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Abstract Breast cancer is one of the most prevalent cancers with an increasing trend in both incidence and mortality rates in Iran. Survival analysis is a pivotal measure in setting appropriate care plans. To the best of our knowledge, this study is pioneering in Iran, introducing a multi-method approach using a Deep Neural Network (DNN) and 11 conventional machine learning (ML) methods to predict the 5 year survival of women with breast cancer. Supplying data from two centers comprising a total of 2644 records and incorporating external validation further distinguishes the study. Thirty-four features were selected based on a literature review and common variables in both datasets. Feature selection was also performed using a p value criterion (

ABSTRACT Background The utilization of mobile application in postoperative care for breast cancer patients has seen a significant rise in recent years. This study aimed to synthesize the literature to identify the features of breast cancer postoperative care mobile applications. Methods This scoping review was conducted using the framework developed by Arksey and O'Malley. All articles published from inception until July 25, 2024, were searched in the PubMed, Scopus, Web of Science, IEEE, and Cochrane databases. The quality of publications was evaluated using the mixed‐methods appraisal tool (MMAT). Results A total of 999 publications were found, of which 28 studies were considered in this review. Out of these studies, 14 used native apps, 14 used hybrid apps. Nine features were used in applications, and Tracker, Tailored Education, and Community Forum were the most repetitive features. In five studies, various devices and sensors, like Bluetooth and GPS, were utilized in mobile applications to monitor physical activity, stress levels, heart rate, sleep patterns, and calorie intake. Conclusions Mobile applications for postoperative breast cancer care encompass a range of features. In a co‐design approach, understanding patients' required features could help to develop usable applications to improve the postoperative care for breast cancer patients.

Abstract Background Adolescence is a critical stage for the development of self-care. Many adolescents use mobile apps to monitor and improve their health. Health information technology plays a significant role in the field of self-care. This article provides a protocol for a study to design and evaluate mobile applications for adolescent self-care. Methods The present research is a combination of applied development study, methodological, and intervention experimental. This study will be done in three stages: The first stage is the design and evaluation of a mobile application for adolescent self-care. The second stage is, designing and evaluating the psychometric properties of the “Questionnaire for Measuring Adolescent Self-Care Performance.” This questionnaire will be used before and after using the application in the third stage. The third stage is determining the effectiveness of self-care interventions based on mobile applications among adolescents. The target group will be adolescents aged 10–19 from the schools of Amol City. In the first stage, the opinions of 30 people adolescents, parents, and experts will be used. In the second stage, the number of samples will be 10 times the number of items in the questionnaire. In the third stage, 50 people will be in the intervention group and 50 people will be in the control group. Descriptive statistics will be used for data analysis. Between-group and intra-group comparisons will be calculated about quantitative variables, independent t-test and paired t-test, and analysis of variance. The chi-square test and Fisher’s exact test will be used in SPSS 16 software to test the homogeneity of qualitative variables between the two groups. Discussion In the first stage, based on the opinions received from the target group, a user-centered educational application for self-care of adolescents will be designed. In the second stage, after determining the validity and reliability, a questionnaire will be designed to measure the self-care performance of adolescents. In the third stage, using an intervention study for 3 months, the effectiveness of the training will be determined through the designed application. Our findings are scheduled for a full analysis, with expectations that analyses will be completed by September 2023.

