جستجوی مقالات مرتبط با کلیدواژه « تحلیل پوششی داده ها » در نشریات گروه « پزشکی »

Managers need to evaluate the performance of their subordinates in order to plan, organize, and improve the performance of their organizations. In this study, the performance and efficiency of the district's primary health care (PHC) system in the southeast of Iran were evaluated using the data envelopment analysis (DEA) model.

In this study, the efficiency of 9 cities affiliated to Kerman University of Medical Sciences was analyzed in 2019. The quantitative non-parametric DEA was used to evaluate the performance of the PHC system in the districts. Human forces, physical facilities, and vehicles were the variables used as the inputs, and the number of services and service recipients was considered as the outputs to measure efficiency. Data collection was done in the field using a checklist. The data were analyzed using the DEAP 2.1 software, efficiency was calculated with the output maximization approach and the assumption of variable returns to scale. It was carried out as linear programming with nine scenarios for nine districts in 2018.

The mean efficiency of the studied districts with the assumption of variable returns to scale was 0.68, indicating at least 32% capacity to increase efficiency in the studied PHC systems without any increase in production factors. According to the mean values, Kerman was efficient while the other 8 districts were inefficient. The most inefficient PHC systems were those of Shahr-e Babak, Baft, and Orzooieh.

Inefficiency in most PHC systems of the studied districts, indicating that PHC managers can provide more health services to the community through proper management of available resources. Inefficient districts can compare themselves with successful and reference districts to eliminate their shortcomings and improve their performance.

The outbreak of coronavirus disease 2019 (COVID-19) has led to many visits of patients to medical centers which has subsequently affected the performance evaluation of hospitals. One of the important non-financial performance measures is medical professional ethics. This study aims to evaluate the performance and rank the hospitals in Shiraz, Iran based on medical professional ethics affected by the COVID-19 pandemic.

Based on the balanced scorecard (BCS) method, the indicators were divided into four perspectives. Then, using the decision-making trial and evaluation laboratory (DEMATEL) method, the causality between the four BSC perspectives as well as the relative weights between the evaluation indicators were determined. The fuzzy data envelopment analysis (DEA) method was used to rank the performance of 37 hospitals. The DEA model ranked the decision-making units (DMUs) based on efficiency.

The DMUs (hospitals) 1, 3, 5, 8, 12, 13, 17, 21, 22, 23, 24, 25, 27, 28, 29, 30, 31, 32, 33, 35, 36 and 37 were efficient, while others were inefficient. 

The efficiency of hospitals in Shiraz is lower in learning and growth perspective than in other perspectives, and all hospitals are efficient in terms of customer perspective. This indicates that hospital managers pay less attention to learning and growth and more attention to the customer (patients) perspective during the COVID-19 pandemic.

Hospital is organization which its performance improvement is very important. In order to do this, we must evaluate the allocated resources and performance of hospitals. Calculating hospitals efficiency is one of the possible ways to evaluate the performance of them. In this study, the efficiency of allocated financial and human resources of public hospitals by provinces is examined.

This study was conducted in 2017-2018. Data were collected from 31 provinces of Iran. Input (including: number of physicians, number of nurses and number of active beds per ten thousand population) and output (number of hospitalizations and number of outpatients per ten thousand people). Data were collected from studies. The efficiency analyzing of the provincial treatment department was performed with DEAP software.

The input population (nurse, doctor, bed) is related to hospitals and health centers in Semnan, Yazd and Mazandaran provinces And the least amount of input was related to Sistan and Baluchestan, Khuzestan, North Khorasan provinces. The highest output (inpatient and outpatient) belongs to East Azarbaijan province and the lowest output belonged to Hamedan province. Efficiency score, variable return to scale and constant return to scale for all hospitals in the country are 0.565, 0.813 and 0.47, respectively.

proper and correct distribution of resources between provinces may increase efficiency of resource distribution.

