Shiraz University of Medical Sciences
Health Management & Information Science
2783-302X
6
3
2019
07
01
Management of IT Services in the Field of Pre-Hospital Emergency Management with the Combined Approach of COBIT Maturity Model and ITIL Framework: A Conceptual Model
85
95
EN
Saeed
Saeedinezhad
0000-0003-0132-8967
Ph.D. Student in Information Technology Management,Faculty of Management, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
saeedsaeedinezhad@gmail.com
Amirreza
Naghsh
0000-0003-1572-7221
Department of Management, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
ar.naghsh@khuisf.ac.ir
The purpose of emergency management planning is to enable the management to make<br />quality decisions under the pressure of time to avoid or minimize the damage Planning is<br />a complex issue, which involves key actions and critical decisions. It improves the response<br />to the effects of a disaster by organizing timely delivery, effective rescue, relief and timely<br />and reliable assistance; also, it ensures that the right people are functioningat the right time.<br />Effective plans are also intended to provide and possibly include the resources and proprietary<br />funds that are provided through powerful rules. Written and well documented programs<br />increase the likelihood of successful outcomes.<br />This research aims to develop an information technology (IT) maturity model for prehospital<br />emergency management that merges the most known IT frameworks’ practices.<br />Our proposal intends to help the organizations overcome the current limitations of<br />multiframework implementation by informing the organizations about the frameworks’<br />overlap before their implementation. ITIL is the most popular “best practices” framework for<br />managing Information Technology (IT) services. However, not only implementation of ITIL<br />is very difficult, but also there are no recommendations and guidelines for it. As a result, ITIL<br />implementations are usually long, expensive and risky. In this paper, we proposed a maturity<br />model to assess an ITIL & COBIT implementation and provided a roadmap for improvement<br />based priorities, dependencies, and guidelines. We finally concluded that considering ITIL &<br />COBIT implementation in pre-hospital emergency management could be very useful.
IT services,pre-hospital emergency management,COBIT,ITIL
https://jhmi.sums.ac.ir/article_45871.html
https://jhmi.sums.ac.ir/article_45871_5bd53305a1d24fde1c91223689b9976b.pdf
Shiraz University of Medical Sciences
Health Management & Information Science
2783-302X
6
3
2019
07
01
Improved Accuracy of Predicting Diabetic Retinopathy in Type 2 Diabetes Mellitus using Genetic Algorithm
96
105
EN
Saghar
Foshati
0000-0002-4130-6255
M.D
sagharfoshati@gmail.com
Ali
Zamani
PhD
zamaniali@yahoo.com
Malihe
Sabeti
PhD
msabeti@yahoo.com
<strong>Introduction</strong>: Diabetes mellitus is a prevalent disease and its late diagnosis leads to<br />dangerous complications and even death. One of the serious complications of this disease<br />is diabetic retinopathy, the leading cause of blindness in the developed countries. Because<br />of slowly progressive nature and lack of symptoms in the early stages of the disease, it is<br />essential to predict the probability of developing diabetic retinopathy promptly to implement the appropriate therapy.<br /><strong>Methods</strong>: Our dataset contains 29 extracted features from 310 patients with types 2 diabetic disease, 155 patients of whom sufferred from diabetic retinopathy. The patients were selected randomly from Motahari clinic in Shiraz, Iran between 2013 and 2014. First, the genetic algorithm, (GA) as a feature selection process, was implemented to select the most informative features (high-risk factors) for prediction of diabetic retinopathy. Then, three well-known classifiers including k-nearest neighbors (kNN), support vector machine (SVM), and decision tree (DT) were applied to the optimized dataset for classification of the two mentioned groups.<br /><strong>Results</strong>: Our finding showed that GA selected 13 factors for better prediction of diabetic<br />retinopathy; these factors were the duration of the disease, history of stroke, family history, cardiac diseases, diabetic neuropathy, LDL, HDL, blood pressure, urine albumin, 2HPPG, HbA1c, FBS, and age. Given the selected risk factors, the classification accuracy was obtained 69.35%, 81.29% and 96.13% by SVM, DT, and kNN, respectively. Our results showed that kNN had the highest accuracy in the prediction of diabetic retinopathy compared to SVM and DT, and the difference between kNN and the other algorithms was statistically significant.<br /><strong>Conclusion</strong>: The proposed approach was compared and contrasted with recently reported<br />methods, and it was shown that a considerably enhanced performance was achieved. This<br />research may aid healthcare professionals to determine and individualize the required eye<br />screening interval for a given patient.
