فهرست مطالب leila shahmoradi

 Self-care applications are effective in the control and treatment of disease symptoms. Today, the mobile phone is used as one of the tools that can help us in this regard. The present study attempts to develop and evaluate a functional self-care mobile-phone application for patients with skin and hair problems using treatment protocols of herbal medicine.

 This study is a descriptive-applied type. At first, a questionnaire was prepared for data need assessment and also to determine the data items and required capabilities of the application. Based on the results, an application was designed using the Java programing language in the Android software environment. In the next step, the application was installed on the mobile phones of several specialists and patients, and the necessary corrections were made. Then, the final version of the application was evaluated.

 The most critical data elements of the mobile application for skin and hair patients included the application's functionality, temperament survey, and clinical information. After considering users' feedback, the screen functionality, the application's information and idiom, and overall functionality of the application were evaluated and approved by the users.

 By and large, the developed application could help the patients to receive the best and high-priority treatment protocols based on their own temperament.

Chronic pain is a significant clinical problem in the world. There is not quite effective treatment for chronic pain due to its complex nature. However, timely retrieval of accurate and comprehensive information through organized clinical and epidemiological studies is an essential prerequisite for providing high-quality clinical care and more accurate health care planning. This can be achieved by the creation of an electronic registry system as a strong source of information. The purpose of this study was to develop and evaluate a chronic pain registry for patients with chronic pain syndromes.

In this study, Onion architecture with the MVC design pattern was selected in design phase. Using onion architecture leads to more flexible and reusable codes and results in easier development and maintenance. In the development phase, MYSQL DBMS and the PHP programming language, which are suitable for developing the web-based system, were used.

The minimum data set was determined in the previous study. This dataset covered six areas: demographic information, initial pain assessment, medical history, mental health and well-being, diagnostic measures, and diagnosis and treatment plan. A web-based pain registry system was developed based on the minimum data set.

There are many studies for development of web- based pain registries in the world but there is a few information about technical architecture and structure in design phase. In this study, we focused on the technical architecture design of system. Using onion architecture leads to more flexible and reusable codes and results in easier development and maintenance. In the current study, it was chosen to use MYSQL and the PHP programming language, which is suitable for developing the web-based system. Finally, a web-based registry system was developed to store and report on the information of patients suffering from chronic pain. It can manage and control chronic pain and facilitate future research.

Nurses are the first line in assessing the patient's pain and performing palliative measures, and their proper training is essential. The aim of this study was to compare the effectiveness of lecture and mobile phone-based teaching methods on the knowledge and performance of nursing students in patient’s pain management.

The present study was a semi-experimental before and after study with two intervention and control groups. The samples included 52 nursing students in Saveh Medical Sciences Faculty. Learners were placed in two intervention (mobile based application) and control (lecture) groups by a simple random method. The data collection tool included a questionnaire to measure the level of awareness and a checklist to measure the pain management skills of patients by the learners. Mann-Whitney, paired t test and independent t test were used to data analysis.

After training, students' knowledge scores about pain management increased significantly in both intervention and control groups. In addition, there was a significant difference in the mean score of pain management skill and its measurement among the learners of both groups after the intervention (P<0.05).

The use of a mobile-based application can improve pain management and pain measurement skills in nursing students. The correct use of these programs can improve the quality of students' learning and also improve their knowledge and skills.

To collect, store, and distribute the electronic health records of patients with amblyopia, it is important to determine the data elements. The present study aims to determine the minimum data set (MDS) for electronic health record of patients with amblyopia in Iran.

This is an applied study that was conducted in 2020. To identify data elements, a search was conducted in PubMed, Scopus, Google Scholar, Web of Science, Scientific Information Database (SID), Magiran and Barakat knowledge system and the records of patients with amblyopia were examined and consultation with ophthalmologists in Farabi Hospital was done. Then, a questionnaire with two sections of “demographic information” and “suggested MDS for amblyopia” was prepared based on a five-point Likert scale. After confirming the validity and reliability of the questionnaire, it was completed by 20 experts from the amblyopia clinic of Farabi Hospital who were selected using a convenience sampling method. Data analysis was done using descriptive statistics in SPSS software. The data elements with an agreement score >3 were selected for the MDS of amblyopia.

