leila ahmadian

Neonatal mortality remains a critical global challenge, with preventable instances prevailing. The initial stride in mitigating neonatal mortality involves elucidating its underlying causes.

This study utilized an umbrella review approach to discern factors associated with neonatal mortality. Five international databases, namely Pub Med, Web of Science, Scopus, CINAHL, and EMBASE, were meticu-lously searched to achieve this.

The initial search yielded 12,631 articles using a search strategy centered onkeywords related to factors contributing to neonatal mortality. Ultimately, 95 articles met the criteria incorporated into this study.

This study endeavors to identify the primary risk factors contributing to neonatal mortality. The discerned risk factors have been systematically categorized into four groups: maternal factors, neonatal factors, aspects linked to healthcare systems, and socio-economic factors. As such, it is imperative for policymakers to take heed of these identified risk factors and formulate comprehensive strategies encompassing both long-term and short-term initiatives. Effective interventions spanning various sectors are crucial for the prevention of ne-onatal mortality.

As a common disease among people of almost any age, allergic rhinitis has many adverse effects such as lowering the quality of life and efficiency at work or school. Considering these conditions and the collection of large amounts of data, the present research was conducted on allergic rhinitis and asthma patients' data to extract the common symptoms of these diseases using cluster analysis and the k-means algorithm.

The present cross-sectional research was conducted in Mashhad city. The inclusion criteria were affliction with one or two respiratory allergy diseases diagnosed by an allergy specialist through clinical history taking and physical examination. A researcher-made checklist was used in the present study for data collection. Then, the K-means algorithm's cluster analysis model was conducted to extract clusters (WEKA software (3, 6, 9)).

Overall, 1,231 patients met the inclusion criteria. The result of the Cluster analysis consisted of  1: Cluster 1 in allergic rhinitis consisted of 702 patients, and cluster 2 consisted of 382 patients. 2: 46 asthma patients were assigned to cluster 1 and 23 to cluster 2. 3: Also, 60 asthma and allergic rhinitis patients were assigned to cluster 1 and 19 to cluster 2. The most common symptoms in all patients were rhinorrhea, sneezing, nasal congestion, and itchy nose.

Overall, Salsola kali was the most common allergen in allergic rhinitis and asthma patients. Also, the most common symptoms in patients are rhinorrhea, sneezing, itchy nose, and nasal congestion. This study can help physicians diagnose allergic rhinitis and asthma in geographical areas with a high prevalence of Salsola kali.

Injury surveillance studies are essential factors in protecting the athlete's health. Minimum data set is a standard evaluation tool used during the data collection process to ensure that decision makers have access to a uniform set of information.  The purpose of this study was to create a set of minimum data to record a large number of sports injuries from community and amateur sports that can be used to develop a standard surveillance system in Iran.

The sport injuries minimum data set was developed through a four-stage process: 1. Systematic review, 2. Classification of the data elements, 3. Validation of the data elements using the Delphi technique, 4. Determination of the accessibility of data elements using focus group discussion.

A systematic review identified 1905 eligible articles that were relevant to the objectives of the study. From this number of articles 15 articles had all the inclusion and exclusion criteria and 101 data elements were subsequently extracted from these articles. The data elements were classified by five experts and validated by two rounds of a Delphi technique. The accessibility of the data elements was then evaluated during a focus group discussion. Finally, 86 data elements were selected as the minimum data set.

The proposed data set can be used as a standard tool for collecting sport injuries. This minimal data set can help information system designers to develop surveillance and registry systems.

Various training methods such as web-based training tools have been developed to achieve the potential benefits of classification systems developed by the World Health Organization (WHO). Given that users of these tools have different levels of capability, usability problems could reduce the speed and accuracy of learning among users interacting with these tools. This study aims to identify usability problems of web-based training tools under the WHO family of international classifications (WHO-FIC).

In this descriptive and cross-sectional study, ten trained evaluators independently examined WHO-FIC training tools using the heuristic evaluation method. The identified problems were classified into 10 Nielsen’s usability heuristics. Then, their average severity was calculated.

