شهید بهشتی، تهران، ایران mojtabaabed1988@gmail.com امیرتیمور پاینده نجف‌آبادی Amirteymor Payandeh Najafabadi گروه بیم‌سنجی، دانشکده علوم ریاضی، دانشگاه شهید بهشتی، تهران، ایران amirtpayandeh@gmail.com Classification Insurance Health Risk Regression کلاس‌بندی بیمه سلامت ریسک رگرسیون 1 Niakan L, Nooredini SS. Loss management solutions for complementary health insurance, Research Group of Personal Insurance, Insurance Research Center. 2015. No: 47.##2 Zweifel P, Manning WG. Moral hazard and consumer incentives in health care. Handbook of health economics. 1: Elsevier; 2000; 409-59.##3 Popescu GH. Economic aspects influencing the rising costs of health care in the United States. American Journal of Medical Research. 2014;1(1):47-52.##4 Lorenzoni L, Belloni A, Sassi F. Health-care expenditure and health policy in the USA versus other high-spending OECD countries. The Lancet. 2014;384(9937):83-92.##5 Mazloomi N, Haghighi Kaffash M, Khashei V, Nateghi AA. Strategic Management Risks Model in the Iranian Insurance Industry. Commercial Strategies. 2020;15(12):125-42.##6 Riyahifar M. Designing a health insurance risk management model for Iran. Insurance Research Journal. 2007;21(4):119-24.##7 Eling M, Schmeiser H, Schmit JT. The Solvency II process: Overview and critical analysis. Risk management and insurance review. 2007; 10(1), 69-85.##8 Asmussen S, Rubinstein RY. Sensitivity analysis of insurance risk models via simulation. Management Science. 1999; 45(8): 1125-1141.##9 Central Insurance of the Islamic Republic of Iran. Regulation No. 94 of the Supreme Insurance Council: ‘Regulations for determining insurance premiums for various insurance fields’. Available at: https://centinsur.ir##10 Amsc N, SAFT AA. Department of defense standard practice system safety. 2012.##11 Anthony (Tony) Cox Jr L. What's wrong with risk matrices? Risk Analysis: An International Journal. 2008;28(2): 497-512.##12 Dehnavi Z. An introduction to risk-based supervision in insurance companies. Tazehaye Jahane Bimeh. 2004; 80: 42-56.##13 Majed V, Nooredini SS. Risk-based supervision in the insurance industry. International Insurance and Development Conference. 2013.##14 Yazdan Panah A, Khalilzadeh P. Risk-Based Supervision in the Insurance Industry: A Conceptual Framework. International Insurance and Development Conference. 2013.##15 Riahifar M. Designing a risk management model for health insurance for Iran. Iranian Journal of Insurance Research. 2016;21(4):119-155.##16 Ghafouri M. Study of factors affecting the satisfaction of health insurance policyholders of Dana Insurance Company. Iranian Journal of Insurance Research. 2004; 75: 136-151.##17 Moghaddisi H, Hosseini AS, Asadi F, Esmaeili M. Problems of the Iranian health insurance system and the necessity of implementing a reform approach. Health Management. 2011;14(44):71-80. ##18 Bodenheimer T, Fernandez A. High and rising health care costs. Part 4: can costs be controlled while preserving quality? Annals of internal medicine. 2005;143(1):26-31.##19 Ghasemi M, Banisi P, Yadegari F. Presenting a Model in the Field of Risk Management Training in the Insurance Industry. Iranian journal of educational sociology. 2017;1(5):37-50.##20 Dehghani A, Shahryar B. A Proposed Pattern of Enterprise Risk Management in Insurance Companies. 2018.##21 Campbell PC, Korie PC, Nnaji FC. Risk management assessment of health maintenance organisations participating in the National Health Insurance Scheme. Nigerian medical journal: journal of the Nigeria Medical Association. 2014; 55(5):399.##22 Mazloomi N, Haghighi Kaffash M, Khashei V, Nateghi AA. Strategic Management Risks Model in the Iranian Insurance Industry. Commercial Strategies. 2020;15(12):125-42.##23 Kamali Khaneghah R. The effect of integrating risk management on strategies and corporate governance (a case study in Pasargad insurance companies). Shabak. 2019; 5.##24 Mohammadpour M, Asaadi A, Davoodi A. Identifying and ranking the factors affecting the risks of complementary health insurance using network analysis technique (case study of insurance companies in Khorasan Razavi province). 2nd International Conference on Management & Economics Tehran, Iran. 2016.##25 Royalty AB, Hagens J. The effect of premiums on the decision to participate in health insurance and other fringe benefits offered by the employer: evidence from a real-world experiment. Journal of Health Economics. 2005; 24(1), 95-112. ##26 Ahmadzadeh A. Analysis of rate-breaking in the insurance industry. Research Group of Personal Insurance, Insurance Research Center. 2021; No: 128.##27 Ghanbarzadeh M, Abbasi M, Hamzeh A, Hozarmoghadam N. Pathology of group health insurance rating. Journal of Strategic Management Studies. 