Out of 98 proposed data elements, 92 were included in the MDS for amblyopia and were classified into 6 categories of demographic data, clinical data, type of strabismus, sensory tests, doctors’ prescriptions, and treatment plan.

It seems that the integration of information for patients with amblyopia in Iran and the improvement of their information management can be possible by determining the MDS for their electronic health record. By storing and retrieving standard electronic health information based on a minimum data set, it is possible to compare information, obtain high-quality information, and increase the effectiveness of medical services.

Computerized programs for brain empowerment with regular, intensive, and continuous cognitive exercises improve cognitive functions such as attention in attention deficit hyperactivity disorder. This review study aimed to identify effective computerized programs for improving attention in children and adolescents with attention deficit hyperactivity disorder (ADHD).

This descriptive narrative review was done in 2018 through library review and searching keywords including "attention deficit hyperactivity disorder", "computerized cognitive rehabilitation programs", and "play therapy" in databases such as PubMed, Scopus, and Google Scholar. The results of this review were investigated through the semi-structured interview and classified based on the attention areas of children and adolescents with ADHD.

Based on the review, Caption Log, Pay Attention, Cogmed Working Memory, Memory GYM, Attention GYM, Brainware Safari, 8 Sciences' ACTIVATET, Lumosity, My Happy Neuron, Smart Driver, and educational packages such as Maghzine were effective programs to improve different types of attention (focused, divided, intermittent, continuous, and selective) in the ADHD children aged four years old and older.

Considering the significant effects of computerized cognitive rehabilitation programs in empowering cognitive skills such as attention, their use as a complementary treatment in improving the quality of life of children and adolescents with ADHD is promising. However, it is suggested to evaluate such programs with larger samples, transfer their educational effects to daily life, and improve their quality by providing more components of such programs.

Registries are powerful tools for the collection and distribution of valid and reliable data. The initial step in health information management is to design a minimum data set that can improve the collection of high-quality data from the registry. The present pilot study aimed to determine the optimal minimum data set for dental implants to effectively utilize at Tehran University of Medical Sciences, Tehran, Iran.

This descriptive cross-sectional study was conducted in 2019 at Tehran University of Medical Sciences. A minimum data set checklist was developed based on our previous systematic review. The content validity of the minimum data set was approved by the recruited experts and the final minimum data set was established using the Delphi technique.

The minimum data set for dental implants consists of two separate sections - administrative and clinical data. The administrative portion includes two main segments: patient demographic data and clinic data, consisting of 12 data elements. The clinical part includes five main segments (patient clinical data, implant data, implant complications, implant loss, and implant follow-up), and contains 96 data elements.

This study suggests a minimum set of data for dental implants that can aid in efficient management of information, facilitate evidence-based decision-making, and enable high-quality clinical research, evaluation of treatment results, monitoring, and benchmarking of care.

Postoperative infection in Coronary Artery Bypass Graft (CABG) is one of the most common complications for diabetic patients, due to an increase in the hospitalization and cost. To address these issues, it is necessary to apply some solutions.  The study aimed to the development of a Clinical Decision Support System (CDSS) for predicting the CABG postoperative infection in diabetic patients. This developmental study is conducted on a private hospital in Tehran in 2016. From 1061 CABG surgery medical records, we selected 210 cases randomly. After data gathering, we used statistical tests for selecting related features. Then an Artificial Neural Network (ANN), which was a one-layer perceptron network model and a supervised training algorithm with gradient descent, was constructed using MATLAB software. The software was then developed and tested using the receiver operating characteristic (ROC) diagram and the confusion matrix.  Based on the correlation analysis, from 28 variables in the data, 20 variables had a significant relationship with infection after CABG (P<0.05). The results of the confusion matrix showed that the sensitivity of the system was 69%, and the specificity and the accuracy were 97% and 84%, respectively. The Receiver Operating Characteristic (ROC) diagram shows the appropriate performance of the CDSS.   The use of CDSS can play an important role in predicting infection after CABG in patients with diabetes. The designed software can be used as a supporting tool for physicians to predict infections caused by CABG in diabetic patients as a susceptible group. However, other factors affecting infection must also be considered for accurate prediction.