In total, 40 usability problems were identified after merging and eliminating the duplicates. The highest number of problems was related to ICD-10 training tool (n=20). The highest number of problems was related to heuristics of aesthetic and minimalist design (25.0%), and user control and freedom (17.5%). Heuristics of flexibility and efficiency of use and helping users recognize, diagnose and recover from errors had the highest average severity of problems.

Violating heuristics of aesthetic and minimalist design, user control and freedom and recognition rather than recall were among the most common problems of WHO-FIC training tools. Evaluators reported that half of the user interface problems of WHO-FIC training tools were of major and catastrophe type. Solving the usability problems of these tools could lead to ease of work, increased speed of learning and acceptance of these systems among users.

Considering the worldwide spread of the COVID-19 pandemic, it is critical to use electronic health (e-health) to prevent, diagnose, and treat this disease. According to reports on the use of e-health technology in past and present crises, this technology can have the potential to improve the quality and the quantity of provided services and control and manage diseases in epidemic conditions. The important issue is how to implement this technology fairly and facilitate the use of this technology by health care providers and the general public. Moreover, the concerns about the physician-patient relationship, patient privacy and health costs should be addressed. Therefore, it is necessary for health policymakers and planners to develop laws and guidelines to address legal and ethical barriers to the use of this technology, focusing on vulnerable populations, to manage the crisis and also determine the role of insurers in this area.

Liver cancer is the third most common cause of cancer mortality. Artificial intelligence, as a diagnostic tool, can reduce physicians’ working load. However, the main fear is that due to the existence of many causes and factors, liver diseases are not easily diagnosed. This study analyzes liver disease intelligently. Various decision tree models were used in this research.

The records of 583 patients in the North East of Andhra Pradesh, India, registered at the University of California in 2012, were collected. Decision tree models were compared by three measures of sensitivity, accuracy, and area under the ROC curve.

In this study, Decision-Stump showed better results than other models. Accuracy, sensitivity, and ROC curve of Decision-Stump were 71.3058, 1, and 0.646, respectively.

The superior model with the highest precision is the Decision-Stump model. Therefore, the Decision-Stump model is recommended for liver disease diagnosis. This paper is invaluable for the allocation of health resources for risky people.

Intensive Care Unit (ICU) has the highest mortality rate in the world. ICU has special equipment that leads to the hospital's most costly parts. The length of stay in the ICU is a special issue, and reducing this time is a practical approach. We aimed to use artificial intelligence to help early and timely diagnosis of the disease to help with health.

We designed a rule-based intelligent system to predict the length of stay and the mortality rate of trauma patients in ICU. A neuro-Fuzzy and eight machine learning models were used to predict the mortality rate in trauma patients in ICU. The performances of these techniques were evaluated with accuracy, sensitivity, specificity, and area under the ROC curve. Decision-Table was used to predict the length of stay in trauma patients in ICU. For comparison, eight machine learning models were used. The method is compared based on Mean absolute error and relative absolute error (%)

Neuro-Fuzzy expert system and Decision-Table showed better results than other techniques. Accuracy, sensitivity, specificity, and ROC Area of Nero-Fuzzy are 83.6735, 0.9744, 0.3000, 0.8379, and 1, respectively. The mean absolute error and Relative absolute error (%) of the Decision-Table model are 4.5426 and 65.4391, respectively.

Neuro-Fuzzy expert system with the highest level of accuracy and a Decision-Table with the lowest Mean absolute error, which are rule-based models, are the best models. Therefore, these models are recommended as a valuable tool for prediction parameters of ICU as well as medical decision-making.

Discharge summaries (DSs) are among the most important tools for transferring information from hospital physicians to other physicians and play an important role in the continuity of care. Low quality and lack of information are the main problems of DSs, and evaluation of their quality from the physicians' perspective in Iran has rarely been done. This study aimed to evaluate the DSs' quality of content and completeness.

This descriptive cross-sectional study was performed on the DSs of Shafa Hospital in Kerman. A valid and reliable researcher-made questionnaire (α=0.97) was used. This questionnaire had three sections, including questions related to demographic information, evaluation of the quality of DSs (8 questions), and the degree of completeness of the DSs (8 questions).

