ارزیابی عملکرد واحدهای استانی سازمان تامین اجتماعی در بخش درمان غیرمستقیم در سال 1396 با استفاده از روش تاپسیس
محورهای موضوعی : -مدارک پزشکیعباس جهانگیری 1 , محمد جهانگیری 2
1 - باشگاه پژوهشگران جوان و نخبگان، واحد خمین، دانشگاه آزاد اسلامی، خمین، ایران
2 - کارشناس ارشد مهندسی بهداشت حرفه‌ای، سازمان تامین اجتماعی، مدیریت درمان استان مرکزی، بیمارستان امام خمینی (ره)، اراک، ایران
کلید واژه: درمان غیرمستقیم, ارزیابی عملکرد, سازمان تامین اجتماعی, تاپسیس, تصمیم‌گیری چند شاخصه,
چکیده مقاله :
مقدمه:سازمان تامین اجتماعی به عنوان یک سازمان ارائه دهنده خدمات سلامت، بخشی از مراقبت‌های بهداشتی و درمانی را به صورت غیرمستقیم از طریق عقد قرارداد با مراکز خصوصی و دولتی ارائه می‌دهد. هدف از این مقاله ارزیابی عملکرد و رتبه‌بندی واحدهای استانی این سازمان در بخش درمان غیرمستقیم بود. روشپژوهش:در این مطالعه مقطعی- توصیفی عملکرد درمان غیرمستقیم آن سازمان در سراسر کشور با استفاده از روش تاپسیس با درنظرگیری6 شاخص مهم مورد سنجش قرار گرفته شد. بدین منظور هر استان به عنوان یک گزینه لحاظ شد و نیز داده‌های مورد نیاز از سالنامه آماری سال 1396 به دست آمد. محاسبات لازم و رتبه‌بندی استان‌ها به کمک نرم‌افزار Excel 2010 انجام شد. یافته‌ها: نسبت تعداد کل مراکز درمانی طرف قرارداد به جمعیت تحت پوشش درمان هر استان و نسبت تعداد کل پزشکان طرف قرارداد به جمعیت تحت پوشش درمان هر استان شاخص‌های با بیشترین وزن شناسایی شدند. بیشترین و کمترین نمره عملکردی به ترتیب 1 و 6-10×4 محاسبه شد. نتیجه‌گیری:گرچه سازمان تامین اجتماعی از شیوه درمان غیر مستقیم در تمامی‌استان‌های کشور به عنوان یک راهبرد جهت افزایش دسترسی بیمه‌شدگان به منابع درمانی استفاده نموده است اما عملکردی یکسان در همه استان‌ها نداشته لذا پیشنهاد می‌شود قراردادهای خرید خدمات درمانی را با بیمارستان‌ها، کلینیک‌ها، پلی کلینیک‌ها، دی کلینیک‌ها، مراکز بهداشتی و درمانی، پزشکان عمومی، متخصص و دندانپزشکان بخش دولتی، خصوصی، نظامی‌و غیره مخصوصاً در استان‌هایی که عملکرد ضعیفی داشته اند افزایش دهد.
Introduction: Social Security Organization as a health service provider provides some parts of healthcare services in indirect sector through contracting with private and public centers. The purpose of this paper was to performance assessment and ranking provincial units of this organization in indirect treatment sector. Methods: In this cross-sectional descriptive study, the performance of this organization's indirect treatment across the country was assessed using the TOPSIS method by considering six important attributes. For this purpose, each province was considered as an alternative also the required data from the 2017 statistical yearbook was obtained. Calculations and ranking of provinces were done using Excel 2010 software. Results: The ratio of the total number of contracted healthcare centers to the population covered by the treatment of each province and proportion of the total number of doctors contracted to the population covered by the treatment of each province attributes with the highest weight were identified. The highest and lowest performance scores were calculated 1 and 6×10-4 respectively. Conclusion: Although the social security organization has used indirect treatment in all provinces of the country as a strategy to increase the access of insured persons to medical resources, it did not have the same performance in all provinces. Therefore, it is recommended to increase the purchase contracts of health services with hospitals, clinics, polyclinics, day clinics, healthcare centers, general practitioners, specialists and dentists of public sector, private, military, etc., especially in provinces with poor performance.
1- Educational booklet A brief introduction to the Social Security Organization [Internet], 2013. Available from: http://www.estekhtam.com/wp-content/uploads/2015/12/tamin.readme931.pdf. [In Persian]
2- Jahangiri A. Ranking Different Regions of Iran in Terms of Level of Health Services Outsourcing and Indirect Care Activities of the Social Security Organization in 2016 by Using Multiple Attribute Decision Making. Health Information Management, 2018; 15(1): 34-9. [In Persian]
3- Ghoddousinejad J, Janati A, Arab-Zozani M, Imani A. Strategic Purchasing in Health System of Iran: A Review Study. Depiction of Health, 2018; 8(4): 260-6. [In Persian]
4- Rao KD, Paina L, Ingabire M-G, Shroff ZC. Contracting non-state providers for universal health coverage: learnings from Africa, Asia, and Eastern Europe. International journal for equity in health, 2018; 17(1): 127.