Identifying risk factors is recommended as the first step for depression management in children and adolescents. This study aims to determine the data elements required for developing a clinical decision support system for screening major depression in young people.

This research was a descriptive-analytical study. The research population included a variety of mental health specialists that were both psychologists and students in psychiatry and guidance & counseling majors as well as electronic databases including Scopus, Pubmed, Embase, PsychInfo, WOS and Clinical key. The data collection tool was a questionnaire designed in three main sections which was answered by a convenient sample of 8 people who were specialists in the field. To analyze the extracted data Content Validity Ratio (CVR) and Mean measures were calculated for each item in questionnaire. Content Validity Index (CVI) and Cronbach’s Alpha (using SPSS software) were calculated which were equal to 0.74 and 0.824 respectively which confirmed validity and reliability of the research tool. 

 According to Lawshe’s table, data elements with CVR between 0 and 0.75 and Mean less than 1.5, like “Ethnicity and race” (CVR=-0.25, Mean=1.125), were rejected. Items such as “Gender” (CVR=0.5) with a CVR equal to or less than 0.75, as well as items with a CVR between 0 and 0.75 and a Mean equal to or more than 1.5, like “Marital status” (CVR=0.5, Mean=1.625) were retained and considered to be included as the minimum data set for screening major depression in ages 10 to 25 years. Data elements were categorized in three categories: Demographic, Clinical and Psychosocial

Clinical decision support systems can facilitate providing healthcare at different levels such as screening major depression. These systems can be used for screening major depression risk factors to improve accessibility to mental health practitioners, assure the implementation of guidelines and provide a common language between different levels of healthcare. Determining the minimum data set for screening major depression in ages 10 to 25 years, is the first step toward developing a clinical decision support system for screening individuals for major depression.

Health information systems play an important role in improving the quality of patient c are and patient safety. to ensure their effectiveness and efficiency, they need to be evaluated. Although HIS evaluation has been investigated in many studies, there is no consensus on which aspects of HIS to evaluate. The aim of this study is to identify the indicators for the evaluation of health information systems and to provide an overview of the criteria devised and studies conducted.

An umbrella review was performed exploring databases PubMed, Science direct, Web of Science, Sci ence, and IEEE while following the PRISMA protocol. Articles were reviewed by two authors independently using the covidence tool to check the inclusion criteria and to extract the data items. Risk of bias was assessed using ROBIS and AMSTAR.

All i ncluded studies showed a high risk of bias according to ROBIS criteria. The extracted evaluation criteria were classified into 13 categories. Most of the studies believe that a more reliable and standardized tool is needed for the evaluation of health info rmation systems. Two studies mentioned that surveys and questionnaires were the most commonly used method for evaluation of the systems. Summative evaluation was the most used method in two studies and the least used method in another one study.

All the included studies had high risk of bias. Accordingly, further research and evidence is needed in this field. Most of the studies highlighted the need for more reliable and standardized tools for evaluation of health information systems.

This study aims to outline the major phases involved in developing a mobile app for self-management of knee and lumbar osteoarthritis.

This developmental research had three phases, including, content selection, application design and development, and evaluation. First, a questionnaire was created based on the literature review, and its content validity index (CVI) and content validity ratio (CVR) were measured by 15 specialists. To approve the contents of the app, the 15 rheumatologists used the Delphi technique. The application was designed using Android programming tools after the content was selected. SQLite was also used to develop a database. Finally, 12 patients evaluated the application's usability through the questionnaire for user interaction satisfaction (QUIS).

