کارایی سیستم های سلامت کشورها در مقابله با کووید-19، با استفاده از تحلیل پوششی داده های پنجره ای، شاخص بهره وری مالم کوئیست و تحلیل پوششی داده ای با متغیرهای ورودی کنترل ناپذیر (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
هدف این مقاله، ارزیابی واکنش کشورها در مقابله با کووید-19 برای 16 کشور، که با در نظر گرفتن تفاوت ها در ویژگی های مختلف جمعیتی، فرهنگی و جغرافیایی انتخاب شده اند، در سه دوره متوالی از دی ماه سال 1398 تا آبان سال 1401 است. برای این ارزیابی، از مدل تحلیل پنجره ای، شاخص بهره وری مالم کوئیست و تحلیل پوششی داده ای متغیرهای ورودی کنترل نشدنی در سه دوره 345 روزه، استفاده خواهد شد. مدل تحلیل پنجره ای و تحلیل پوششی داده ای متغیرهای ورودی کنترل نشدنی برای مقایسه کارایی کشورها در چند دوره مختلف استفاده می شود و روش شاخص بهره وری مالم کوئیست، امتیازاتی را برای پیشرفت عملکرد کشورها در طی دوره های متوالی، محاسبه می کند. امتیازات عملکردی محاسبه شده با مدل تحلیل پنجره ای، نشان می دهد در واکنش کشورها تفاوت وجود داشته است و بر اساس نتایج این روش، چین بیشترین و ایتالیا بدترین کارایی را در طول سه دوره داشته اند. نتایج روش شاخص بهره وری مالم کوئیست برای مقایسه پیشرفت عملکردها نیز نشان داد که کشورها، کارایی ها و پیشرفت های متفاوتی دارند. بر اساس نتایج این روش، مالزی بیشترین و سنگاپور کمترین پیشرفت را در طول سه دوره داشته اند. چین با وجود امتیاز بالای کارایی از مدل تحلیل پنجره ای، از شاخص مالم کوئیست و مدل متغیرهای کنترل نشدنی، امتیاز خوبی نگرفته است که این رشد کم و حتی پسرفت این کشور را در طی سه دوره بررسی شده نشان می دهد و مشخص می کند که ایتالیا پیشرفت کرده است، اما با توجه به نتایج تحلیل پنجره ای، این رشد برای کاراکردن عملکرد این کشور، کافی نبوده است. براساس مدل متغیرهای کنترل نشدنی، مصر بهترین عملکرد را داشته است. اگرچه این مدل میان بیشتر کشورها، تمایزی قائل نمی شود.Evaluating the Health Systems Efficiency of Countries Infected by COVID-19 Using Window Data Envelopment Analysis, Malmquist Productivity Index, and Data Envelopment Analysis with Non-Controllable Input Variables
Purpose: This paper aims to evaluate the response of different countries against Covid-19 for three consecutive periods from January 2020 to October 2022. 16 countries have been chosen based on their differences in various demographic, cultural, and geographical characteristics.
Design/methodology/approach: Window Data Envelopment Analysis (DEA) model, Malmquist Productivity Index and DEA with non-controllable input variables have been used over three periods of 345 days to evaluate the efficiency of health systems of the countries. By the Window DEA and DEA with non-controllable input variables, the efficiency of the countries in several different periods has been compared. Also, the scores for the progress of countries' performance during successive periods have been computed by the Malmquist Productivity Index.
Findings: The performance scores calculated with the window DEA indicated that there is a difference in the countries' responses. Based on the obtained results, China had the most efficiency and Italy had the worst efficiency during the three periods. Based on the model of uncontrollable variables, Egypt had the best performance, although the model did not distinguish among most countries. The results of the Malmquist Productivity Index method also indicated that countries had different efficiencies and progress. Based on its results, Malaysia had the most progress, while Singapore had the least progress during the three periods. China despite its high-performance score from the window DEA, had not received a good score from the Malmquist Productivity Index and non-controllable input variables model, which implies the low growth and even retrogression of this country during the three periods. According to the results of the window DEA, Italy had progressed, but this growth has not been enough to make this country's performance efficient.
Research limitations/implications: The selection of different and more precise time intervals based on COVID-19 variants (alpha, delta and micron) and a wider selection of countries can be considered in future studies. Considering the amount of vaccination or the type of vaccine and observing its effects dynamically on the DEA model can be also a potential direction for future research. The development of window DEA and the Malmquist Productivity Index for uncontrollable variables and their application to the data of this paper are also suggested. Besides, the selection of input and output indicators based on other goals can be investigated in future studies.
Practical implications: To increase countries’ efficiency in dealing with epidemics such as COVID-19, different countries need to know as much as possible about their current situation. One of the ways to get this recognition is to compare them with other countries with the best performance. In such conditions, finding relative efficiency and trying to make the inefficient ones efficient is a solution to increase efficiency. It is possible to identify and extract coping strategies from successful countries with good performance in dealing with COVID-19, and suitable strategies can be implemented in Iran according to the required facilities and infrastructure.
Social implication: Appropriate reactions and successful strategies of health systems of countries in dealing with epidemic diseases such as COVID-19 can be very effective in controlling such diseases and reducing their negative social and economic impacts. The results of evaluating the efficiency of different countries along with the review of their strategies can be helpful in this direction.
Originality/value: An attempt has been made to present a new picture of countries' response to the COVID-19 pandemic by selecting a diverse range of countries, indicators, and relatively long periods using DEA. Windowed DEA, Malmquist productivity index and DEA with uncontrollable input variables in a period of almost three years were used for the first time to evaluate the efficiency of countries' health systems and their progress in dealing with COVID-19.
تبلیغات
