Journal of Health Management and Informatics
Volume:8 Issue: 1, Jan 2021

Economic growth has a direct impact on public health expenditures; also, itindirectly affects public health expenditures through the environment’s quality. Therefore,this study aimed to investigate the relationship between environmental performance index,economic growth, and public health expenditures in countries with high and very highhuman development index. The present descriptive-analytical and applied study was performed on 16 countrieswith high and very high human development index. The time-series data required for theyears 2006-2018 were extracted from the World Bank and United Nations database andenvironmental performance index extracted from the Yale University website. Im, Pesaranand Shin (IPS), Levin, Lin, and Chu (LLC), Augmented Dickey–Fuller (ADF)– Fisher, andPhillips-Perron (PP)–Fisher tests for stationary and Pedroni and Kao tests for cointegrationwere used. The study model was estimated by the DOLS cointegration method in Eviews 10software. The mean environmental performance index for selected countries with very highand high human development index was 79.04 and 64.71, respectively; also, the elasticity ofpublic health expenditures to gross national production, environmental performance index,physician supply, and urbanization ratio were 0.96, -2.41, 0.441 and 0.448, respectively. Increasing economic growth, urbanization ratio, and physician supply hada positive effect, and improving environmental performance index had a negative effecton public health expenditures. Therefore, to reduce public health expenditures, policiesare recommended to maintain environmental sustainability and reduce environmentalpollutants, and to invest in advanced equipment to purify pollutant gases. Maintaining andincreasing economic growth is also essential for adopting policies to increase physicians andinvest in health infrastructure.

Reclassification risk in the health insurance market happens when premiumprices are determined based on the health level. It is necessary for insurance applicants tomanage this risk due to uncertainty about the individual’s health status in later periods.Guaranteed renewable insurance fully covers this risk because the health level is not takeninto account in calculating the premiums. This study is an attempt to calculate the welfarebenefits resulting from the coverage of this risk by providing guaranteed renewable insurancein this market. The economic welfare model in the form of computable general equilibrium hasbeen used to measure welfare. The model is calibrated by the data of social accounting matrixand national health accounts in 2011. Social accounting matrix is extracted based on the latestinput-output table for the economy of Iran presented in this yea The results show that, in general, the more guaranteed renewable insurance expandsin the health insurance market, the greater the welfare effects will be; therefore, the eliminationof basic insurance from this market and provision of the same insurance for all people in theform of guaranteed renewable insurance (complete elimination of reclassification risk) canincrease economic welfare up to 6%. Reclassification risk management by providing guaranteed renewable insurancein the health insurance market of Iran, due to increasing the welfare of the insured, will leadto the provision of a unit insurance plan and equal access to health services for all.

One of the important factors that may affect the destination of developmentis medical and healthcare tourism. The presence of experts in medical tourism and thegeographical location of Iran is one of the most important factors in the sustainabledevelopment of Iran. This study aimed to identify and prioritize the components of themedical and healthcare tourism entrepreneurship ecosystem (EE) in Iran with a structuralinterpretivemodeling approach.

This research is methodologically a mixed (qualitative-quantitative) exploratorytype, and its participants were health tourism experts and entrepreneurs. The method forselecting the participants was Purposeful sampling.15 participants were interviewed based ontheoretical saturation. The data collection tools were interviews and questionnaires. Also, toanalyze the data in this research, we used two overlapping processes of open and axial codingand structural-interpretive modeling.

The results of data analysis showed that the components of the health tourism EEwere included in the seven main dimensions of law, regulations and governance factors,financing and investment, the role of culture, influential institutions (universities andEducational centers), influential regional market factors, the role of human capital, andeffective infrastructure.

Researchers examining entrepreneurial ecosystems have not studied the roleof a regional level of analysis. The results of qualitative analysis and Interpretive StructuralModeling (ISM) showed that to create the entrepreneurial ecosystem of the medical andhealthcare tourism, the central factors resulting from qualitative research interacted with eachother at three different levels, and the set of factors at these levels caused the medical sciencesuniversity to move towards creating an Entrepreneurial ecosystem drive in the university

Trauma patients are potentially at high risk of acquiring infections in hospitals,which is the main cause of in-hospital mortality. The aim of this study was to identify the riskfactors contributing to death from hospital-acquired infections in trauma patients by datamining techniques.

This is a cohort study. A total of 549 trauma patients with nosocomial infectionwho were admitted to Shiraz trauma hospital between 2017 and 2018 were studied. Sex,age, mechanism of injury, body region injured, injury severity score, length of stay, typeof intervention, infection day after admission, microorganism cause of infections, andthe outcomes were collected. Association rule mining techniques were applied to extractknowledge from the data set. The IBM SPSS Modeler data mining software version 18.0 wasused as a tool for data mining of the trauma patients with hospital queried infections database.

The age older than 65, surgical site infection skin, bloodstream infection, mechanisminjury of car accident, invasive intervention of tracheal intubation, injury severity score higherthan 16, and multiple injuries with higher than 71 percent confidence level were associatedwith in-hospital mortality. The relationship between those predicators and death amonghospital-acquired infection was strong (Lift value >1).

Factors such as increasing age, tracheal intubation, mechanical ventilator,surgical site infection skin, upper respiratory infection are associated with death fromhospital-acquired infections in trauma patients by data mining.

Public higher education is competing for limited public funds. Activity-basedcosting (ABC) provides detailed evidence that higher education administrators and policymakerscan be employed to allocate scare resources more effectively and better understandwhat education centers do. Conducting context-specific studies on ABC and budgeting foreducational systems is the crux of the matter for cost containment and making decisions. Thepresent study was undertaken with the aim of determining the costs of training undergraduateand postgraduate students.