Based on the rheumatologists' preferences for information content and format, 45 key data elements were specified in 8 sections. The application was then built, which included six primary modules: medical records, educational information, disease management, record activities, reminders, and reporting. Finally, the application's usability was praised (7.56 out of 9). The application was updated with the necessary improvements based on user feedback following the evaluation.

app evaluating is currently underway to verify the application's usability and feasibility, and its effect on osteoarthritis outcomes linked to pain control and physical activity will be investigated in future studies.

This study aims to conduct a review of information technologies and telemedicine services during Covid-19 pandemic in order to identify the main challenges on the way, and provide recommendations.

A systematic review of medical informatics and telemedicine application in the 2019n-CoV period was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) method. The original papers or proceedings in English language containing the keywords were considered eligible for this study. 323 studies from the seven databases searched (PubMed, Web of Science, Science Direct, Scopus, Google Scholar, IEEE Xplore Library, and Springer Link) were imported to a project in Covidence.com and checked for duplications. After the reviewers screened their titles and abstracts, each potentially relevant study (n=107) was assessed in full text by one reviewer. As a result, 37 papers entered the study. The selected papers were then thoroughly checked by the reviewers for the desired data.

The included studies were reviewed to extract the following information: types of technologies used in each paper, challenges and limitations faced around the world (both developed and developing countries). It also provided recommendations made by reviewed studies as solutions to the mentioned challenges.

This review unveils that there are few suitable policies and strategies simplifying technology use in managing crisis like pandemics even in countries that do not lack infrastructures or equipment. This study can present a starting point as it identifies the most utilized technologies and existing limitations on the way and offers practical recommendations to conquer them.

Child abuse is a significant global concern, with short-term and long-term consequences for the lives of children who are victims of violence. For effective action by decision-makers, the information and analysis obtained from surveillance systems must be used to determine the problem, the magnitude of maltreatment, its relationship with other issues, and the likelihood of preventing maltreatment. Due to the importance of child abuse and the management and control of this event, this study was conducted to design and evaluate a child abuse surveillance system. The system was designed in Visual Studio version 2017 using the C# programming language and ASP.NET framework. SQL Server was used to store the data. The design of the child abuse surveillance system was evaluated according to the usability evaluation. The minimum data set was indexed to collect and store data on abused children by the standard format. Web-based child abuse surveillance system (CASS) has 3 types of users. The system evaluation results showed that the highest number of problems were related to the principle of "help and documentation". Designing a CASS is a practical step in managing and controlling the data of abused children. This system and registration of information will help professionals, managers, and decision-makers make the right decisions to take care of injured children with up-to-date information

Scientific collaboration indicates active teamwork between researchers beyond the simple exchange of material or information. This study is a systematic review of the papers published by Iranian researchers, aiming to provide comprehensive indicators, methodologies, and software used for evaluating scientific collaboration. According to guidelines of the Cochrane Handbook, the national and international databases were used for searching by English and Persian keywords without any time limitations. The retrieved articles were managed using EndNote software. By applying the inclusion and exclusion criteria, 201 articles remained for this review. These articles were selected from 93 domestic and foreign journals between 2000 and 2019. The studies used 16 software to extract and analyze scientific collaboration indicators. Systematic review shows that bibliometric and network analysis methods were the main approaches used in scientific collaboration studies among papers published by Iranian researchers (93.5%). More than 25 indicators were extracted from these studies, and they were categorized into patterns of collaboration and co-authorship network analysis. Researchers have revealed an increasing interest in the factors affecting scientific collaboration in recent years. The present study provides comprehensive information on the articles published by Iranian researchers on scientific collaboration. The methodologies and software were identified that are most often used to evaluate scientific collaboration and adapted to direct future research. Still, a variety of indicators situates them in heterogeneous methods of research. This analytical perspective does not locate the evaluation of scientific collaboration at a single spot. Future scientific collaboration studies will continue to evolve to offer more powerful indicators for assessing the knowledge flow status quo.