 Today, there isgap between the potential of the health system and its current performance, which justifies the need to a performance appraisal model for the health sector. The purpose of this study is to provide a comprehensive performance evaluation model for assessing the performance of hospitals.

 For this purpose, 12 hospitals under the supervision of Tehran University of Medical Sciences have been selected as a case study. The fuzzy best-worst method was used to identify the criteria for assessing hospital performance based on expert opinions. The productivity of each hospital unit was calculated using the established criteria. The data research from the Tehran University of Medical Sciences statistical yearbook were collected during the years 2012 to 2016.The present study is applied in terms of purpose and based on the nature of the data, it is a quantitative research based on mathematical planning. This research was conducted in 1398 and was conducted in GAMS software.

The results show that Farabi Hospital, Roozbeh Psychiatry and Baharlo Hospital have the highest levels of efficacy, respectively and Arash Hospital, Farabi Hospital and Ziaeean Hospital have the highest rate of Effectiveness, respectively and Farabi Hospital, Arash Hospital and Ziaeean Hospital have the highest rates of Productivity during the Study period, respectively.

Also the efficiency, effectiveness, and productivity scores of most hospitals fluctuated and did not have a growing trend. This indicates that although most hospitals sought to improve the quality of their services, they needed to take more serious steps.

Productivity is one of the indicators for assessing the status quo regarding use of production factors, including financial resources, and the health management systems, especially hospitals, are no exception. This study endeavored to evaluate the financial productivity of social security hospitals in Iran using the Malmquist Productivity Index (MPI).

This study was a survey research. To calculate the MPI in all social security hospitals during 2015 to 2018, initially, through interviews with 10 experts in this field, the most important criteria for evaluating financial productivity in hospitals were identified (10 criteria). Seeing as the specified criteria had some special features, they required mathematical modeling; in such a way that some of these criteria were uncontrollable and others were among the undesirable criteria. The proposed mathematical model was a network data envelopment analysis (DEA) model with correct input and output, fixed input, and undesirable output for use in calculating the MPI.

The calculation of financial productivity of hospitals was possible using MPI and DEA method with the help of 10 main criteria including personnel cost, administrative cost, cost of transfer payments, number of active beds, cost of physicians’ benefits and perks, cost of staff’s motivational benefits and perks, the amount of invoices for hospitalized patients, the amount of invoices for outpatients, the sum of medical functions, and the number of days of hospitalization. The results confirmed those obtained in the previous studies.

Knowing the financial productivity of hospitals during different periods can lead to the optimal allocation of financial resources to increase the financial productivity of hospitals.

Measuring the efficiency of hospitals due to the high proportion of budget allocated to them on the one hand, and the need to ensure the best practices regarding the use of scarce resources on the other hand, is of particular importance. The purpose of this study is to evaluate the technical efficiency of the affiliated hospitals of Shahrekord University of Medical Sciences by using a combination of Principal Component Analysis and (PCA) & Data Envelopment Analysis (DEA).

This was an analytical and cross-sectional study measuring the technical efficiency of all 8 hospitals affiliated to Shahrekord University of Medical Sciences. The required information was collected from the medical records unit of each hospital. For better differentiation between efficient and inefficient units, and the increase of research accuracy and further differentiation between hospitals in terms of efficiency, at first, 17 indicators were selected to assess and adjust these parameters to 3 components proportional to the number of the hospitals by using PCA and SPSS 16 software. After doing the PCA, 7 studied input variables became 7 principal components among which the first input component reflecting the 83 % of scattering data was selected as principal input component, and for being more influenced by human resource variables, it was named as a human resource index. Furthermore, among the output variables, the first 2 output components, which represented 76% of the variance of the data, were selected as the 2 principal components of the output for the study, which were mostly affected by these variables, respectively, the number of admissions and length of stay. Then, the modified input and output components were entered into the software Windeap 2.1 and the technical efficiency of hospitals and their rank were calculated by assuming constant and variable efficiency with respect to the scale. In order to evaluate the effect of using the combined method instead of the conventional method of efficiency measurement, the results of the PCA - DEA method were compared with the results of the conventional DEA method.