This is a descriptive-analytic and applied study. The costs incurred by 7 differentdisciplines and degrees including bachelor (n=2), master (n=4), and PhD (n=1) in the Schoolof Management and Medical Information Sciences of the Shiraz University of MedicalScience in the academic year 2015-16 were examined and costs of training undergraduate andpostgraduate students were totaled by ABC method. The total number of students in includeddisciplines was 269; of them, 71% were studying in the bachelor, 26% in the master, and 3%in PhD programs. Since the primary purpose of our study was to calculate the total sum ofcost per student, no sampling was done. After identifying the activity centers and incurredcosts per activity center, the proportion of the schools’ costs to the university headquarter wastraced. In the school level, the costs of non-faculty staff by the deputies of education, research,support, and cultural-student affairs were estimated. Moreover, other costs, namely energycosts, rentals, consumables, depreciation, and missions were determined and assigned basedon the number of students. Data management and analysis were performed using Excel 2007.

The cost of training undergraduate students in the disciplines of health servicesmanagement and health information technology was $24413±2891 and $24286±2926,respectively. The maximum cost of schooling a student in the master degree belonged to thediscipline of medical informatics. The total cost of training a PhD student in the academicyear 2014-2015 was $95303±16106.

In an era of resource scarcity, the ability to recognize the gaps between resourcesand academic goals and redirect the resources into programs which maximize the valueadded is crucial for all higher education institutes.

Job crafting is the process of making proactive changes in the boundariescomposing a job, which are known as mental fences that individuals adopt to define their job’sphysical, emotional, or cognitive limitations. Job crafting considers the change in the natureof jobs, whether realistically in the form of task crafting and relational crafting, or as cognitiveperceptions. In this study, the role of self-efficacy as the antecedent and work engagement asthe consequence of job crafting was studied.

The jobs were academic and the sample was selected from faculty members ofShiraz University of Medical Sciences. The research questionnaires were distributed amongfaculty members of Shiraz University of Medical Sciences. A PLS model is analyzed andinterpreted in two stages: the assessment of the reliability and validity of the measurementmodel, and the assessment of the structural model.

The results showed that self-efficacy was positively related to all dimensions ofjob crafting. Moreover, the triple dimensions of job crafting had a significant positiveeffect on work engagement. The moderating role of gender and academic level in therelationship between self-efficacy and work engagement was confirmed. However, theresults showed that gender did not moderate the relationship between self-efficacy andtask crafting.

The main novelty of this research is the study of job crafting, self-efficacy andengagement variables considering the moderating role of gender and academic level.

The purpose of this research is to provide an appropriate framework forimplementing IT management services in the field of pre-hospital emergencies with anintegrated approach of COBIT maturity model and ITIL framework.

In a qualitative part, experts familiar with the field of pre-hospital emergency andinformation technology were purposefully selected. In the quantitative phase of the statisticalcommunity, we included experts in the field of information technology management whoare also experts in the field of emergency, as well as university professors who workedin the field of emergency and senior and middle managers in the field of pre-hospitalemergency entered the community. Considering the limitations of the community and thepurposefulness of the selection of individuals to enter the community, 915 individuals wereselected as a sample. To select a sample in the quantitative section, Morgan table was used.They were selected by simple random method using software. To collect information, wefirst reviewed the texts and articles in the field of ITIL and COBIT and then the extractedcodes in this category were reviewed and an overview of the research was obtained; then,in the qualitative part the interview method and in the quantitative part the researchermadequestionnaire were used. To analyze the data in the qualitative section, we used MAXQDA software to review and categorize the information. Then, in the quantitative section,the researcher-made questionnaire was collected and finally the model was fitted usingconfirmatory factor analysis.

In the end, it was concluded that the main components such as management,organization, processes, eyes, size, goals of the organization, staff, monitoring and evaluation,support, organization, information architecture and service delivery and their subcomponentswere the main factors that should be paid special attention in the field of prehospitalemergency management.

To be more successful in implementing the organization’s framework, it mustidentify the most important problems and then create a controllable domain to implementservice support processes in the organization. The selected processes should be strongly andclearly supported by the general management of the organization. A codified and specificplan for implementation should be developed. A coordinated and planned approach fordesign, implementation should be specified and after the implementation of the mentionedprocesses. After expressing the output measurement indicators of the processes, the outputsshould be measured and based on the changes that exist, these changes should be consideredand returned to the planning stage to re-formulate the steps.

Distinguishing P300 signals from other components of the EEG is one of the mostchallenging issues in Brain Computer Interface (BCI) applications, and machine learningmethods have vastly been utilized as effective tools to perform such separation. Althoughin recent years deep neural networks have significantly improved the quality of the abovedetection, the significant similarity between P300 and other components of EEG in parallelwith their unrepeatable nature have led to P300 detection, which are still an open problemin BCI domain. In this study, a novel architecture is proposed in order to detect P300 signalamong EEG, in which the temporal learning concept is engaged as a new substructureinside the main Convolutional Neural Network (CNN). The above Temporal ConvolutionalNetwork (TCN) may better address the problem of P300 detection, thanks to its potentialin involving time sequence properties in modelling of these signals. The performance ofthe proposed method is evaluated on the EPFL BCI dataset, and the obtained results arecompared in two inter-subject and intra-subject scenarios with the results of classical CNNin which temporal properties of input are not considered. Increased True Positive Rate ofthe proposed method (an average of 4 percent) and its accuracy (an average of 2.9 percent)in parallel with the decrease in its False Positive Rate (averagely 3.1 percent) shows theeffectiveness of the TCN structure in promoting the detection procedure of P300 signals inBCI applications