According to global statistics, stroke is known as the main health problem in the world. Many clinical and molecular research, which are stored in the different repository with the various format have been conducted in the area of stroke domain. The heterogeneity of these research data does not make a comprehensive view of the disease. Recently, translational research has been developed to fill the gap between these studies. In this study, we used the integrative disease modeling method to model the underlying mechanism of stroke risk factors.

This study was conducted in three steps: data gathering, model construction, and mechanism discovery. First, using semantic and information retrieval tools, we extracted the cause and effect statement from the literature to create the mechanistic model, and the validated molecular data to evaluate the constructed model. Then, the integrative model was created and evaluated. Finally, we used Gene Set Enrichment Analysis to identify the main biological process and signaling pathways in the mechanism of the disease.

In the evidence-based information retrieval from the literature, 1837 causal statement was extracted. The initial network was created with 648 nodes (molecular, clinical, and environmental factors) and 1837 edges (interactions). Also, 51 genes/proteins and nine single nucleotide polymorphisms were matched with data in the model. The inflammatory response, response to lipid, regulation of body fluid levels, and regulation of response to stress, complement and coagulation cascades, and PPAR signaling pathway were the main biological processes and signaling pathways enriched in GSEA analysis.

This study showed thatwe can identify the underlying mechanism of stroke risk factors and use a proper strategy to prevent it, using Integrative Disease Modeling.

During the epidemic and with an increase in coronavirus (COVID-19) disease prevalence, emergency care is essential to help people stay informed and undertake self-management measures to protect their health. One of these self-management procedures is the use of mobile apps in health. Mobile health (mHealth) applications include mobile devices in collecting clinical health data, sharing healthcare information for practitioners and patients, real-time monitoring of patient vital signs, and the direct provision of care (via mobile telemedicine). Mobile apps are increasing to improve health, but before healthcare providers can recommend these applications to patients, they need to be sure the apps will help change patients' lifestyles.

A search was conducted systematically using the keywords "Covid-19," "Coronavirus," "Covid-19, and Self-management" at the "Apple App Store". Then we evaluated the apps according to MARS criteria in May 2020.

A total of 145 apps for COVID-19 self-management were identified, but only 32 apps met our inclusion criteria after being assessed. The overall mean MARS score was 2.9 out of 5, and more than half of the apps had a minimum acceptability score (range 2.5-3.9). The "who academy" app received the highest functionality score. Who Academy, Corona-Care and First Responder COVID-19 Guide had the highest scores for behavior change.

Our findings showed that few apps meet the quality, content, and functionality criteria for Covid-19 self-management. Therefore, developers should use evidence-based medical guidelines in creating mobile health applications so that, they can provide comprehensive and complete information to both patients and healthcare provider.

Using educational websites can be effective in enhancing the health-related knowledge of patients suffering from osteoarthritis. This study aimed to design and evaluate an educational website to improve the awareness of patients with osteoarthritis. This is a descriptive-applied study. Having reviewed valid scientific articles retrieved from Medline (through PubMed), Scopus, and Google Scholar databases, the contents required for the website were identified and classified. Then, the scientific content extracted from the articles was evaluated by general physicians and Ph.D. of physical medicine and rehabilitation. Different sections of the website were designed by "Google sites," and the content was published. In the last stage of the research, the osteoarthritis educational website was evaluated by students of medicine and health information technology in terms of technical performance by a standard questionnaire. In this study, an educational website was designed to educate patients with osteoarthritis. Users can log in to the website and learn about symptoms, consequences, predisposing factors, pain relief exercises, nutritional information, and self-care programs. The content provided on the website includes three main sections of general disease information, clinical information, and disease self-care information, which physicians evaluated in the first phase. According to the content evaluation results extracted from the studies and the questionnaire's analysis, the designed website had a good quality. The average scores of the questions related to website usability, screen capabilities, terminology and information, learning ability, and overall website capability were 7.79, 8.15, 8.4, 8.08, and 8.03, respectively, which were at a "good" level. At the end of this research an educational website for osteoarthritis was created. Patients can access the site via the link and receive educational information about symptoms, consequences, predisposing factors, exercises to reduce pain, self-care, and nutritional information.