Abstract Background Mobile phones can be an ideal platform to engage adolescents to maintain, improve, and promote self-care. Therefore, the current study aims to design and evaluate the usability of a mobile application for self-care in adolescents with a user-centered approach. Methods The current applied developmental study was done in four steps. The first step, polling and examining opinions was conducted through in-depth semi-structured interviews, with the aim of user-centered mobile application design with the involvement of 30 participants. The second step, extracting and compiling the educational content related to the main themes of the self-care app, was obtained from national and international guidelines and instructions, including the World Health Organization, the Center for Disease Control and Prevention, the Ministry of Health and Medical Education, etc. In the third step, the initial version of the mobile application was developed. In the fourth step, app usability was evaluated by 30 participants from the target group, 2 weeks after using the app, using the MAUQ questionnaire. Results In the first step, 789 codes, 12 sub-categories, and 3 categories were extracted. These codes were used in the design of the mobile application. In the second step, educational information was prepared and arranged in 5 sections (physical activity, nutrition, personal hygiene, risky behaviors and safety and events) in the form of text, images and short videos. In the third step, the mobile application was designed based on step 1 and 2. This application operates in online mode and under the Android operating system. the initial version of the mobile application was developed using JavaScript and Typescript programming languages in a Visual Studio Code environment. In the fourth step, the participants the overall level of usability of the application as very good with an average of 6.28 ± 0.55. The highest average score was given to the user interface and satisfaction with an average score of 6.43 ± 0.58. Conclusions The "My-Care" app is a collaboratively designed smartphone app for adolescents that targets 5 dimensions of physical self-care. This app has the potential to teach, assess, and promote self-care among adolescents.

Abstract Background Public Health Dashboards (PHDs) facilitate the monitoring and prediction of disease outbreaks by continuously monitoring the health status of the community. This study aimed to identify design principles and determinants for developing public health surveillance dashboards. Methodology This scoping review is based on Arksey and O'Malley's framework as included in JBI guidance. Four databases were used to review and present the proposed principles of designing PHDs: IEEE, PubMed, Web of Science, and Scopus. We considered articles published between January 1, 2010 and November 30, 2022. The final search of articles was done on November 30, 2022. Only articles in the English language were included. Qualitative synthesis and trend analysis were conducted. Results Findings from sixty-seven articles out of 543 retrieved articles, which were eligible for analysis, indicate that most of the dashboards designed from 2020 onwards were at the national level for managing and monitoring COVID-19. Design principles for the public health dashboard were presented in five groups, i.e., considering aim and target users, appropriate content, interface, data analysis and presentation types, and infrastructure. Conclusion Effective and efficient use of dashboards in public health surveillance requires implementing design principles to improve the functionality of these systems in monitoring and decision-making. Considering user requirements, developing a robust infrastructure for improving data accessibility, developing, and applying Key Performance Indicators (KPIs) for data processing and reporting purposes, and designing interactive and intuitive interfaces are key for successful design and development.

Abstract This study aimed to design an end-to-end deep learning model for estimating the value of fractional flow reserve (FFR) using angiography images to classify left anterior descending (LAD) branch angiography images with average stenosis between 50 and 70% into two categories: FFR > 80 and FFR ≤ 80. In this study 3625 images were extracted from 41 patients’ angiography films. Nine pre-trained convolutional neural networks (CNN), including DenseNet121, InceptionResNetV2, VGG16, VGG19, ResNet50V2, Xception, MobileNetV3Large, DenseNet201, and DenseNet169, were used to extract the features of images. DenseNet169 indicated higher performance compared to other networks. AUC, Accuracy, Sensitivity, Specificity, Precision, and F1-score of the proposed DenseNet169 network were 0.81, 0.81, 0.86, 0.75, 0.82, and 0.84, respectively. The deep learning-based method proposed in this study can non-invasively and consistently estimate FFR from angiographic images, offering significant clinical potential for diagnosing and treating coronary artery disease by combining anatomical and physiological parameters.

Abstract Background Data management related to COVID-19 vaccination in pregnant women is vital to improve the treatment process and to establish preventive programs. Implementing a registry to manage data is an essential part of this process. This study aims to design a national model of the COVID-19 vaccination registry for pregnant women in Iran. Methods The present study is an applied descriptive study conducted in 2021 and 2022 in two stages. In the first stage, the coordinates of the National Registry of COVID-19 vaccination of pregnant women from related references and articles, as well as the comparative study of the National Registry of COVID-19 vaccination of pregnant women in the United States, Canada, and the United Kingdom was done. In the second stage, the preliminary model was designed. The model was validated using the Delphi technique and questionnaire tools and analyzing the data. Results The presented national COVID-19 vaccination registry model of pregnant women’s main components consist of objectives, data sources, structure, minimum data set, standards, and registry processes, all of which received 100% expert consensus. Conclusion The vaccination registry of pregnant women has a major role in managing COVID-19 vaccination data of pregnant women and can be one of the Ministry of Health and Medical Education priorities.

