مقالات رزومه محسن سلیمانی

Stroke is the second leading cause of mortality and the third leading cause of morbidity worldwide. This study aimed to examine the spatial-temporal distribution of stroke in rural districts, Zanjan Province, Iran.

This cross-sectional study was conducted at Zanjan University of Medical Sciences (ZUMS). Patients with a discharge diagnosis of stroke (the ICD-10 code of I64), hospitalized during 2012-2019 at ZUMS hospitals, were selected as the study sample. Spatial statistical tools, autocorrelation Moran’s I, high-low clustering analysis, and hot spot analysis were used for spatial data analysis. ArcGIS 10.7, R 3.6.0, and RStudio 1.2.1335 software packages were used to analyze the data.

During 2012-2019, 8404 stroke cases were hospitalized at ZUMS hospitals, with an incidence of 697 patients per 100 000 people. Men had a higher rate of stroke incidence (52.06%) compared with women (47.94%). The mean age of patients was 69.3±14.7 years; the mean length of stay was 158.8±270 hours. In the study area, 4 significantly hot spot areas and 4 low-high outliers of stroke were found.

This study showed a high incidence of stroke in Zanjan Province, Iran, from 2012 to 2019. Identifying high-risk areas of stroke is a warning to healthcare authorities and policymakers to focus on major risk factors. It can help to figure out the possible causes of stroke and implement prevention programs to reduce stroke incidence in these areas.

There is a significant relationship between the appropriate treatment plans and accurate medical diagnosis. Admission and discharge diagnoses in hospitals are often different and this has significant implications on patient care and safety. The aim of this study was to explore  the discrepancies between the admission diagnosis and the discharge diagnosis.
This was a longitudinal study conducted at Zanjan University of Medical Sciences (ZUMS). The study sample included admitted patients in hospitals during 2012-2019. The ICD-10 codes between I00 and I99 were selected as Cardiovascular Diseases. Data analysis was conducted by R (v3.6.0) and Rstudio (v1.2.1335) software. Agreement analysis was conducted by Cohen’s Kappa statistics, and Chi Square statistic was used for examining the relationships between categorical variables.
Agreement analysis of cardiovascular diseases subgroups showed that the values of Kappa coefficient range were varied between κ = 0.34 for Chronic rheumatic heart diseases and κ = 0.93 for Acute rheumatic fever diseases. The values of the Kappa coefficient for the 10 most common ICD-10 codes were in the range from κ = 0. 44 for I25.9 to κ = 0. 77 for I80.2.
The results of this study showed that there was a significant difference between ADx and DDx, and the values of kappa coefficient were not the same between CVDs subgroups. There are definite needs for improvement on diagnostic accuracy, especially in regard to CVDs cases with acute condition.

Cardiovascular diseases (CVDs) are the most common chronic diseases and the leading cause of death in the world and in Iran. The aim of this study was to explore the geographical epidemiology of CVDs in the province of Zanjan, Iran.

 This cross-sectional study was carried out at Zanjan University of Medical Sciences. Patients with adischarge diagnosis of CVDs (I00-I99 group of ICD-10 codes) who were hospitalized from 2012-2019 were selected as a study sample. All spatial analyses were performed in ArcGIS 10.7, and descriptive analysis was conducted by R (v3.6.0) and RStudio (v1.2.1335) software.

 The ischemic heart disease subgroup accounted for the majority of CVD cases (43.8%), while acute rheumatic fever (0.03%) was the least common contributor to CVD. Men had a higher rate of CVD (53.1%) than women (46.9%). The mean age of all CVD subgroups was 56.88 years, and the mean length of stay of all CVD subgroups was 114.2 hours. Zanjan city (57.4%) had the greatest incidence rate of CVDs in Zanjan province, Iran.

 Geographical epidemiology studies can identify the pattern of CVD distribution in different areas and can be helpful in preventing CVDs. A spatial-temporal pattern of CVD distribution provides crucial information for health development planning in Iran. The findings of this study provide useful information for health authorities in Zanjan, Iran, to plan CVD prevention programs.

Health Information Technology (HIT) has the potential for improving the quality, safety, and efficiency of healthcare and nurses are the largest group of HIT users.

Therefore, the present study mainly aimed to investigate the use of HIT by nurses in healthcare.

This cross-sectional and descriptive-analytical study was conducted in four educational and treatment centers of Zanjan University of Medical Sciences in 2019. A researcher-made questionnaire was used for data collection, the validity and reliability of which were confirmed by experts’ approval and Cronbach’s test (0.84). Eventually, the data were analyzed by R and Rstudio statistical Software, and Chi-square test was used to examine the relationship between the variables.

The most commonly used HITs among nurses were the hospital information system (100%), picture archiving and communication system (83.2%), as well as tele-nursing (76%) and mobile-health (64.9%). However, none of the nurses used a radio frequency identification system (0%) in nursing care.

The findings of this study revealed that although the application of HITs presents potential benefits in improving healthcare quality, their features are not used completely in nursing care