Pyelonephritis is a subset of urinary tract infections that occurs by the ascent of bacteria from the lower urinary tract to the upper tract, such as kidneys. The purpose of this study is to create an introductory multimedia educational package for pyelonephritis. The required information was retrieved from Medline (through PubMed), Web of sciences, Scopus, and Google Scholar databases by searching "Educational package" or "Training package" and "Pyelonephritis" keywords. In the next step, AutoPlay Media Studio software was selected to build an electronic educational multimedia package, considering the features of different Autoruns. In the usability evaluation stage, the isometric questionnaire 9241 part 10 was used. Four kidney and urinary tract specialists and eight experts in health information technology gave their views to us by completing the stated questionnaire. The results collected from the questionnaires were entered into SPSS-23 software for analysis using descriptive statistics. The content of the educational multimedia package, i.e., the definition of pyelonephritis, types of pyelonephritis, the causes of pyelonephritis, the underlying factors, clinical signs and symptoms, and methods of diagnosis and treatment are presented on different pages of the electronic package, respectively. The results of this usability evaluation showed that the items; "after not using the system for a long time, it is easy for the user to re-learn how to use the system" and "the user can use the system properly without asking his/her colleagues for help" had the lowest mean value (4.2) and the item; "explanations provided help the user to use the system more skillfully" had the highest mean value (4.9). The use of educational multimedia packages by patients can improve awareness and affect public health. Our educational multimedia package is superior to traditional training due to easy access and not being limited to a specific time and place, increasing the quality of learning and awareness.

Pain is a common health issue and acute pain is the main problem for patients after surgery and injury. Inadequate and inappropriate management of pain is dangerous and costly for patients and leads to undesirable health effects. To overcome this problem, empowerment of the health‑care team, especially nurses, is essential. Today, to improve the quality of health‑care provision, various methods are used that e‑learning is one of them.

Based on the studies on pain management, existing parameters were extracted, and according to them, the educational content of the software was approved by nursing professors and anesthesiologists. The Unified Modeling Language diagrams were designed to provide a better understanding of the entities and the order in which the software operates. The software was implemented in the google android studio environment using Photoshop and JQuery mobile. Finally, the software was evaluated by using Questionnaire for User Interface Satisfaction. The software was evaluated by experts and students in two stages. The first stage was evaluated by eight anesthesiologists and nursing professors, and the second stage was evaluated with the participation of 55 undergraduate students and 28 M.Sc. nursing students.

The software was developed with two main modules of training and testing, and sections of the report, about us and exit, and four scenarios for the test section. In the initial evaluation of software by experts with an average of 91.85%, and in the second assessment of students, with a mean of 78.15%, application software was evaluated at a good level.

In order to teach academic and practical (clinical) materials to students, the use of digital teaching aids and e‑learning, along with traditional methods such as lectures, increases the students’ eagerness, and motivation to learn more and thereby enhance the level of learning and improving the quality of education.

Virtual patient simulation (VPS) as a computer interactive simulation has many applications in the field of medical education. This study aimed to investigate medical learners’ views regarding the role of learning based on these types of technologies in surgical training.

In this descriptive-analytical study, the convenience sampling method was used through which 100 interns and residents from Tehran University of Medical Sciences were selected. A researcher-made questionnaire was used to collect data after confirming its validity and reliability. The data were analyzed using descriptive and inferential statistics.

According to the respondents, the greatest impact of VPS can be in creating effective learning and facilitating knowledge acquisition. Among the items examined, the highest mean score was related to the effectiveness of VPS in gaining clinical experience in rare surgeries and lack of available clinical situations (4.27) and the lowest was obtained for the effect of VPS on reducing human error and minimizing it in the patient’s bedside (3.48). VPS-based training has been given priority in cardiovascular and neurological surgeries than in other surgeries. There was also more emphasis on learning rather than evaluation with this technology.

