Journal of Health Management and Informatics
Volume:8 Issue: 3, Jul 2021

The quality management and financial control of drugs have been considered as a priority for healthcare managers. The drug classification and coding systems, as an information management tool, could be beneficial. The review aims to extract the characteristics of the drug classification systems and identify their main applications in the drug management processes.

For this purpose, the library sources including e-databases PubMed, Scopus, Web of Science, and Google Scholar search engine, e-files, and specialized websites were searched using keywords “Drug”, “Classification system”, “Coding system”, and “Terminology” alongside their synonyms. The search results were limited to the drug classification systems that categorize drugs and pharmaceutical information using code sets with an appropriate granularity level.  

Twenty-eight drug classification systems were included. Half of these systems are used internationally, and the others are used nationally. All included systems were divided into three categories, based on their features. The domain classification of systems includes human drugs, animal drugs, herbal medicines, dosage forms, drug side effects, and ingredients of medicinal products. Most of them are hierarchically designed. The code structure of these systems was mainly numerical, and some of them were alphabetical-numeric or alphabetical. They are mostly applied for unique identification, interoperability, statistics, pharmacovigilance and drug-related problems, marketing, and artificial intelligence methods.  

The drug classification systems are designed in different ways with respect to their applications. The development of multipurpose systems and provision of  efficient mapping among these systems could be beneficial to improve the drug management processes.

Outsourcing in healthcare services is becoming a significant and popular strategy. Paying more attention to the essential activities and poor performance of internal departments is one of the most important reasons, causing the organizations to outsource their activities. This study seeks to propose an effective outsourcing model using fuzzy MCDM methods in Zeinabieh Hospital, Shiraz, Iran. In this research, the mixed methodology was used. In the first stage, all of the criteria affecting the outsourcing of the wards and units in the hospital were identified though a literature review and with reference to the opinions of the experts in the hospital. In the second stage, these criteria were finalized using content validity ratio (CVR) and the fuzzy best-worst method (BWM). Finally, the selected wards and units were identified and prioritized through fuzzy VIKOR method. The results showed that seven criteria constituted the final model of outsourcing in Zeinabieh Hospital wards/units: strategy, management, economic aspects, quality, security and protection of information of patients and related centers, service, and agility. The fuzzy BWM analysis showed that the “economic aspects” had the highest priority in outsourcing-related decision-making, and according to the fuzzy VIKOR analysis, among all the wards and units, the clinic showed the highest priority. Making decisions about outsourcing in hospital services is a complex and multi-criteria problem. Therefore, different factors must be considered in the process of outsourcing hospital wards and units. This study proposed a model that could efficiently and effectively facilitate the process of outsourcing of hospital wards and units.

The present study was carried out to analyze the costs involved with COVID-19 in one of the largest hospitals in Iran. In this descriptive study, the total costs of hospitalization in Imam Khomeini Hospital affiliated to Tehran University of Medical Sciences for COVID-19 confirmed patients were analyzed until April 17, 2020. Data were extracted by reviewing patient record bills, and analyzed using descriptive and analytical statistics in SPSS 21. Data related to 1324 patients with COVID-19 were analyzed. Totally, 32.4% of all hospitalized patients had comorbidities, and 13.7% required intensive care and were admitted to the ICU. The average cost per hospitalized patient was 33,121,029 Rials (US $ 209.22), but this average had a high standard deviation (66,936,158 Rials, US $ 422.82). There was a significant difference in costs based on the length of stay (P-value = 0.000), ICU hospitalization (P-value = 0.000), presence of comorbidities (P-value = 0.002), age (P-value = 0.002) and gender (P-value = 0.002), but the results of path analysis showed that only the variables of length of stay and hospitalization in the ICU had a direct effect on the costs and other factors had indirect effects. COVID-19 is imposing significant costs on the health system, a significant proportion of which belongs to the length of hospital stay and the need to intensive care units. Directing resources to expand timely diagnostic capacity and manage disease in the early stages can both reduce the financial burden of providing highly costly inpatient services.

Overweight obesity is now so widespread in the world. This study aims to use an artificial neural network modeling tool to develop a predictive model for the diagnosis of obesity in children and adolescents.   Participants consisted of 460 school students, aged 7-18 years, who studied in a national school-based surveillance program (CASPIAN-V). Training network with 10 input variables including: age, sex, weight, height, waist circumference, systolic blood pressure, diastolic blood pressure, body mass index, waist-to-height ratio, physical activity, and with output variable obesity with 17 and 15 hidden neurons for girls and boys was designed.   After designing the network, the value of gradient on the data was 0.0021194 for girls and 0.0031658 for boys. The sensitivity, specificity and accuracy of the neural network were 0.9444, 0.9855, 0.9822, respectively in girls, and 0.9655, 0.9757, 0.9755 in boys;  in all these cases, the designed artificial neural network performed better than waist circumference and body mass index. A review of the final weights of this network showed that the input variable body mass index in girls and the input variable waist-to-height ratio in boys had the most influence in diagnosis of obesity.   Our results show that although body mass index has a better diagnostic performance in determining excess body fat than waist circumference, in boys and girls of both groups, and also in all parameters of sensitivity, specificity and accuracy, the artificial neural network acts better than body mass index and waist circumference, so that with an accuracy of more than 96%, we can detects obesity.