Diabetic Retinopathy,Feature selection,genetic algorithm,Classification
https://jhmi.sums.ac.ir/article_45869.html
https://jhmi.sums.ac.ir/article_45869_bf531c21b31892b1337c116d67ec0bf6.pdf
Shiraz University of Medical Sciences
Health Management & Information Science
2783-302X
6
3
2019
07
01
A Scientometric Assessment of the Medical Universities Performance: Two Decades Analysis from 1998 to 2018
106
118
EN
Mohammad Reza
Zare Banadkouki
Faculty of Industrial Engineering, Meybod University, Meybod, Iran
mr.zare@gmail.com
<strong>Introduction</strong>: Given the key role of universities and higher education institutes in the<br />social and economic development of countries, it is necessary to evaluate their performance regularly with appropriate methods and measures. Since research and science production are among the essential functions of universities, measurement of scientific outputs is an important part of university performance evaluation. The aim of this study was to rank the Iranian medical universities by scientometric indicators.<br /><strong>Methods</strong>: One way to evaluate the scientific outputs is to use one of many scientometric<br />indicators defined over the years for quantitative and qualitative evaluation of the researchers. This approach can also be expanded for evaluation at the university level. In the descriptive<br />survey presented in this paper, 152597 scientific articles published by the authors affiliated<br />with 50 Iranian medical universities were investigated. The scientific output data extracted<br />from the Scopus database of each university were analyzed separately using the cumulative<br />number of scientific papers, number of citations, citation impact, h-index, m-parameter,<br />and g-index. The universities were then ranked according to each indicator. This study is<br />an applied research based on the results. The sample number in this study was all scientific<br />output of the universities studied.<br /><strong>Results</strong>: Among the studied universities, Tehran University of Medical Science ranked first<br />in terms of cumulative number of scientific papers, citations, h-index, and g-index, Alborz<br />University of Medical Science ranked the first in terms of m-parameter, and Arak University<br />of Medical Sciences ranked the first in terms of citation impact.<br /><strong>Conclusion</strong>: The obtained rankings were compared with the results of Islamic World Science<br />Citation Database (ISC) ranking system. This comparison showed that the rankings of Iranian medical universities based on cumulative number of papers, number of citations, and h-index were strongly correlated with the results of ISC ranking system.
Scientific Performance,Medical University Ranking,Scientometric,Scientific output
https://jhmi.sums.ac.ir/article_45870.html
https://jhmi.sums.ac.ir/article_45870_d6a9a45d040b8d4699650d9ce8a37f52.pdf
Shiraz University of Medical Sciences
Health Management & Information Science
2783-302X
6
3
2019
07
01
Influencing Factors on Buying Health Supplemental Insurance by the Staff of Shiraz University of Medical Sciences
119
125
EN
Zahra
Kavosi
0000-0001-8662-7987
Health Human Resources Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
zhr.kavosi@gmail.com
Effat
Norouz Sarvestani
student research committee, Shiraz University of Medical Sciences, Shiraz, Iran
effatnoroozi@yahoo.com
Najmeh
Bordbar
0000-0001-9179-857x
Ph.D. candidate of health services management, Student Research Committee, School of Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran.