The result of DEA on the selected components showed the capacity to upgrade the Technical Efficiency (TE) of hospitals is 15 % (TE: 0.852). Moreover, out of 8 hospitals, 1 hospital was increasing return to scale, 3 decreasing returns to scale and 4 constant returns to scale. The technical efficiency of 3 hospitals was 1 (TE = 1), 2 hospitals had the technical efficiency between 0.80 to 1 (1 > TE > 0.80) and that in 3 hospitals was less than 0.80 (TE < 0.80).  The scale efficiency for 50 % of hospitals and the management efficiency for 62/5 % of them were equal 1.

The average of total technical efficiency, management efficiency and scale efficiency were calculated to be 0.999, 1 and 0.999, respectively based on the usual comprehensive analysis method; while using the combined method, the average total technical efficiency, management efficiency and scale efficiency were 0.852, 0.947 and 0.902 respectively. The results confirm that the use of PCA method, due to its important role in reducing alignments, increases research accuracy and better differentiates between hospitals in terms of efficiency.

Urban health centers are one of the most important centers for providing primary health services. According to the wide range of health centers and the number of services provided by these centers, a significant portion of the community health system resources are allocated to these centers; therefore, the determination and continuous monitoring of the effectiveness of these centers can play a significant role in improving the efficiency of health resources and preventing waste of resources. The purpose of this study Assessment of Technical Efficiency of Comprehensive Health Services Centers of Hamadan by Data Envelopment Analysis (DEA) in 2019.

This descriptive-analytic study evaluates the effectiveness of Hamedan comprehensive health centers services using the data envelopment analysis method. Inputs include: number of physicians and number of employees (midwife, specialist in the fight against diseases.). Outputs include: number of examinations by physician, midwifery services, vaccinations, injections and dressings.

In 2018 the average technical efficiency of the comprehensive health services centers was 0.751, the mean management efficiency was 0.85 and the mean efficiency of the scale was 0.88. Of the total centers of comprehensive health services surveyed, 6 centers have technical capacity of 1 and 13 centers with a technical efficiency of less than 1.

In centers with efficiency less than 1, there were initial and optimal values of the same and different inputs. Therefore, it is suggested that these centers reduce their inputs as much as possible so that they can achieve maximum efficiency.

The outbreak of coronavirus disease 2019 (COVID-19) has become one of the important global challenges. According to World Health Organization (WHO), a long-term challenge is ahead. This study endeavored to investigate the performance of distinguished countries in the management of Covid-19 in two areas of disease control and treatment.

This was a descriptive study using WHO and World Bank databases carried out in the distinguished countries (including Iran) for three months from April 1 to June 30, 2020. After determining the input and output variables, the two-stage data envelopment analysis model was selected to calculate the proficiency of the countries. Besides, they were classified into four groups based on their performance in outbreak control and medical treatment.

During the study period, China and Iceland had the most performance, while Indonesia had the least in both aspects. Besides, the results of using area chart showed that China, Iceland, and Luxembourg were the only countries in the first area in each of the three consecutive months, which represented the highest level of performance.

By identifying the efficiency trend of the selected countries, actions and executive policies of the proficient countries can be good benchmarks for other countries to promote their performance.

There is no doubt that determining the efficiency of hospitals is one of the key steps that must be taken. Therefore, performance appraisal can help health plan executives to better understand its strengths and weaknesses. The purpose of this study is to evaluate the effect of health system transformation plan on the efficiency of selected hospitals in Ahvaz in the period 2012 to 2017.

Data related to seven hospitals implementing the project and one control hospital in 2012, 2013, 2016 and 2017 were collected. The efficiency of hospitals was calculated using data envelopment analysis technique using CCR method and WinDeap2 v 2.1 software. Independent t-test and Poisson using Stata v 15.1 software were used for inferential analysis.