Out of 110 physicians, 98 (89%) filled out questionnaires. Completeness, awareness, continuity of care, legibility, relevancy, length, consistency, organization, and physicians’ satisfaction were below the average (50%) throughout the hospital. The highest level of physicians' satisfaction with the quality of the content (79.27%) and completeness (77.73%) was attributed to electronic discharge summaries of the neurology department. Organization, legibility, and consistency, respectively, were identified as the best predictors of physicians' satisfaction with the quality of the DSs’ content.

Policymakers should increase the quality of DSs by creating instructions, holding documentation training courses, increasing the supervision of senior physicians on interns and residents, and finally developing electronic automated DSs.

One way to reduce medication errors in the cardiovascular settings is to electronically prescribe medication through the computerized physician order entry system (CPOE). Improper design and non - compliance with users' needs are obstacles to implementing this system. Therefore, it is necessary to consider the standard mini mum data set (MDS) of this system in order to meet the basic needs of its users. The aim of this study was to introduce MDS in the cardiovascular CPOE drug system to standardize data items as well as to facilitate data sharing and integration with other sy stems.

This study was a survey study conducted in 1399 in Iran. The study population was all cardiologists in Iran. The data collection tool was a researcher - made questionnaire consisting of 33 questions. Data were analyzed in SPSS - 24 using descriptive statistics.

A total of 31 cardiologists participated in this study. The participants identified 19 of the 25 drug data items as essential for drug MDS. Five data items (Medication name, Medication dosage, Medication frequency, Medication start date and Patient medication history) were considered essential by more than 90% of the participants.

The results of this study identified drug MDS for the cardiovascular CPOE system. The results of this study can be a model for CPOE system designers to develop new systems or upgrade existing systems.

Our aim in this study was to summarize information on the use of intelligent models for predicti ng and diagnosing the Coronavirus disease 2019 (COVID - 19) to help early and timely diagnosis of the disease.

A systematic literature search included articles published until 20 April 2020 in PubMed, Web of Science, IEEE, ProQuest, Sco pus, bioRxiv, and medRxiv databases. The search strategy consisted of two groups of keywords: A) Novel coronavirus, B) Machine learning. Two reviewers independently assessed original papers to determine eligibility for inclusion in this review. Studies wer e critically reviewed for risk of bias using p rediction model r isk of b ias a ssessment t ool.

We gathered 1650 articles through database searches. After the full - text assessment 31 articles were included. Neural n etworks and d eep n eural n etwork vari ants were the most popular machine learning type. Of the five models that authors claimed were externally validated, we considered external validation only for four of them. Area u nder the c urve (AUC) in internal validation of prognostic models varied from .94 to .97. AUC in diagnostic models varied from 0 .84 to 0 .99, and AUC in external validation of diagnostic models varied from 0 .73 to 0 .94. Our analysis finds all but two studies have a high risk of bias due to various reasons like a low number of partic ipants and lack of external validation.

Diagnostic and prognostic models for COVID - 19 show good to excellent discriminative performance. However, these models are at high risk of bias because of various reasons like a low number of participants and lack of external validation. Future studies should address these concerns. Sharing data and experiences for the development, validation, and updating of COVID - 19 related prediction models is needed

Glycopeptide resistance genes can be transmitted to clinical strains from gram-positive environmental bacteria and the normal flora. The aim of this study was to evaluate the prevalence of vancomycin and teicoplanin-resistant Enterococcus faecalis and Enterococcus faecium isolates in hospital environment and fecal samples of healthy individuals.

Human stool and hospital environment samples were collected and inoculated on selective M-enterococcus agar medium. Then, E. faecalis and E. faecium were identified using phenotypic and molecular methods. Antibiotic susceptibility pattern of the isolates against teicoplanin and vancomycin was determined by micro-broth dilution method. Data were analyzed in SPSS applying Chi-square test.

From 145 isolates, E. faecalis and E. faecium were detected in 84 (54.93%) and 61 (42.07%) isolates, respectively. One (1.19%) E. faecalis isolate and 4 (6.56%) E. faecium isolates were resistant to vancomycin, while 4 (6.56%) E. faecium isolates were found to be resistant to teicoplanin. The minimum inhibitory concentrations of 50 (MIC50) and 90 (MIC90) for vancomycin and teicoplanin in E. faecalis and E. faecium were 4 and 16 μg/ml, respectively.