The present study aimed to explore the impact of green human resourcemanagement on corporate sustainability, with a focus on the function of environmentalperformance as a moderator and the perspective of sports organizations employees’empowerment in Fars province.

This research is applied in terms of purpose and correlational descriptivesurvey in terms of the data collection method. The statistical population consisted of 4047employees working at sports organizations in Fars province, and the sample size was 395utilizing the stratified sampling method, optimal allocation, and Cochran’s formula. Thestandard questionnaires of organizational resources management by Sakhavalkar and Tadani(2013), corporate sustainability by Karkolian et al., (2015), environmental performance byMadersgloo and Altanlar (2011), and Spritzer’s staff empowerment (1995) were employed toconduct the current study.

Sports management authorities approved the face and content validities of thequestionnaire prepared for this investigation. In addition, the Cronbach’s alpha methodwas used to calculate its reliability which were 96%, 46%, 68%, and 64% for green resourcemanagement, corporate sustainability, environmental performance, and empowerment,respectively. The data were statistically analyzed using structural equation modeling. Greenhuman resource standards affect the sustainability, according to the findings, with a pathcoefficient of 0.364. Environmental performance and empowerment were found to havea mediating function concerning green human resources and sustainability, with pathcoefficients of 0.476 and 0.434, respectively.

Considering green human resources by relying on environmental performanceand employee empowerment is one method of ensuring the sustainable development ofsports organizations.

The aim of this study was to design a glass ceiling management model for female employees in a case study at Shiraz University of Medical Sciences. Glass ceiling refers to artificial and invisible obstacles, organizational decisions, and prejudices of the organization's officials that prevent the progress of qualified people or minorities (especially women) within organizations. The glass ceiling in this study is defined as obstacles to women in managerial positions at Shiraz University of Medical Sciences. This is an exploratory research with a qualitative approach which was conducted through theme analysis. Its population included 15 experts in the qualitative phase, and 31 experts in the quantitative phase from Shiraz University of Medical Sciences and university professors. They were selected through forming a panel of experts for data collection. Descriptive and inferential statistics were used to analyze the data. After collecting and summarizing the data, Atlas software and SPSS16.0 were used, respectively. 67 indicators were identified. Using the experts' opinions, validity analysis (cvr) and Cronbach's alpha in the experts' panel, these indicators were reduced to 49. They were placed in 7 components including individual, group, cultural, political, regulatory, structural, procedural, and content factors. These components were categorized into three dimensions. Based on the results of this study in the behavioral dimension, the organization should divide the type of work based on physical and gender characteristics, and to consider social respect for women at the individual and group levels when defining their  jobs. In the environmental dimension, women, due to their subtlety in affairs, can act as evaluators of the organization's strategies to respond to the environment (the environment includes consumers, competitors and facilities). Also, in the organizational dimension, policymakers need to be careful when legislating, so that managers pay attention to women's power when appointing them in managerial positions and cannot destroy equal opportunities for them by violating the laws.

Internet of Things is an extensive network of interconnected objects across the world, in which each thing has a unique address. IoT is considered as the future innovation in the field of wireless technologies, which would be used in certain areas such as healthcare services, medical operations, etc. Hence, security requirements are very essential in these technologies. This study aims at finding the most effective model of IoT to improve Security for managing telemedicine. Following its widespread applicability, security have attracted a lot of attention and also have brought about some new challenges over security, confidence, and privacy areas. In this study, previous literature on how to improve the security in various layers of IoT protocol and resistance against the certain attacks in any layer for the telemedicine have been considered. Relying on previous studies made on the field of research, The Recommended Architecture of IoT for Telemedicine is the three-layer : perception, network, and application. Data Security along with how data are received completely in receivers with a minimum delay, which can influence the network, is a vital challenge one may find in telemedicine. The recommended method was RPL protocol in which telemedicine systems are used. We need to pay more attention to the connection points employed to transfer data among all things, cloud and networks over the telemedicine and make them secure as much as possible.

The infinite and increasing need for health service providers along with limited health sources has led to an increase in health costs and, consequently, the transfer of government resources from other social services to the health sector. One of the hospital services that has increased the costs in hospitals is total knee arthroplasty. Knee joint is one of the important joints of the body that is affected by various inflammatory and erosive diseases, which ultimately causes destruction of the articular cartilage and loss of proper joint function. Today, we are faced with an increasing demand for total knee arthroplasty. Knowledge of the distribution and extent of TKA provides the basis for health managers to design and implement interventions to reduce TKA surgery.

This study is a cross-sectional study. 14329 records of total knee arthroplasty patients in Iran were selected by census method in 2019-2021. The data collection tool in this study was a standard checklist. Data were analyzed by SPSS version 24 software using descriptive statistics.

The mean age of the patients was 66.1 years. 81.31% of the patients were female. 87.4% of them lived in cities, 31.5% had supplementary insurance, and most of the patients (51.9%) had undergone total knee arthroplasty in private hospitals. Discussion and

The pattern of total knee arthroplasty in our country is similar to that of other countries; most surgeries are performed in private hospitals, which may generate induced demand. TKA is more prevalent in the urban population, and most people who have had surgery do not have supplementary insurance coverage, and the northern provinces have the highest TKA;  thus, the attention of researchers and policy makers to the field of health in identifying and preventing the factors leading to knee replacement will make the demands for total knee arthroplasty reasonable.