2024; 58(15), 65-83.##28 Dionne G, Rothschild CG. Risk Classification and Health Insurance. Encyclopedia of Health Economics. 2014; 3: 272-280.##1 Niakan L, Nooredini SS. Loss management solutions for complementary health insurance, Research Group of Personal Insurance, Insurance Research Center. 2015. No: 47.##2 Zweifel P, Manning WG. Moral hazard and consumer incentives in health care. Handbook of health economics. 1: Elsevier; 2000; 409-59.##3 Popescu GH. Economic aspects influencing the rising costs of health care in the United States. American Journal of Medical Research. 2014;1(1):47-52.##4 Lorenzoni L, Belloni A, Sassi F. Health-care expenditure and health policy in the USA versus other high-spending OECD countries. The Lancet. 2014;384(9937):83-92.##5 Mazloomi N, Haghighi Kaffash M, Khashei V, Nateghi AA. Strategic Management Risks Model in the Iranian Insurance Industry. Commercial Strategies. 2020;15(12):125-42.##6 Riyahifar M. Designing a health insurance risk management model for Iran. Insurance Research Journal. 2007;21(4):119-24.##7 Eling M, Schmeiser H, Schmit JT. The Solvency II process: Overview and critical analysis. Risk management and insurance review. 2007; 10(1), 69-85.##8 Asmussen S, Rubinstein RY. Sensitivity analysis of insurance risk models via simulation. Management Science. 1999; 45(8): 1125-1141.##9 Central Insurance of the Islamic Republic of Iran. Regulation No. 94 of the Supreme Insurance Council: ‘Regulations for determining insurance premiums for various insurance fields’. Available at: https://centinsur.ir##10 Amsc N, SAFT AA. Department of defense standard practice system safety. 2012.##11 Anthony (Tony) Cox Jr L. What's wrong with risk matrices? Risk Analysis: An International Journal. 2008;28(2): 497-512.##12 Dehnavi Z. An introduction to risk-based supervision in insurance companies. Tazehaye Jahane Bimeh. 2004; 80: 42-56.##13 Majed V, Nooredini SS. Risk-based supervision in the insurance industry. International Insurance and Development Conference. 2013.##14 Yazdan Panah A, Khalilzadeh P. Risk-Based Supervision in the Insurance Industry: A Conceptual Framework. International Insurance and Development Conference. 2013.##15 Riahifar M. Designing a risk management model for health insurance for Iran. Iranian Journal of Insurance Research. 2016;21(4):119-155.##16 Ghafouri M. Study of factors affecting the satisfaction of health insurance policyholders of Dana Insurance Company. Iranian Journal of Insurance Research. 2004; 75: 136-151.##17 Moghaddisi H, Hosseini AS, Asadi F, Esmaeili M. Problems of the Iranian health insurance system and the necessity of implementing a reform approach. Health Management. 2011;14(44):71-80. ##18 Bodenheimer T, Fernandez A. High and rising health care costs. Part 4: can costs be controlled while preserving quality? Annals of internal medicine. 2005;143(1):26-31.##19 Ghasemi M, Banisi P, Yadegari F. Presenting a Model in the Field of Risk Management Training in the Insurance Industry. Iranian journal of educational sociology. 2017;1(5):37-50.##20 Dehghani A, Shahryar B. A Proposed Pattern of Enterprise Risk Management in Insurance Companies. 2018.##21 Campbell PC, Korie PC, Nnaji FC. Risk management assessment of health maintenance organisations participating in the National Health Insurance Scheme. Nigerian medical journal: journal of the Nigeria Medical Association. 2014; 55(5):399.##22 Mazloomi N, Haghighi Kaffash M, Khashei V, Nateghi AA. Strategic Management Risks Model in the Iranian Insurance Industry. Commercial Strategies. 2020;15(12):125-42.##23 Kamali Khaneghah R. The effect of integrating risk management on strategies and corporate governance (a case study in Pasargad insurance companies). Shabak. 2019; 5.##24 Mohammadpour M, Asaadi A, Davoodi A. Identifying and ranking the factors affecting the risks of complementary health insurance using network analysis technique (case study of insurance companies in Khorasan Razavi province). 2nd International Conference on Management & Economics Tehran, Iran. 2016.##25 Royalty AB, Hagens J. The effect of premiums on the decision to participate in health insurance and other fringe benefits offered by the employer: evidence from a real-world experiment. Journal of Health Economics. 2005; 24(1), 95-112. ##26 Ahmadzadeh A. Analysis of rate-breaking in the insurance industry. Research Group of Personal Insurance, Insurance Research Center. 2021; No: 128.##27 Ghanbarzadeh M, Abbasi M, Hamzeh A, Hozarmoghadam N. Pathology of group health insurance rating. Journal of Strategic Management Studies. 2024; 58(15), 65-83.##28 Dionne G, Rothschild CG. Risk Classification and Health Insurance. Encyclopedia of Health Economics. 2014; 3: 272-280. ##