5- Raji A. The purchase of medical services will be replaced with the development of social Security therapeutic centers: Islamic Republic News Agency; 2016 [26-12-2017]. Available from: http://www.irna.ir/fa/News/82334420. [In Persian]
6- Azad E, Ketabi S, Soltani I, Bagherzade M. Analysis of Efficiency and Resource Allocation at Different Wards in Shariati Hospital, Isfahan, Iran, Using Data Envelopment Analysis. Health Information Management, 2012; 8(7): 938-47. [In Persian]
7- Jahangiri A. Application of Data Envelopment Analysis Technique in Iranian hospitals (A Systematic Review). Hospital, 2016; 15(3): 103-24. [In Persian]
8- Najafi B, Behesti Dehkordi A, Emami Meibodi A. The productivity of general hospitals of Ardebil Province (1999-2006). The Journal of Qazvin University of Medical Sciences, 2011; 14(4): 64-70. [In Persian]
9- Jahangiri A, Jahangiri M. Performance Evaluation of Hospital by Using Dynamic Multiple Attribute Decision Making (DMADM): A Case Study in Imam Khomeini Hospital Affiliated to Social Security Organization in Arak. Journal of healthcare management., 2017; 8(1): 91-102. [In Persian]
10- Goudarzi R, Mehrolhassani M, Dehnavieh R, Darvishi A. Performance Assessment of Provincial Units of Social Security Organization in Indirect Health Services Sector using DEA Method in 2014. Iranian Journal of Epidemiology, 2017; 12(5): 65-73. [In Persian]
11- Social Security Notification Base. Statistical reports of the Social Security Organization 2018 [cited 2018-12-8]. Available from: https://www.tamin.ir/file/file/198028. [In Persian]
12- Jahangiri A, Keramati MA. The importance of Recruitment of qualified manpower and Its role in promoting efficiency: A case study. Hospital, 2014; 13(3): 77-88. [In Persian]
13- Jahangiri A, Jahangiri M, Mosali A. Ranking Provinces of Iran in Terms of Existence of Healthcare Resources and Level of People's Access to Them by Using Multiple Attribute Decision Making. Journal of healthcare management., 2017; 8(3): 73-84. [In Persian]
14- Asgarpour MJ. Multiple Criteria Decision Making. 9th edition. Tehran: University of Tehran; 2011: 399. [In Persian]
15- Lee H-C, Chang C-T. Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews, 2018; 92: 883-96.
16- dos Santos BM, Godoy LP, Campos LMS. Performance evaluation of green suppliers using entropy-TOPSIS-F. Journal of Cleaner Production, 2019; 207: 498-509.
17- Tsaur R-C. Decision risk analysis for an interval TOPSIS method. Applied Mathematics and Computation, 2011; 218(8): 4295-304.
18- Mao N, Song M, Deng S. Application of TOPSIS method in evaluating the effects of supply vane angle of a task/ambient air conditioning system on energy utilization and thermal comfort. Applied Energy., 2016; 180: 536-45.
19- Chou Y-C, Yen H-Y, Dang VT, Sun C-C. Assessing the Human Resource in Science and Technology for Asian Countries: Application of Fuzzy AHP and Fuzzy TOPSIS. Symmetry, 2019; 11(2): 251.
20- Roszkowska E. Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/University of Economics in Katowice, 2011; 6: 200-30.
21- Amaryar Software group. Comparison between AHP and Topsis, what is the difference and likeness between the AHP and Topsis techniques? 2017 [cited 2019-1-4]. Available from: http://amaryar.com/miniurl0064718. [In Persian]
22- Shukla A, Agarwal P, Rana RS, Purohit R. Applications of TOPSIS Algorithm on various Manufacturing Processes: A Review. Materials Today: Proceedings, 2017; 4(4): 5320-9.
23- Loevinsohn B, Harding A. Buying results? Contracting for health service delivery in developing countries. The Lancet, 2005; 366(9486): 676-81.
24- Liu X, Hotchkiss DR, Bose S. The effectiveness of contracting-out primary health care services in developing countries: a review of the evidence. Health policy and planning, 2007; 23(1): 1-13.
25- Odendaal WA, Ward K, Uneke J, Uro‐Chukwu H, Chitama D, Balakrishna Y, et al. Contracting out to improve the use of clinical health services and health outcomes in low‐and middle‐income countries. Cochrane Database of Systematic Reviews, 2018; (4).
26- Nael Befroei E, Samiei K, Rostami Khamene M. Evaluation Of Justice Distribution In Social Security Organization Facilities And Its Insured Needs. journal of medical council of islamic republic of iran, 2013; 31(1): 24-33. [In Persian]
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1- Educational booklet A brief introduction to the Social Security Organization [Internet], 2013. Available from: http://www.estekhtam.com/wp-content/uploads/2015/12/tamin.readme931.pdf. [In Persian]
2- Jahangiri A. Ranking Different Regions of Iran in Terms of Level of Health Services Outsourcing and Indirect Care Activities of the Social Security Organization in 2016 by Using Multiple Attribute Decision Making. Health Information Management, 2018; 15(1): 34-9. [In Persian]
3- Ghoddousinejad J, Janati A, Arab-Zozani M, Imani A. Strategic Purchasing in Health System of Iran: A Review Study. Depiction of Health, 2018; 8(4): 260-6. [In Persian]
4- Rao KD, Paina L, Ingabire M-G, Shroff ZC. Contracting non-state providers for universal health coverage: learnings from Africa, Asia, and Eastern Europe. International journal for equity in health, 2018; 17(1): 127.