The highest efficiency of hospitals were related to 2017 with average 0.987 and the efficiency of two hospitals in 2016 and 2017 was 1 and the other two hospitals have experienced an upward trend during these two years. Efficiency, number of hospital admissions, number of outpatient admissions and number of surgeries before the transformation plan were significantly different from after, but this difference was not true for the number of active beds, number of physicians and number of nurses.

Totally the efficiency of hospitals implementing transformation plan has been experienced an upward trend. considering the health system transformation plan in 2014, the improvement of the efficiency, the number of outpatient admissions, the number of hospital admissions and the number of surgeries was probably due to the transformation plan.

 Hospitals, as one of the main organizations providing health services, have a special sensitivity and importance in the economy and health. Full attention to the efficiency of the hospital as the largest and most costly operational unit of the health system is of particular importance, so the evaluation of hospitals is one of the most important issues for health policy makers.

Data Envelopment Analysis (DEA) is a method for evaluating the efficiency and productivity of decision units. If a network is composed of interdependent steps to generate outputs. Therefore, in this study, we have evaluated the relative efficiency of hospitals with output weight constraints for those outputs that have non-linear values. Equivalently, in the cover form, the give-and-take principle is used to take into account the output constraints. In this way, an ascending weight sequence is considered for larger output values of nonlinear value. This study is examined in a secret network. In this study, using the network data envelopment analysis approach, a system performance evaluation model has been designed that considers the relationship between weights as a reliable area in the evaluation.

In this article, the efficiency of 10 hospitals is examined with a new approach, of which only the fourth hospital has obtained an efficiency score of 1. An important feature is the change in the type of classification of efficient and inefficient units in the findings. The results showed that the proposed method is more accurate because by considering nonlinear pricing, it reduces the error that results from linear pricing in evaluations.

The resulting efficient and inefficient units are different from the previous classical methods, so different policies for the units must be considered by managers.

Hospitals are considered as the largest and most costly unit of the health system. The present study aims to determine the efficiency of hospitals in Mashhad.

This is a descriptive-survey study that was carried out in 2016-2017. The population of the study consisted of patients referring to hospitals in Mashhad. For data collection, records were used in hospitals and the SERVQUAL questionnaire. Data analysis was performed in soft Gams software.

The results of the study indicate that in the SERVQUAL section, three dimensions of empathy response and Warranty were the most important dimensions. Also, 3 characteristics of 26 qualitative features of the service were classified as "attractive". 4 qualitative features are classified as "essential" and 16 features in "single-dimensional". The rankings obtained in the bilingual network method are approximately the same and only in the case of the last four ranks of the final ranking is done by the voting method with equal weights. And it was determined that the hospital number (3) is the lowest and hospital number (5) has the best performance.

By combining the fuzzy SERVQUAL method with network data envelopment analysis, we can eliminate weaknesses in the selection of indicators in different layers of network analysis and calculate the efficiency of such networks. Hospitals need to increase and plan appropriately by designing a hospital that has the highest efficiency and optimal utilization of its resources and cost-effectiveness.

Given the limited government resources, increasing the efficiency and the productivity of using those resources is an important and challenging issue in every country. Thus, the aim of this study was to measure the efficiency and the productivity of the government health expenditures in Iran and other countries with high human development index (HDI) over the period of 1995-2014.Methods: This descriptive study used panel data of Iran and high-HDI countries to measure the efficiency and the productivity of government health expenditure. The non-parametric data envelopment analysis (DEA) method and Malmquist productivity index (MPI) were used.

The calculated average technical efficiency for Iran and high-HDI countries was 45 and 52 percent, respectively. A total factor productivity changes (TFP) of 0.93 and 0.99 was observed in Iran and high-HDI countries, respectively.

Technological efficiency changes have a major impact on the total factor productivity in Iran and high-HDI countries. By identifying the efficiency trend in different years, new proposals can be brought forward to increase the efficiency of government health expenditure in upcoming years.