Considering the positive attitude of the respondents towards the role of technologies in improving education, it is recommended to develop and implement these types of educational assistance programs to facilitate the acquisition of basic surgical skills and techniques.

Clinical decision support systems (CDSSs) interventions were used to improve the life quality and safety in patients and also to improve practitioner performance, especially in the field of medication. Therefore, the aim of the paper was to summarize the available evidence on the impact, outcomes and significant factors on the implementation of CDSS in the field of medicine.

This study is a systematic literature review. PubMed, Cochrane Library, Web of Science, Scopus, EMBASE, and ProQuest were investigated by 15 February 2017. The inclusion requirements were met by 98 papers, from which 13 had described important factors in the implementation of CDSS, and 86 were medicated-related. We categorized the system in terms of its correlation with medication in which a system was implemented, and our intended results were examined. In this study, the process outcomes (such as; prescription, drug-drug interaction, drug adherence, etc.), patient outcomes, and significant factors affecting the implementation of CDSS were reviewed.

We found evidence that the use of medication-related CDSS improves clinical outcomes. Also, significant results were obtained regarding the reduction of prescription errors, and the improvement in quality and safety of medication prescribed.

The results of this study show that, although computer systems such as CDSS may cause errors, in most cases, it has helped to improve prescribing, reduce side effects and drug interactions, and improve patient safety. Although these systems have improved the performance of practitioners and processes, there has not been much research on the impact of these systems on patient outcomes.

The importance of dental implant quality register has been well‑documented. However, no systematic review conducted on dental implant quality register can be found in the literature. Therefore, the purpose of this study was to study the existed dental implant quality registries to explain the goals, data elements, and reports of dental implant quality registries.

This systematic study was conducted in PubMed, Scopus, Web of Science, and Embase databases. For evaluating dental implant quality registers, all studies in the English language were examined with no time limitation. Case reports, conference abstracts, and letters to the editor were excluded. The analysis of the quality of the studies was done by the STrengthening the Reporting of OBservational studies in Epidemiology checklist.

The primary search identified 5565 articles. After eliminating duplicate articles and articles that did not meet the inclusion criteria and reviewing 40 full texts, 11 studies were included in this study. In this review, seven countries as Sweden, the USA, Canada, Germany, Finland, Australia, and South Korea had dental implant quality registers. Furthermore, the goals of dental implant quality registers were classified into the categories of research, epidemiology, administrative, clinical, and surveillance.

The results of this study provide dentists and other stakeholders useful information on the existed dental implant quality registers and databases worldwide. It also provides a framework of the goals, data elements, and reports of dental implant quality registry. The establishment of dental implant quality register will be beneficial for societies and also allows them to control the complications of dental implants in future.

Context:

Congenital hypothyroidism is the most common congenital disorder of the endocrine system, which can lead to preventable mental retardation.

We aimed to evaluate the current status of congenital hypothyroidism information registry systems.

Data Sources:

In this systematic review, the databases Scopus, science direct ProQuest, PubMed, as well as the search engine Google scholar (no restriction on date of publication) up to 2020, were searched. Inclusion criteria were the Articles with the English language that examining information registry systems on congenital hypothyroidism. Articles whose full texts were not accessible, case reports, and letters to the editor had to be excluded. In order to selection of relevant studies, the retrieved articles were accordingly screened based on the inclusion and exclusion criteria.

Study Selection:

in this systematic review 290 papers identified. A total of 254 articles were screened, of which 17 qualified articles were selected.

Data Extraction:

Two authors used the data extraction form to independently extract relevant data from included studies. Disagreements between authors were reconciled through discussion and consensus.