5- Raji A. The purchase of medical services will be replaced with the development of social Security therapeutic centers: Islamic Republic News Agency; 2016 [26-12-2017]. Available from: http://www.irna.ir/fa/News/82334420. [In Persian]
6- Azad E, Ketabi S, Soltani I, Bagherzade M. Analysis of Efficiency and Resource Allocation at Different Wards in Shariati Hospital, Isfahan, Iran, Using Data Envelopment Analysis. Health Information Management, 2012; 8(7): 938-47. [In Persian]
7- Jahangiri A. Application of Data Envelopment Analysis Technique in Iranian hospitals (A Systematic Review). Hospital, 2016; 15(3): 103-24. [In Persian]
8- Najafi B, Behesti Dehkordi A, Emami Meibodi A. The productivity of general hospitals of Ardebil Province (1999-2006). The Journal of Qazvin University of Medical Sciences, 2011; 14(4): 64-70. [In Persian]
9- Jahangiri A, Jahangiri M. Performance Evaluation of Hospital by Using Dynamic Multiple Attribute Decision Making (DMADM): A Case Study in Imam Khomeini Hospital Affiliated to Social Security Organization in Arak. Journal of healthcare management., 2017; 8(1): 91-102. [In Persian]
10- Goudarzi R, Mehrolhassani M, Dehnavieh R, Darvishi A. Performance Assessment of Provincial Units of Social Security Organization in Indirect Health Services Sector using DEA Method in 2014. Iranian Journal of Epidemiology, 2017; 12(5): 65-73. [In Persian]
11- Social Security Notification Base. Statistical reports of the Social Security Organization 2018 [cited 2018-12-8]. Available from: https://www.tamin.ir/file/file/198028. [In Persian]
12- Jahangiri A, Keramati MA. The importance of Recruitment of qualified manpower and Its role in promoting efficiency: A case study. Hospital, 2014; 13(3): 77-88. [In Persian]
13- Jahangiri A, Jahangiri M, Mosali A. Ranking Provinces of Iran in Terms of Existence of Healthcare Resources and Level of People's Access to Them by Using Multiple Attribute Decision Making. Journal of healthcare management., 2017; 8(3): 73-84. [In Persian]
14- Asgarpour MJ. Multiple Criteria Decision Making. 9th edition. Tehran: University of Tehran; 2011: 399. [In Persian]
15- Lee H-C, Chang C-T. Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews, 2018; 92: 883-96.
16- dos Santos BM, Godoy LP, Campos LMS. Performance evaluation of green suppliers using entropy-TOPSIS-F. Journal of Cleaner Production, 2019; 207: 498-509.
17- Tsaur R-C. Decision risk analysis for an interval TOPSIS method. Applied Mathematics and Computation, 2011; 218(8): 4295-304.
18- Mao N, Song M, Deng S. Application of TOPSIS method in evaluating the effects of supply vane angle of a task/ambient air conditioning system on energy utilization and thermal comfort. Applied Energy., 2016; 180: 536-45.
19- Chou Y-C, Yen H-Y, Dang VT, Sun C-C. Assessing the Human Resource in Science and Technology for Asian Countries: Application of Fuzzy AHP and Fuzzy TOPSIS. Symmetry, 2019; 11(2): 251.
20- Roszkowska E. Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/University of Economics in Katowice, 2011; 6: 200-30.
21- Amaryar Software group. Comparison between AHP and Topsis, what is the difference and likeness between the AHP and Topsis techniques? 2017 [cited 2019-1-4]. Available from: http://amaryar.com/miniurl0064718. [In Persian]
22- Shukla A, Agarwal P, Rana RS, Purohit R. Applications of TOPSIS Algorithm on various Manufacturing Processes: A Review. Materials Today: Proceedings, 2017; 4(4): 5320-9.
23- Loevinsohn B, Harding A. Buying results? Contracting for health service delivery in developing countries. The Lancet, 2005; 366(9486): 676-81.
24- Liu X, Hotchkiss DR, Bose S. The effectiveness of contracting-out primary health care services in developing countries: a review of the evidence. Health policy and planning, 2007; 23(1): 1-13.
25- Odendaal WA, Ward K, Uneke J, Uro‐Chukwu H, Chitama D, Balakrishna Y, et al. Contracting out to improve the use of clinical health services and health outcomes in low‐and middle‐income countries. Cochrane Database of Systematic Reviews, 2018; (4).
26- Nael Befroei E, Samiei K, Rostami Khamene M. Evaluation Of Justice Distribution In Social Security Organization Facilities And Its Insured Needs. journal of medical council of islamic republic of iran, 2013; 31(1): 24-33. [In Persian]