Increasing the cost of hospital services in most countries, requires effective use of available resources through the use of resource assignment models and performance evaluation. Data Envelopment Analysis (DEA) is one of the mathematical models used to evaluate the performance of organizations with homogeneous units based on inputs and outputs. The purpose of this study was to evaluate the financial performance of NAJA hospitals using the Data Envelopment Analysis and ranking them based on efficiency.

For this descriptive research, data was collected through hospitals’ documents and formulated in BCC output model using Lingo software.

All NAJA hospitals have a relative level of efficiency, but there are differences in levels. ‘A’ hospital ranked first and ‘G’ hospital was the last.

To increase efficacy, NAJA hospitals should focus on increasing outputs of model, instead reducing the inputs.

Nowadays efficiency analysis due to identification of weaknesses, strengths and amount utilization of available resources is important. The purpose of this study was efficiency analysis and ranking of provincial units of Social Security Organization (SSO) in indirect treatment sector.

In this descriptive cross-sectional study, technical, managerial and scale efficiencies of SSO in 31 provinces of Iran by input oriented model of Data Envelopment Analysis (DEA) with assuming variable returns to scale were analyzed and the provinces were ranked using the Anderson-Peterson model. The input variables included number of specialized staff, number of support staff, income amount of each province and the output variables included number and cost of prescriptions that have been investigated. The required data were adapted from the 2017 SSO Statistical Yearbook and data analysis was performed using DEAP 2.1 and EMS 1.3.0 software.

Average scores of technical efficiency 0.880, managerial efficiency 0.818, and scale efficiency 0.928 were calculated. Based on above efficiency scores, Kohgiluyeh and Boyerahmad and Tehran ranked first and Kerman ranked last.

In general, there is capacity of technical, managerial and scale efficiency improvement respectively 12%, 18.2% and 7.2% in indirect treatment sector of SSO. Therefore, weak and inefficient provinces should be placed in the priority of improving efficiency. This can be achieved through imitation of efficient provinces, implementing electronic prescribing and more accurate management of SSO revenues and number of human resources employed in the indirect treatment sector.

Improving the efficiency and productivity of the higher education, especially in the field of research on health sciences, is one of the characteristics of sustainable development in today's societies. This study aimed to measure the efficiency and productivity of Iran's Medical Sciences Universities (MSU) in the research function. In a descriptive study, the research function of fourty five MSUs in Iran was evaluated using data envelopment analysis (DEA) method and Malmquist index in 2010, 2013, and 2016 years. Measurement of both efficiency and Malmquist index was developed and modeled based on the assumption of variable returns to scale (VRS) and output-oriented. Also, the ranking of efficient units was done using Anderson-Patterson's model. The mean research efficiency was estimated to be 0.86. Findings of Malmquist index showed that between 2010 and 2013, there was a 6% growth in the productivity; while the performance of universities had a 12% drop in research function from 2013 to 2016. Also, the average total productivity during two periods is 0.96, indicating 4% reduction in research efficiency which technology efficiency growth has dropped by 8% and other components of total productivity had a positive growth. The results of the study showed that universities do not work efficiently and average productivity has been decreasing which was mainly due to a decline in the efficiency of technology, which despite the development of technology in recent years could be the result of the lack of effective use of it.

The higher education system plays an important role in the socio-economic development of the country due to its mission in training the required human resources. Therefore, performance evaluation of different sectors of higher education is of great importance. The present study was conducted to evaluate the educational efficiency and productivity changes of Iranian medical sciences universities. This descriptive study was conducted in 2011, 2014, and 2017 to evaluating the performance of 43 Iranian medical universities using Data Envelopment Analysis and output oriented approach. In addition, productivity changes were measured using the Malmquist index. For this purpose, Deap 2.1 software was used. The Anderson Patterson Model and EMS software were also used to rate the units accurately. The average educational efficiency of medical universities was 0.97 in the study years. The average total productivity based on the Malmquist Index was 1.05, and educational productivity of the universities showed an average growth of 5% over the study years. This growth was 1% from 2011 to 2014 and 10% from 2011 to 2017. The results of the study showed the acceptable efficiency of the education sector of Iranian medical sciences universities. Moreover, a positive increasing trend was observed in the productivity of the education sector during the study years. Further research using quality and quantity measures are necessary to assess the educational performance of medical universities more accurately.