Abstract Background Reduced or absence of melanin poses physical, social, and psychological challenges to individuals with albinism. Mobile health (mHealth) applications have the potential to improve the accessibility of information and services while reducing time and costs. This study aimed to develop and evaluate a mHealth application for self-management of albinism. Methods This applied study was conducted in two stages (development and evaluation) in 2022. Initially, the functional requirements were determined, and the conceptual model of the application was then developed using Microsoft Visio 2021. In the second phase, the application was evaluated using the Mobile Application Usability Questionnaire (MAUQ) involving patients with albinism to reflect their views on the usability of the application. Results The key capabilities of the application included: reminders, alerts, educational content, useful links, storage and exchange of images of skin lesions, specialist finder, and notifications for albinism-relevant events. Twenty-one users with albinism participated in the usability testing of the application. The users were predominantly satisfied with the application (5.53 ± 1.10; Max: 7.00). Conclusions The findings of this study suggest that the developed mobile application could assist individuals with albinism to effectively manage their condition by considering the users’ requirements and services that the application should deliver.

Abstract Background Today, the use of data in administrative and clinical processes is quite challenging due to the large volume of data, data collection from various sources, and lack of data structure. As a data management tool, dashboards play an important role in timely visual display of critical information on key performances. Objectives This systematic review aimed to identify functional and non-functional requirements, as well as challenges of using dashboards in hospitals. Methods In this systematic review, four databases, including the Web of Science, PubMed, EMBASE, and Scopus, were searched to find relevant articles from 2000 until May 30, 2020. The final search was conducted on May 30, 2020. Data collection was performed using a data extraction form and reviewing the content of relevant studies on the potentials and challenges of dashboard implementation. Results Fifty-four out of 1254 retrieved articles were selected for this study based on the inclusion and exclusion criteria. The functional requirements for dashboards included reporting, reminders, customization, tracking, alert creation, and assessment of performance indicators. On the other hand, the non-functional requirements included the dashboard speed, security, ease of use, installation on different devices (e.g., PCs and laptops), integration with other systems, web-based design, inclusion of a data warehouse, being up-to-data, and use of data visualization elements based on the user’s needs. Moreover, the identified challenges were categorized into four groups: data sources, dashboard content, dashboard design, implementation, and integration in other systems at the hospital level. Conclusion Dashboards, by providing information in an appropriate manner, can lead to the proper use of information by users. In order for a dashboard to be effective in clinical and managerial processes, particular attention must be paid to its capabilities, and the challenges of its implementation need to be addressed.

Background: Breast cancer is considered one of the most common cancers in women caused by various clinical, lifestyle, social, and economic factors. Machine learning has the potential to predict breast cancer based on features hidden in data. Objective: This study aimed to predict breast cancer using different machine-learning approaches applying demographic, laboratory, and mammographic data.Material and Methods: In this analytical study, the database, including 5,178 independent records, 25% of which belonged to breast cancer patients with 24 attributes in each record was obtained from Motamed cancer institute (ACECR), Tehran, Iran. The database contained 5,178 independent records, 25% of which belonged to breast cancer patients containing 24 attributes in each record. The random forest (RF), neural network (MLP), gradient boosting trees (GBT), and genetic algorithms (GA) were used in this study. Models were initially trained with demographic and laboratory features (20 features). The models were then trained with all demographic, laboratory, and mammographic features (24 features) to measure the effectiveness of mammography features in predicting breast cancer. Results: RF presented higher performance compared to other techniques (accuracy 80%, sensitivity 95%, specificity 80%, and the area under the curve (AUC) 0.56). Gradient boosting (AUC=0.59) showed a stronger performance compared to the neural network. Conclusion: Combining multiple risk factors in modeling for breast cancer prediction could help the early diagnosis of the disease with necessary care plans. Collection, storage, and management of different data and intelligent systems based on multiple factors for predicting breast cancer are effective in disease management.