The results of this study showed that the main goal of nearly half (50%) of the information registry systems for congenital hypothyroidism is to evaluate the efficiency and effectiveness of the screening program. Other information registry systems for congenital hypothyroidism work with the aim of examining the epidemiology of disease in 4 studies (23.6%), monitoring iodine deficiency 3 studies (18%), surveillance disease 1 study (6%) and describing the clinical and familial features of the patient 1 study (6%).

Few studies have been done on the development of an information registry systems, and most studies have focused on the use of information systems in this field. Further Comprehensive reviews are recommended to investigate the infrastructure to commission national registry and world network to record information units on congenital hypothyroidism.

Context: 

Rheumatic Heart Disease (RHD) remains the prominent cause of morbidity and mortality among young individuals in developing countries. The present research aimed to estimate the prevalence of RHD in Iran. 

Data Sources:

 In this review, all population-based studies with a sample size of ≥500 participants related to the prevalence of RHD were included. The search was conducted in national and international databases. The combination of medical subject headings and free-term text items concerning the incidence, prevalence, rheumatic fever, RHD, and Iran were used in this study. 

Data Extraction:

 In this systematic review, 490 papers were identified. A total of 296 articles were screened; of which, 9 qualified articles were selected for the final data analysis. All studies were of cross-sectional, and descriptive natures. Two authors used the data extraction form to independently extract relevant data from the included studies. Disagreements between the authors were reconciled through discussion and consensus.

The overall prevalence of RHD was calculated as 0.02% (20/100000 population). This prevalence rate is estimated based on studies conducted in the northern, southern, eastern, western, and central regions of the country; therefore it could be an estimation of the relevant prevalence rate in Iran. However, there were no updated and high-quality data in this regard. Thus, the reported rate might be underestimated. 

There is a need for a nationwide survey to investigate the precise prevalence of RHD in Iran. This can be achieved by creating a national database of RHD.

Providing care for patients and preventing complications is one of the major subjects in medical sciences. Computerized Physician Order Entry (CPOE) with a decision support system is expected to deliver many benefits. A system with decision support system may help clinicians, patients, and others to suggest patient-appropriate evidence-based treatment options. The present study was conducted to prepare a conceptual model for a CPOE system of diabetic patients (Type 2) using Unified Modeling Language (UML). Then, a software program was designed accordingly.

This cross-sectional study was conducted in 2017. A minimum data set of patient records was used as the patient profile in the system, and a list of drugs and functional requirements of the CPOE system for diabetic patients was provided. Following the confirmation of the minimum data set by diabetes specialists, UML figures were drawn and the software was designed.

The minimum data set of patient records included demographic and clinical information as well as laboratory tests. Functional requirements of the CPOE system for type 2 diabetic patients consisted of the possibility of recording simple and complicated orders, connecting the system to the pharmacy or other auxiliary information systems, controlling drug side effects, etc.

A CPOE system should have minimum errors in documentations and provide information on allergies, drug interactions, and side effects in a timely manner to reduce medical errors, especially drug errors, increase physician efficiency and patient satisfaction, andfinally promote the quality of healthcare services

Data exchange across healthcare facilities is a major issue in healthcare information systems. Standards play an important role in the context of communication. In this paper, we surveyed the usage of standards in the hospital information systems (HISs) in the affiliated hospitals of Tehran University of Medical Sciences.

This survey was performed in 2014-2015. Seventeen hospitals that had an HIS were surveyed. The data were collected using a structured questionnaire. The design of the questionnaire was based on a literature review and consisted of three parts. Descriptive statistics were used to analyze the data.

XML, HL7 and DICOM are commonly used international interchange standards. In the case of security standards, 76.5% of HISs do not support the HIPPA and CEN TC 251 security standards. ICD was the most commonly used terminology standard in the HISs. Several studies have indicated that HISs should cover data exchange, security and terminology standards to provide integration of heterogeneous systems.

In the current study, the role of standards in the architecture of the HISs was inconspicuous. To make the HIS effective, it is necessary to consider the standards when developing the system. In this matter, legislation could help.