Because of organizations must to have a clear perspective of continuing profitability to be accepted in the capital market, researchers survey efficiency evaluation of the Iranian Public Hospital, so that select qualified hospitals for admission to the capital market by separating efficient and inefficient hospitals

It is a descriptive, analytical and retrospective study. Data envelopment analysis technique, CCR model and BCC input-axis, were used to measure efficiency. Data includes input and output of public hospital operations, as the inputs include the number of active beds, the number of physician personnel, the number of non-medical personnel and output include the number of hospital admission, the number of outpatient admissions and the bed occupancy rate. The statistical population consisted of 592 public hospitals. According to available data, 558 hospitals were selected. The DEA Solver Pro and SPSS software were used.

In the CCR model, 123 hospitals were efficient (22%), and in BBC model, 183 Hospitals (33%). The average efficiency of hospitals in the CCR model were 0.66 and in the BCC model were 0.75.

According to the data envelopment analysis model (input-axis) inefficient hospital can achieve efficient unit by changing their inputs. But it seems to make sustainable changes, Macro policies and strategies in the health sector should be changed, which can include the autonomy of hospitals, the integration of efficient and inefficient hospitals, Or the formation of hospital cooperation and accept in the capital market.

Introdution: It is very important to pay attention to the health centers and their roles in countries. Improving the performance of these centers is dependent on their performance evaluation. The aim of this study was evaluating the relative efficiency of health centers with a combined approach of DEA and GT. For this purpose, first by reviewing relevant researches, inputs and outputs associated with the operation of health centers were identified and with a field study, the variables were matched with forms and information resources available in the health center data base. Then, by visiting experts from different functional areas, performance criteria were fitted with proportional data. After data gathering, mathematical modeling has been prepared based on the hybrid DEA-Game techniques. The DEA-Solver and Lingo software, mathematical models were designed and solved. Results showed that performance levels among health centers in Yazd City are different. With reprogramming the resources that was affected the performance of health centers, included the number of employees and their covered population it has expectd an improvement in their efficiency. Managers and policymakers of health care centers can use the model presented in this study to measure the relative efficiency of these centers and to improve their efficiency.

  Efficiency and productivity are considered as the most important performance indicators of an educational organization. This study aimed to estimate the efficiency and productivity of schools in Ahvaz University of Medical Sciences, Ahvaz, Iran. This descriptive study was based on panel and time series data. In total, seven schools of Ahvaz Jundishapur University of Medical Sciences were assessed during 2011-2015 in terms of efficiency and productivity. The input and output indexes were determined based on research and educational performance of schools. In this research, data envelopment analysis method and the Malmquist productivity index (MPI) were used to analyze the efficiency and productivity of schools, respectively. Data analysis was performed in Deap.2 software. In this study, mean index of changes in management, scale, technical and technological efficiency over five years were 1 (constant), 0.991 (decreased), 0.991 (decreased), and 0.862 (decreased), respectively. In addition, all efficiency and productivity indexes grew in 2014, compared to the other years. Moreover, the mean total productivity of schools evaluated in the research was reported to be 0.855. Therefore, the schools had a relative decline in productivity (15.5%) during 2011-2015. Furthermore, the total productivity index increased in 2012 (+19.8%) and 2014 (+73.4%). Among the schools assessed, the schools of medicine (47%), health (43%), pharmacy (32%), nursing (14%), and dentistry (13%) had a reduction in productivity, respectively. On the other hand, the schools of paramedical (80.1%) and rehabilitation (18.4%) had the highest rate of productivity growth among the schools of Ahvaz University. According to the results of this study, efficiency and productivity of evaluated schools required improvement. In this regard, the most important factor for the increase and decrease of total productivity index of the schools was technological efficiency