nabordbar@gmail.com
Mohsen
Bayati
0000-0002-9118-5447
Health Human Resources Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
bayatim66@gmail.com
Farhad
Lotfi
0000-0002-2323-4307
Health Human Resources Research Center, Shiraz University of Medical Sciences, Shiraz, Ira
lotfifarhad@gmail.com
<strong>Introduction</strong>: One of the most reliable sources of financing healthcare costs is health<br />insurance. Covering all the services by basic health insurance is not affordable economically, so that some services are covered by supplementary health insurances. This study aimed to determine the factors influencing buying the different levels of Kowsar supplementary health insurance by the staff of Shiraz University of Medical Sciences in 2014-2015.<br /><strong>Methods</strong>: This is a cross-sectional study. Two data collection forms were used to collect the<br />data. A sample size of 500 was determined using the rule of thumb. The individuals were<br />selected via using two-stage stratified and systematic sampling. To do the estimation, the<br />ordinal logistic regression model (link function was logit) was specified by the one-sided<br />significant variable tests at the first step. Then, the independent variables were examined by the link test, and the linear relationship among variables was also investigated. The software Excel 2010 and STATA 11.0 (stata corp LLC) were used in this paper.<br /><strong>Results</strong>: The findings showed that among the people with supplementary insurance, the<br />majority were males (60%), married (85%), with the basic Tamin Ejtemaei insurance (72.3%). Among those who have not chosen the supplementary health insurance, the largest number were women (69%), unmarried (53%), and insured by Tamin Ejtemaei (80%), respectively. The findings suggest that some factors such as the age, gender, income and cost of insurance packages are the most influential factors on buying different levels of health care insurance. In the first model that included people with supplementary insurance, the income elasticity was significant and positive (Beta=3, P=0.047) and price elasticity of demand was negative (Beta=-0.06, P=0.001). In the second model that complemented those with and without supplementary insurance, the income elasticity was insignificant (Beta=2.46, P=0.085), and the demand price elasticity was negative (Beta=-0.06, P=0.001).<br /><strong>Conclusion</strong>: The economic factor seems to be the most influential factor in choosing<br />supplementary insurance. Since this problem causes the low-income households not to use<br />the insurance; therefore, the government is required to allocate some subsidies for low income household to be covered by supplementary health insurance for special services.
Supplementary Health Insurances,None for Profit Insurance,Logistic Models,Health Financing
https://jhmi.sums.ac.ir/article_45872.html
https://jhmi.sums.ac.ir/article_45872_080e5661fccb5f82558a589228b84ce6.pdf
Shiraz University of Medical Sciences
Health Management & Information Science
2783-302X
6
3
2019
07
01
An Evaluation of the Efficiency Rankings of the Schools of Shiraz University of Medical Sciences Using an Integrated Approach of Data Envelopment Analysis and Goal Programming
126
132
EN
Maryam
Najibi
0000-0003-1214-5314
School of health services Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran.
m.najibi90@gmail.com
Payam
Shojaei
Department of Management, Shiraz University, Shiraz, Iran
pshojaei@yahoo.com
Najmeh
Bordbar
0000-0001-9179-857x
Department of Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran
nabordbar@gmail.com
Peivand
Bastani
Department of Management and Medical Information, Shiraz University of Medical Sciences, Shiraz, Iran
peivandbastani@hotmail.com
Amin
Amiri
Department of Management and Medical Informatics, Shiraz University of Medical Sciences, Shiraz, Iran
aamiri@gmail.com
<strong>Introduction</strong>: Performance appraisal and efficiency evaluation of schools and universities<br />have had remarkable growth over the past two decades. The present study evaluated the<br />performance of the schools of Shiraz University of Medical Sciences.<br /><strong>Methods</strong>: This is a cross-sectional study, conducted in 2017 on 10 schools of Shiraz University of Medical Sciences using data of the year 2016 related to 5 inputs and 12 outputs. In order to determine the weights of the inputs and outputs, fuzzy weighting was performed based on the experts’ views. Then, by utilizing an integrated approach of data envelopment analysis (DEA) and goal programming (GP), the efficiency of the schools was determined using model Minimax. The final rankings were made by employing the super-efficiency ranking method (Anderson-Peterson). The results were exported using TORA software after producing the relevant linear models for each school. The software uses the notation and procedures developed in Taha Hamdi, Operation Research: an introduction, 5/e, Macmillan1992 ,.<br /><strong>Results</strong>: Results from the Minimax model, which presented the best answer, showed that<br />the Schools of Dentistry, Pharmacy, Nutrition and Food Sciences, Paramedical Sciences, and<br />Health were efficient with respect to the 5 inputs and 12 outputs. By employing the superefficiency ranking method of Anderson-Peterson, the highest ranks and points were related to the Schools of Nutrition and Food Sciences, Paramedical Sciences, and Dentistry. The average efficiency score of the schools was 0.89<br /><strong>Conclusion</strong>: According to the results some schools must enhance their outputs. The<br />continuous evaluations and publication of research results leads to awareness of the relative status and ranks, and ultimately causes increased competition and efforts to improve the efficiency of the schools.
Data Envelopment Analysis,Goal programming,Efficiency,Fuzzy-Weighting
https://jhmi.sums.ac.ir/article_45873.html
https://jhmi.sums.ac.ir/article_45873_2009334dd986f0427ab67c12fb0521d9.pdf