Background and Aim: Cancer is the second leading cause of death in the world, which leads to the death of more than 10 million people in the world every year. Its early diagnosis, management and proper treatment play an important role in reducing complications and mortality. One of the support tools in early diagnosis, treatment and management of this disease are Clinical Decision Support System (CDSS), which are divided into two groups, rule-based and non-rule-based. Rule-based decision support systems are created based on clinical guidelines, while non-rule-based decision support systems use machine learning. In this research, the effects of decision support systems, rule-based and non-rule-based, on cancer diagnosis, treatment and management were measured. Materials and Methods: The present study was conducted using a systematic review method, which was conducted by searching the Web of Science, Scopus, IEEE and PubMED databases until 12/31/2021. After removing duplicates and evaluating the characteristics of the inclusion and exclusion criteria, studies related to the goal were selected. The selection of articles was based on the title, abstract and full text The data collection tool was the data extraction form, which included year of study, type of study, system of body, organ of body, the service provided by the decision support system, type of decision support system, effect, effect index and the score of effect index. Narrative synthesis were used for data analysis. Results: Out of 768 articles, 16 articles related to the objectives of the study were identified. Studies were presented in two categories of clinical decision-support systems: Rule-based and non-Rule based. The effects evaluated in the clinical decision support systems were Rule-based, dose adjustment, symptoms, adherence to treatment guidelines, care time, smoking, need for chemotherapy and pain management, all of which except pain management were significant and positive. The effects evaluated were in the category of non-Rule based clinical decision support systems, diagnostic and therapeutic decisions, controlling neutropenia, all of which were significant and positive except controlling neutropenia. Conclusion: The results obtained for the effectiveness of both Rule-based and non-Rule-based decision support systems indicated different benefits of these two categories. Therefore, using their combination in the field of cancer can bring very useful results.

Abstract Background and Aims Infection with Covid‐19 disease can lead to mortality in a short time. Early prediction of the mortality during an epidemic disease can save patients' lives through taking timely and necessary care interventions. Therefore, predicting the mortality of patients with Covid‐19 using machine learning techniques can be effective in reducing mortality rate in Covid‐19. The aim of this study is to compare four machine‐learning algorithm for predicting mortality in Covid‐19 disease. Methods The data of this study were collected from hospitalized patients with COVID‐19 in five hospitals settings in Tehran (Iran). Database contained 4120 records, about 25% of which belonged to patients who died due to Covid‐19. Each record contained 38 variables. Four machine‐learning techniques, including random forest (RF), regression logistic (RL), gradient boosting tree (GBT), and support vector machine (SVM) were used in modeling. Results GBT model presented higher performance compared to other models (accuracy 70%, sensitivity 77%, specificity 69%, and the ROC area under the curve 0.857). RF, RL, and SVM models with the ROC area under curve 0.836, 0.818, and 0.794 were in the second and third places. Conclusion Considering the combination of multiple influential factors affecting death Covid‐19 can help in early prediction and providing a better care plan. In addition, using different modeling on data can be useful for physician in providing appropriate care.

Background: Knowledge management (KM) has a pivotal role in optimizing performance at organizations. In recent decades, hospitals used KM to achieve optimized performance. This study aimed to determine the knowledge management status in a non-governmental general private hospital in Tehran in 2019. Methods: This cross-sectional study was done in 2019. We selected 171 clinical and administrative staff at the hospital by using random sampling. Data wre collected through a valid and reliable questionnaire. Data analysis was done by SPSS v 22 through descriptive and analytical statistics. Results: The results of the study showed that KM dimensions had an inappropriate status (2.99 out of 5). Among the KM dimensions, Technology had a worse status than others (2.72 out of 5). Moreover, there was a significant relationship between People and Technology (pConclusion: Due to the inappropriate situation of technology in the hospital, the managers should help to provide hardware and software requirements and make it a leading hospital for technology use. Due to the positive relationship between People and Technology, equipping the hospital with new technologies led to an increase in the person's abilities and improvement of the health care services delivered to the patients.

