mohamadkarim bahadori

The unit dose distribution system ensures the delivery of drugs from the hospital pharmacy to the ward for a specific patient. Facilitating the improvement process of patients and drug safety requires such research. However, two human factors affecting this process, including pharmacists and nurses, and the impact that the drug distribution system in the hospital has on their condition, have been studied as the purpose of this research.

This study was done by descriptive and analytical-comparative method. Data were collected from the staff of Urmia Women's Hospital in 2021, including 76 hospital staff, 11 pharmacists, and 32 nurses as a sample from three groups using three standard questionnaires. Data were analyzed by two dependent samples T-tests in SPSS-24 software.

Attention to pharmacists in the implementation of the unit-dose system by stimulating their interest in pharmaceutical sciences, being in the center of attention of colleagues, and increasing their desire to work in the hospital changed the level of job identity and, thus, it explained their appropriate professional position. Time saving, lack of differences in the counting of drugs, and the peace of mind of nurses after the implementation of the unit-dose plan increased the role of nurses in the main task of patient care by obtaining job satisfaction (3.29), which increased to above the average level ( P<0.001).

Success in the implementation of this project in the selected hospital is expected to improve the professional position of pharmacists in the hospital and increase the job satisfaction of nurses.

To assess prevalence and predictive factors for Nosocomial Infection (NI) in the military hospitals.

PubMed, Scopus, Cochrane and PreQuest databases were systematically searched for studies published between Jan 1991 and Oct 2017 that reported the prevalence of NI and predictive factors among military hospitals. We performed the meta-analysis using a random effects model. Subgroup analysis was done for heterogeneity and the Egger test to funnel plots was used to assess publication bias.

Twenty-eight studies with 250,374 patients were evaluated in meta-analysis. The overall pooled estimate of the prevalence of NI was 8% (95% 6.0–9.0). The pooled prevalence was 2% (95% CI: 2.0–3.0) when we did sensitivity analysis and excluding a study. The prevalence was highest in burn unit (32%) and ICU (15%). Reported risk factors for NI included gender (male vs female, OR: 1.45), age (Age≥65, OR: 2.4), diabetes mellitus (OR: 2.32), inappropriate use of antibiotics (OR: 2.35), received mechanical support (OR: 2.81), co-morbidities (OR: 2.97), admitted into the ICU (OR: 2.26), smoking (OR: 1.36) and BMI (OR: 1.09)

The review revealed a difference of prevalence in military hospitals with other hospitals and shows a high prevalence of NI in burn units. Therefore careful disinfection and strict procedures of infection control are necessary in places that serve immunosuppressed individuals such as burn patient. Moreover, a vision for the improvement of reports and studies in military hospitals to report the rate of these infections are necessary.

The present study is on the development of a data mining algorithm for finding the influential factors on the hospitalization of patients subject to chronic obstructive pulmonary disease.

This is a descriptive analytical study conducted cross sectionally in 2017 on a research community of 150 people with disease symptoms referred to clinics and hospitals across Tehran (Iran). The people were surveyed by a self-designed questionnaire, including queries on life style and family information. The sampling was simple intuitive from previously published studies. The modeling of the data was based on the CRISP method. The C5 decision tree algorithm was used and the data was analyzed by RapidMiner software.

The common symptoms of the patients were found to be shortness of breath, cough, chest pain, sputum, continuous cold, and cyanogens. Besides, the family history, smoking, and exposure to allergic agents were other influential factors on the disease. After accomplishment of this study, the results were consulted with the experts of the field.

It is concluded that data mining can be applied for excavation of knowledge from the gathered data and for determination of the effective factors on patient conditions. Accordingly, this model can successfully predict the disease status of any patient from its symptoms.

Transformation in universities is a necessity in the path of community development. Due to a large number of students and the need to think about ways to facilitate their employment, this study aimed to develop an entrepreneurial university model at Islamic Azad University of Medical Sciences.

This study was qualitative-quantitative. In the qualitative section, ten experts in entrepreneurship in Islamic Azad University participated in semi-structured interviews. The content analysis method was used to analyze semi-structured interviews. Then, with the Maxqda software, the concepts were extracted from the interviews and the primary and sub-variables were obtained. In the quantitative section after extraction of final variables from qualitative analysis of interviews, the fuzzy Delphi method was used to survey the identified variables and select the final variables. For this purpose, several experts were confidentially sent the “Fuzzy Delphi Questionnaire” containing the criteria. Criteria with a mean score of less than seven were omitted. Fuzzy Delphi method calculations were performed by coding in the Matlab environment.

According to the experts' viewpoint, the entrepreneurship university model of Islamic Azad University of Medical Sciences was developed with two main variables including software factors (including six sub-variables) and hardware factors (including six sub-variables).

The Entrepreneurship University model of Islamic Azad University of Medical Sciences was developed with two main variables including software and hardware factors. Therefore, it is suggested that this model be used to provide the necessary infrastructure for university entrepreneurship.

The achieve uses 7 variables: ability; clarity; help; incentive; evaluation; validity; and environment, to provide leaders and staffs with the necessary tools to improve performance, and help managers to determine cause of performance problem. And create change strategy for solving those problems. We try to determine factors affecting the performance of nurses, base on this model in selected hospital of Isfahan (Iran).

This was a descriptive‑correlation survey. The population of study was 85 nurses of 9 hospitals in Esfahan. Data gathering was done via achieve questionnaire. Reliability was calculated by Cronbach’s alpha (r = 0.85). Data analysis was done by using SPSS 16.

The ability and help variables were the most important factors in improving performance of nurses and validity and evaluation were less important.

Today, staff effectiveness is one of the important problems in health care organization. In fact, performance improvement is the most important step for organization improvement.