The MIC results of vancomycin and teicoplanin showed that most of enterococci isolates studied were sensitive to these two antibiotics. Therefore, their use should be closely monitored to prevent resistance.

In peer teaching, students act as both teachers and learners. Peer teaching can be a useful way to learn courses in interdisciplinary fields of study.

The purpose of this study was to investigate the viewpoint of health information technology students about learning through peer teaching.

This cross-sectional study was conducted in 2017 at Kerman University of Medical Sciences. Undergraduate students in the health information technology department using the peer teaching method participated. Data were collected using a self-administered questionnaire. The questionnaire consisting of 42 questions assesses students' attitudes toward peer teaching. It consisted of two categories: "learning improvement" and "students' satisfaction with the peer teaching." Data were analyzed using SPSS software.

A total of 52 students participated in the study. Regarding learning improvement, the mean score of development of individual skills, improvement of students' learning, and improvement of peer performance were 3.43 ±1.05, 3.34 ±1.08, and 3.37 ±1.03, respectively. In terms of student satisfaction the mean score of interaction between learner and teacher, knowledge transferred to the student, and the class conditions were 3.52 ±1.10, 3.31 ±1.09, and 3.21 ±1.15, respectively. Students who attended more in peer classes were more satisfied and their learning improved (P<0.05). There was no significant relationship between age, gender, and the number of passed semesters with students' satisfaction and learning (P>0.05).

From the students' point of view, peer teaching can improve their learning. Also, the students were satisfied with the training provided by their peers. Peer teaching can be a complement to the teacher-centered method by providing a positive experience.

Nowadays, widespread use of automated teller machines (ATMs), has increased the possibility of contamination of hands due to contact with the surfaces of these devices. This study aimed to investigate the prevalence of bacterial contamination and antibiotic resistance pattern of the isolated bacteria from the keyboard of these devices in Sari, north of Iran.

In this descriptive-analytic study, the keyboards of 200 ATMs were sampled by sterile swab and transferred to the laboratory. The samples were inoculated in TSB medium and, after 24 hours of incubation at 37 ° C, were cultured on specific solid media and incubated. Then, the isolated bacteria were identified and their antibiotic resistance pattern was examined by disk agar diffusion method.

Bacterial contamination was observed in 97% of the samples. Klebsiella pneumoniae was the most frequent identified bacteria (36.08%), while Bacillus cereus was the least frequent bacteria (1.54%). K. pneumoniae showed a high resistance rate against Tetracycline (91.42%) and a low resistance rate towards Imipenem (2.85%).

Regular disinfection of ATM keyboards has a significant role in reducing and controlling bacterial contamination. Also, due to increased antibiotic resistance of isolated bacteria, it is possible to combat this problem by precise monitoring on the performance of antimicrobial stewardship programs.

The implementation of different reimbursement methods has various positive and negative effects on the health system of different countries. Identifying the challenges of these methods is essential to improve these reimbursement methods and modify them if required. This article aimed to qualitatively assess the challenges of current hospitals' payment systems in the Iranian health system and determine the required solutions for modifying these payment systems.

This qualitative study was conducted in 2019. Semi-structured interviews were conducted recruiting 20 experts including operational, middle and top managers working in three different levels of health systems. Data collection was continued until it reached a saturation point. MAXQDA 10 was used for data analysis. The data content analysis method was used to analyze the data and the themes and categories were determined.

The challenges of the payment systems were categorized into four main themes regarding policy, cost, regulatory and functional challenges, and 15 sub-themes. The findings related to the proposed strategies were presented in six main themes consisting of legal solutions, structural reform, cost, quality improvement, service provider and client, and monitoring and evaluation; and 12 sub-themes.

This study showed that the health systems in Iran face various structural and procedural challenges in terms of reimbursement mechanisms. Therefore, it is recommended that policymakers pay attention to these challenges before making any changes. Using hybrid payment systems can be one of the proper solutions.

Speech recognition (SR) technology has been existing for more than two decades. But, it has been rarely used in health care institutions and not applied uniformly in all the clinical domains. The aim of this study was to investigate the accuracy of speech recognition system in four different situations in the real environment of health services. We also report physicians' experience of using speech recognition technology.