Introduction: Effective information management in the emergency department (ED) can improve the control and management of ED processes. Dashboards, known as data management tools, efficiently provide information and contribute greatly to control and management of ED. This study aimed to identify performance indicators and quality dashboard functionalities, and analyze the challenges associated with dashboard implementation in the ED. Methods: This systematic review began with a search in four databases (Web of Science, PubMed, Embase, and Scopus) from 2000 to May 30, 2020, when the final search for papers was conducted. The data were collected using a data extraction form and the contents of the extracted papers were analyzed through ED performance indicators, dashboard functionalities, and implementation challenges. Results: Performance indicators reported in the reviewed papers were classified as the quality of care, patient flow, timeliness, costs, and resources. The main dashboard functionalities noted in the papers included reporting, customization, alert creation, resource management, and real-time information display. The dashboard implementation challenges included data sources, data quality, integration with other systems, adaptability of dashboard functionalities to user needs, and selection of appropriate performance indicators. Conclusions: Quality dashboards facilitate processes, communication, and situation awareness in the ED; hence, they can improve care provision in this department. To enhance the effectiveness and efficiency of ED dashboards, officials should set performance indicators and consider the conformity of dashboard functionalities with user needs. They should also integrate dashboards with other relevant systems at the departmental and hospital levels.

Background: The information content of medical tourism websites could influence the decisions patients and their families make regarding medical centers. This study aimed to investigate the information content of medical tourism websites. Methods: This systematic review was carried out in 2017. Key terms used for searching consisted of, but not restricted to, medical tourism, information content, information needs, and medical tourism website. The terms were searched on PubMed, Science Direct, Web of Science, Embase, ProQuest and Cochrane. One hundred and ninety-two articles out of 1185 retrieved were duplicated and removed from the study. Titles and abstracts of the remaining identified studies were scanned considering the aim of the study. Finally, 31 relevant studies were included in the study. Results: The information content of medical tourism websites can be grouped into three main categories including general information (with six subgroups), medical information (with eight subgroups) and tourism information (with one subgroup). The subgroups include information about medical centers, target country, costs and insurance, contact details, website information, photo galleries, the quality of services, trustworthiness, the quality of supportive services, risks, patient rights, physicians and their specialties, and patient instructions for receiving medical and tourism services. Conclusion: The medical tourism websites should provide a wide range of information. Considering the important role of medical tourism websites in meeting patients’ information needs, the relevant bodies should improve the information content of medical tourism websites to help patients to make their decisions reliably.

Background: The field of medicine has been influenced by the growth and development of information systems such as the Computerized Provider Order Entry (CPOE) System. Objective: This study aimed to evaluate the usability of CPOE systems for electronic prescription in Tehran, Iran. Methods: This was an evaluation study conducted in 2017. The research population consisted of the CPOE systems used in hospitals of Tehran (Iran) and nurses who had access to, and used, the CPOE systems. Five hospitals with CPOE systems were included in the research sample. The data were collected using a questionnaire, and included a total of 50 questions. The questionnaires were distributed among 254 nurses who were the users of the systems. Data analysis was performed by IBM-SPSS version 21, using independent-samples t-test. A p-value of ≤0.05 was considered statistically significant. Results: Among the four aspects assessed, the “user-friendliness” (3.87±0.59) had the highest mean score. The lowest mean score (2.01±0.58) was related to the “decision support” feature of the systems. The highest and lowest mean scores for “prescription support” criterion belonged to system E (3.26±0.23) and system C (1.90±0.16), respectively. There was a statistically significant difference between the usability of the systems used in the private and the public hospitals (p

One of the important factors for achieving “Vision 2020” targets is the availability and accessibility of eye health information systems. This study aimed to describe eye health information systems in selected countries. The status of eye health information systems in Australia, the United States, and England was reviewed. Data were gathered from the PubMed, Scopus, and ScienceDirect databases. The main key terms used included, but were not limited to “National Action plan”, “Eye Health Information System”, “Database”, and “Registery”. Also, the websites of the World Health Organization, the International Agency for the Prevention of Blindness, and Departments of Health in the selected countries were accessed. Fifty documents and articles of 170 retrieved references related to the research goals were used in this study. In all three countries, the issue of eye health is considered to be a national health priority. Concerning data gathering, the most common point in these countries was data gathered directly (health information systems, eye registries) and indirectly (studies, projects, and surveillance systems) by the organizations that participated in eye health programs. Producing accessible, timely, and highly quality information about eye health is one of the most important goals in the formation of eye health information systems in the selected countries, which facilitates achievement of the goals of the “Vision 2020: The Right to Sight” initiative.

ObjectivesAs the largest group providing healthcare services, nurses require well-designed information systems in their practice. This study aims to evaluate the usability of nursing information systems (NIS).MethodsThis cross-sectional survey was conducted in 2015. The settings of the study consisted of four hospitals affiliated with three medical universities in Tehran (Iran). The subjects of the study included nurses who had access to and used a NIS developed by four major software companies. The data were collected using a modified version of a usability questionnaire known as IsoMetrics, based on the International Standard ISO 9241, Part 11. The questionnaire is composed of 35 questions divided into seven general criteria. The validity of the questionnaire was determined by experts in the field, and the reliability was checked using Cronbach's alpha (α = 0.91). The questionnaire was then distributed to 184 nurses.ResultsThe response rate was 64.6%. Among the seven ISO usability criteria, suitability for the task (3.10 ± 1.24) and suitability for learning (3.10 ± 1.27) had the highest mean value. The lowest mean value (2.37 ± 1.29) was related to the suitability for individualization.ConclusionsAddressing issues related to individualization and self-descriptiveness could improve the usability of nursing systems. Considering usability requirements in the design of a NIS will lead to the efficient and effective use of these systems.

Background Long-term complications and high costs of cerebral palsy (CP) as well as inconsistency in data related to this disease reveal the need for extensive planning to obtain accurate and complete data for the effective management of patients.Objective The present study reviews the information architecture of CP information system.Method The relevant articles published from early 1988 to 31 July 2018 were extracted through searching PubMed, Scopus, Cochran, Web of Science and Embase databases conducted independently by two researchers.Results A total of 39 articles on CP information system were reviewed. Hospitals, rehabilitation centres and outpatient clinics were found to be the main organisations in charge of generating CP data. Each CP database used several data sources, with hospitals serving as the most important sources of information and the main generators of data. The main CP datasets were categorised into four groups of demographic data, diagnosis, motor function and visual impairment. The majority of data standards were related to the use of the International Classification of Functioning, Disability and Health and the Gross Motor Function Classification System. Finally, accuracy, completeness and consistency were the criteria employed in data quality control.Conclusion Developing a robust CP information system requires deploying the principles of information architecture when developing the system, as these can improve data structure and content of CP system, as well as data quality and data sharing.