To do this study, NEVISA SR software professional v.3 was installed on the computers of expert physicians. The pre-designated medical report was tested by the physicians in four different modes including slow expression in a silent environment, slow expression in crowded environments, rapid expression in a silent environment and rapid expression in a busy environment. After using the speech recognition software by 15 physicians in hospitals, a designed questionnaire was distributed among them.

The results showed that the highest average accuracy of speech recognition software was in the silent environment by slow expression and the minimum average accuracy was in the busy environment by rapid expression. Of all the participants in the study, 53.3% of the physicians believed that the use of speech recognition system promoted the workflow.

We found that software accuracy was generally higher than the expectation and its use required to upgrade the system and its operation. In order to achieve the highest level of recognition rate and error reduction by speech recognition, influential factors such as environmental noise, type of software or hardware, training and experience of participants can be also considered.

The online social networks as new and widespread sources of information have been able to facilitate the accessibility of people to health information. The aim of this study was to determine the use of online social networks and their role in sharing health information among pregnant women.

This descriptive-analytical study was conducted in Kerman in the winter of 2017. The study participants were the pregnant women referring to 21 gynecologists’ private offices in Kerman city. Data were collected by a researcher-made questionnaire. The validity of this questionnaire was confirmed by 4 medical informatics and health information management specialists, and its reliability (71%) was estimated with Cronbach's alpha. Data were analyzed by SPSS using descriptive statistics and analytical tests.

In general, 89% of pregnant women used online social networks and more than 80% of them used it daily. Moreover, more than 57% used these networks for the related information about health and pregnancy period care, and almost 68% of pregnant women considered these networks useful.

This study showed the widespread use of online social networks among pregnant women in Kerman city. If accurate and trustworthy information bits were shared in such networks, they could provide an appropriate platform to improve the awareness, knowledge and health literacy of pregnant woman, and facilitate the exchange of information and experience among them.

The aminoglycoside modifying enzymes (AMEs) and class 1 integrons in clinical isolates of pseudomonas aeruginosa are the major factors leading to rapid spread of antibiotic resistance. The aim of the present study was to investigate the frequency of aac(6)-IIa, ant(2'')-Ia, and class 1 integrons in clinical isolates of pseudomonas aeruginosa.

For this descriptive-analytic study (2017-2018), 100 clinical isolates of pseudomonas aeruginosa were collected from Sari teaching hospitals and identified by differential diagnostic tests. Antibiotic susceptibility pattern of all isolates against selected antibiotics was evaluated using standard disk agar diffusion method. Subsequently, all isolates were evaluated for the presence of aac (6) -IIa, ant (2'') -Ia genes, and class I integrons using PCR method.

Out of 100 pseudomonas aeruginosa clinical isolates, 28%, 42%, and 39% were resistant to amikacin, gentamicin, and tobramycin, respectively, while 26 isolates were resistant to all three antibiotics. The results of PCR showed that 42% of the clinical isolates contained class 1 integrons. The prevalence of aac (6) -IIa and ant (2 '') - Ia genes in aminoglycoside resistant isolates was 41.8% and 13.9%, respectively.

Aminoglycosides are the preferred drug for the combined treatment of infections caused by Pseudomonas aeruginosa and the prevalence of resistance to them is also high, so the intermittent examination of the susceptibility pattern of these antibiotics and the genes associated with this issue is necessary to prevent the prevalence of high levels of resistance in this bacterium.

The acquisition of knowledge by parents of children with asthma plays an important role in the treatment of children. Thus, it is important to understand their needs and provide this information through available methods such as a website.The aim of this studywas to determine the content of a pediatric asthma website based on the evaluation of parents information needs.
This cross-sectional studywas conducted by a descriptive-analytical approach in Kerman, Iran. Data were collected using a semi-structured questionnaire.The questionnaire was distributed among a sample of 300 parents visiting allergy and asthma specialists’ offices. Three experts confirmed validity of the questionnaire. The reliability of the questionnairewas confirmed using the test- retest method on 40 participants (r = 0.82). Data were analyzed using descriptive and analytical statistics by SPSS version 20.0 software.
Participants demanded information concerning asthma nutrition (79.0%), prevention (78.1%), treatment (77.1%), medications (72.4%) as well as general information (71.4%) and information about etiology of the disease (70.5%), respectively. The results showed that the fathers use the Internet significantly more than the mothers (p=0.0001). There was a statistically significant relationship between participants’ educational level and the type of resources they use to obtain information (P This study highlighted the most important information needs of parents of children with asthma. The results indicated that most parents have access to the Internet and prefer to get their required asthma information from it.Therefore, providing required information to parents through a website can offer them the opportunity to increase their corresponding level of knowledge and skills.