Background: Poisoning is a common condition worldwide that requires precise evaluation of the quality and rapid management. Registry plays an essential role in the management of toxins. This study aimed to examine the features and processes of poisoning registries. Methods: This review study was conducted in 2020. Several searches were conducted in the following scientific databases: PubMed, Scopus, Embase, and Web of Science using a combination of keywords, such as “data management, registry, poison, and toxic”. The review of titles, abstracts, and full-text of the selected articles was independently performed by two researchers. Besides, the obtained data were analyzed based on the research objectives by the content analysis method. Results: Some critical features of registries were considered the confidentiality of patients’ information, i.e., equipped with various technologies, such as Geographical Information System (GIS), warning systems, searches, and text retrieval tools. The most common sources of case findings were self-reported contacts by individuals and healthcare professionals to poison control centers. Moreover, the main tool for data collection was electronic forms. The major indices of data quality were the accuracy, completeness, and consistency of the data. Phone calls were usually made at follow-ups. Conclusion: The registry’s features and processes are an essential and fundamental step to achieve the registry goals, as well as designing and developing these systems. It is recommended that the registries be equipped with various technologies to better manage the exposure cases. It is recommended to use educational, incentive, competitive, participatory, and motivational mechanisms among all organizations and individuals involved in poisoning registry programs.

Introduction: Achieving the potential benefits of electronic health record (EHR) requires data interoperability. Interoperability of a summary record is more practical than a detailed record. Interoperability requirements include identification and development uniform and standard EHR structure. This study aimed to provide an architecture model for the summary record. Methods: This was an applied and descriptive study. In this study, EHR standards and structural models were studied. After studying the standards, a structural model was designed in accordance with the summary record and health information management. Delphi technique was also used to consult informatics experts. Results: Content analysis and descriptive statistics were respectively used for preparation of the model and its validating. A proposed model was prepared based on integration of the Continuity of Care Document (CCD), Medical Markup Language (MML) and ISO 13606 [Electronic health record extract (EHR extract)] structural models and was accepted by experts. Conclusion: It seems that merging the structural models of MML, CCD and standards of EHR extract can lead to designing a structural model for summary HER brief since these models have the potential of interoperability and mapping with each other. The designed model can also be a suitable framework for organizing and sharing the records across wide geographic area.

Members of Polyphysaceae (Acetabulariaceae) are very beautiful and attractive unicellular plants which grow on coral reefs of the intertidal regions especially in tropical oceans and seas. In this study morphological features of some collected and identified species of the family from the Iranian seashores of Persian Gulf has been reported. Parvocaulis parvulus, Acetabularia caliculus and Parvocaulis clavatus are three identified species in the studied area which mainly collected from Hormozgan province seashores. Cap forms, number and form of rays, form of corona, hair scars and size of vegetative and reproductive parts of each species were studied after decalcification and results were presented in this paper.

Introduction: The pharmacy information system (PIS) is a subsystem of the hospital information system (HIS). In this study, the PIS implemented in hospitals affiliated with three medical universities in Tehran (Iran) were evaluated. Methods: This applied study was conducted using descriptive method in 2015. The study sample included five PISs in hospitals affiliated with three medical universities in Tehran which were selected and evaluated according to the system suppliers. The data were collected through observation and using a checklist (addressing both general and specific criteria). The content validity of the checklist was approved by 6 experts in the field. Data analysis was carried out using descriptive statistics. Results: With respect to the general features of the systems, only two systems were capable of restricting repeated attempts made for unauthorized access to the system. The evaluation of the specific criteria of the systems showed that no attention was paid to patient safety aspects. Furthermore, it was revealed that there was no connection between these systems and information systems of pharmaceutical companies. Conclusion: Financial aspects were the main consideration when designing and producing PISs and little attention was paid to therapeutic criteria such as patient safety. Efficient and effective use of PISs requires the consideration of both general and specific aspects in the development of such systems.

ObjectivesIn hospitals, the pharmacy information system (PIS) is usually a sub-system of the hospital information system (HIS). The PIS supports the distribution and management of drugs, shows drug and medical device inventory, and facilitates preparing needed reports. In this study, pharmacy information systems implemented in general teaching hospitals affiliated to medical universities in Tehran (Iran) were evaluated using a multi-dimensional tool.MethodsThis was an evaluation study conducted in 2015. To collect data, a checklist was developed by reviewing the relevant literature; this checklist included both general and specific criteria to evaluate pharmacy information systems. The checklist was then validated by medical informatics experts and pharmacists. The sample of the study included five PIS in general-teaching hospitals affiliated to three medical universities in Tehran (Iran). Data were collected using the checklist and through observing the systems. The findings were presented as tables.ResultsFive PIS were evaluated in the five general-teaching hospitals that had the highest bed numbers. The findings showed that the evaluated pharmacy information systems lacked some important general and specific criteria. Among the general evaluation criteria, it was found that only two of the PIS studied were capable of restricting repeated attempts made for unauthorized access to the systems. With respect to the specific evaluation criteria, no attention was paid to the patient safety aspect.ConclusionsThe PIS studied were mainly designed to support financial tasks; little attention was paid to clinical and patient safety features.

Introduction: The radiology management information systems (RMIS) are of particular importance in facilitating managers’ decision-making, controlling and planning roles. This research, hence, aimed to study the RMIS in hospitals affiliated to Tehran and Shahid Beheshti University of Medical Sciences. Methods: This research was a descriptive and cross-sectional study. To conduct the study, the hospitals affiliated to Tehran and Shahid Beheshti University of Medical Sciences was classified into two groups, and random sampling was used to select hospitals from each group. In total, the sample of the study was composed of 21 hospitals. Data collection was conducted using observation and interview using a questionnaire and a checklist. The Validity of research tools was reassured using the method of content validity. The Reliability of questionnaire was checked using test-re-test method (r=0.89), and data were then analyzed using descriptive statistics. Results: The findings showed that a mixture of paper-based and computer-based methods was used in the majority of radiology management information systems (RMIS). The data related to equipment, were gathered with 27.8%- 44.4% and this was 16.6% -33.3% for administrative and financial data. The main sources used for data acquisition were hospital information system (HIS) in computer-based systems, master patient index (MPI) and patients’ insurance documents in paper-based systems. Among the reports prepared, financial reports and those for key indices had the lowest frequency. In all centers under study, the RMIS was integrated with hospital information systems, and integration with other systems reported as 16.7%-27.8%. Conclusion: Development and improvement of RMIS would be facilitated considering complete gathering of data related to personnel, equipment and financial affairs; accurate and complete data processing as well as appropriate distribution of information.

Methods: A literature search was carried out using Science Direct, Scirus and PubMed database. The search strategy included keywords on EMS, Pre-hospital Emergency Services, Ambulance Services, Information System, and Information. The retrieved articles were then assessed for relevance and then were examined. Results: In all 172 articles were identified. Of these 65 articles were found relevant. Minimum dataset of pre-hospital emergency information system included 51 elements in America and 28 elements in England. More comprehensive and analytical reports were being created in the America’s pre-hospital emergency care than those of in England. In addition, information management and communication systems were mainly electronic-based in America compared to England. In terms of people, software and hardware equipments involved in the management of information both systems were similar. Conclusion: The effectiveness of pre-hospital emergency information system depends on the capabilities of the system, as well as its interoperability with other information systems. The pre-hospital emergency information system benefited from more capabilities in America compared to those in England, and this might be due to more robust information and communication technology infrastructures in America.

Introduction: The review of medical records with the aim of assessing the quality of codes has long been conducted in different countries. Auditing medical coding, as an instructive approach, could help to review the quality of codes objectively using defined attributes, and this in turn would lead to improvement of the quality of codes. Method: The current study aimed to present a model for auditing the quality of clinical codes. The audit model was formed after reviewing other audit models, considering their strengths and weaknesses. A clear definition was presented for each quality attribute and more detailed criteria were then set for assessing the quality of codes. Results: The audit tool (based on the quality attributes included legibility, relevancy, completeness, accuracy, definition and timeliness); led to development of an audit model for assessing the quality of medical coding. Delphi technique was then used to reassure the validity of the model. Conclusion: The inclusive audit model designed could provide a reliable and valid basis for assessing the quality of codes considering more quality attributes and their clear definition. The inter-observer check suggested in the method of auditing is of particular importance to reassure the reliability of coding.