Gastric cancer is one of the most common cancers all over the world and is the world's second fatal cancer. This study was done to identify the epidemiological features and risk factors of gastric cancer in different regions of Birjand. Such study can be an effective step in preventing, controlling and curing the diseases.
This descriptive-analytical study was conducted in Birjand educational hospitals. All patients with gastric cancer who were hospitalized in the period 2006-2011 in educational hospitals were recruited through census. Data were collected using researcher-made checklist through examining medical record of patient. Data were analyzed using descriptive and analytical statistics by SPSS software. Ethical approval was received from the Birjand University of Medical Sciences.
Results of this study showed that villages around Ghaien had the highest rate of gastric cancer (n=14, 12.6%). In this study, the relationship between histopathology with therapeutic interventions (P=0.006) and diagnostic methods (P=0.005) was significant. In addition, there was a significant relationship between the place of residence (P=0.018) and the type of therapeutic interventions.
Findings of this study depicted an accurate and complete image of the epidemiology of this cancer in the region and provided authorities with valuable findings to make decisions about the identification of risk factors of gastric cancer in order to reduce cancer rates. It can also be an alarm for the villagers to change their habits and diet and to have a healthy life.

Health knowledge acquisition, training, and controlling of risk factors of cardiovascular disease (CVD) can not only reduce healthcare costs, but can also improve the quality of life (QOL) of patients and help prevent re-hospitalization. The purpose of this research was to evaluate heart patients’ point of view on health knowledge acquisition and its role in the treatment process.
This descriptive-analytical study was carried out on 200 patients with CVD. Data were collected using a questionnaire the validity and reliability of which were, respectively, confirmed by experts and by means of test-retest (20, 0.82). Data were analyzed using descriptive (frequency and percentage) and analytical statistics (chi-squared test and marginal independence).
After the diagnosis of heart disease, 80.5% of patients had tried to enhance their knowledge about their disease. To increase their knowledge, all of them (161 individuals) used the physician as a source of knowledge acquisition. Overall, 146 (90.7%) patients had acquired knowledge regarding the causes of the disease. A small percentage of the patients believed that educational CDs could help improve their knowledge.
The results of this study can be used to plan for the improvement of health knowledge among patients. Determining the most common sources of knowledge acquisition can help in the provision of knowledge through these sources. This can also clarify the reasons for the lack of use of other sources.

Among all cancers, colon cancer is common and deadly, yet preventable. The estimated worldwide incidence of colon cancer is more than one million new cases per year. This study was done to identify the epidemiological features and risk factors of colon cancer in different regions of Birjand.
This retrospective, descriptive analytical study of patients with colon cancer was conducted in Birjand educational hospitals. This study examined the patients whose colon cancers had been confirmed by a pathologist (2006-11). Statistics related to these patients were collected from pathology centers affiliated to Birjand University of Medical Sciences. Data were analyzed using descriptive (frequency and relative frequency) and analytical (chi square test) statistics. SPSS software was used to analyze the collected data.
Results of the present research showed that a total of 38 people with colon cancer were hospitalized in Birjand educational hospitals between 2006 and 2011. In the present study, there was a significant difference between the patients’ job and the type of morphology (P=0.018) and the therapeutic procedures (P=0.001); Adenocarcinoma was mainly reported among housewives (n=10, 76.9%). Concerning therapeutic procedures, housewives underwent colectomy surgery more than other groups (n=8, 61.5%).
Controlling colon cancer which is one of the most common cancers in the world is a great epidemiologic success. The findings of this study presented a complete and exact image of epidemiology of this cancer in the region and provided the authorities with precious information; therefore, they can make decisions about identifying colon cancer risk factors in the region.

Geographic information system is a modern technology that helps to make sound policy and decisions to promote patients’ health. This systematic review was carried out to determine the application of GISs in health in Iran.
Material & In the current study, English and Persian databases were systematically searched using predefined key terms. All relevant studies utilizing GISs in the field of health in Iran were retrieved. Then, a data extraction form that its reliability was approved by experts was applied to extract the data. Data regarding GIS capabilities, the sources of data used, and the fields that GISs were applied for were extracted from the papers. Data were analyzed and reported using descriptive statistics.
Totally, 33 out of 119 retrieved articles were selected as eligible and reviewed by the authors. The subject area of almost half of the studies was noninfectious diseases. Cancer (21%) was the most common disease analyzed by GIS in Iran. Eighty-five percent of the studies used mapping and locating capabilities of GIS software.
The use of GIS in health in Iran is still in the preliminary stage. GIS as an applied software is considered as a valuable tool to present geographical distribution of diseases and produce geospatial data to improve health and health care systems.

Aims: Satisfaction of educational field is one of the important factors in the education and students success. One of the influencing factors in students satisfaction, is educational curriculumn. Medical records and health information technology fields have similarities with each other in terms of educational curriculum. Therefore, the aim of this study was to compare medical records and health information technology students’ satisfaction from their educational field.
In this cross-sectional study, the study population included all students of medical records and health information technology at Kerman University of Medical Sciences in 2013. Data collection tool was a questionnaire with 20 questions that its validity confirmed by expert consensus and its reliability confirmed by test-retest (α=95.7% ,P-value= 0.01) . The collected data were analyzed using descriptive and analytical statistics in SPSS 20 software.
The mean of satisfaction score to educational field among students of medical records was 4.23 and among health information technology students was 4.08 which was less than acceptable level. The results showed that there was a significant relationship between sex and working status, and knowledge about the field.
The majority of students in two fields had not acceptable attitude and satisfaction regarding their educational field. Medical records and Health Information Technology students had not high knowledge about the content of curriculum, when choosing their educational field and majority of them had chosen their educational field without cognition.

Numerous studies have evaluated health information systems in Iran, but most studies have not ýfollowed a standard format for reporting their findings. The objective of this study was to ýevaluate the compliance of health information systems’ evaluations published in Persian journals ýwith the Statement on Reporting of Evaluation Studies in Health Informatics (STARE-HI).
This was a review study in which papers reporting on evaluation of health information systems ýwere assessed in terms of 51 principles of the STARE-HI using a checklist. These papers were ýretrieved from the Persian databases of Magiran, IranMedex, and SID using appropriate ýkeywords. Data were classified and reported based on 13 main sections of the STARE-HI.
From the 727 retrieved papers, 36 were relevant to the study objectives. All paper had an ýintroduction section, but none of the paper had the authors’ contribution and conflict of interests ýsections. The mean compliance of articles with the STARE-HI was 71.4%, with the lowest being ýý52.94% and the highest being 82.35%.
The writing style and structure of studies evaluating health information systems require ýimprovementsþ.þý The quality of study reports can be improved through reporting essential ýinformation in articles and using corresponding guidelines in the design of authors’ instruction ýsections of journals. Improving the reporting format of papers can result in better and higher rate ýof application of study results and increased citation of articles.

Considering the importance of accurate documentation in psychiatric history and mental assessment and its effect on the current and future treatment among patients, this study aimed to determine data elements in the psychiatric history and mental assessment forms.
This is a descriptive-comparative study. Using psychiatric history and assessment forms, the required data were gathered in this study. Finally, all psychiatric history and mental assessment forms gathered from the selected countries including the United States (n=9), Australia (n=1), France (n=1), Iran (n=2) were assessed. After preparing the comparative tables, a comprehensive list of data elements related to the psychiatric history and assessment was provided. Using bottom up approach the extracted data elements were categorized.
In total, 58 data elements including demographic data, patient history, current symptoms of disease, evaluation of psychological states, suicide risk assessment, behavioral/emotional conditions, thinking process, drug abuse assessment, family safety/violence assessment, multi-axial diagnosis and treatment type/plan were extracted from psychiatric history and assessment forms.
The present study provides a general view of important data elements considered for documentation in psychiatric history and assessment forms.