Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Background: Monitoring the trend of child abuse can significantly help in measuring the magnitude of the problem and understanding its recurrence. The minimum data set (MDS) is a set of elements of each domain that provides the basis for decision-making. This study was conducted to determine the comprehensive national minimum data set for child abuse surveillance system (CASS) in Iran. Methods: This is a cross-sectional descriptive study. Data were gathered from the selected countries and child abuse registry and surveillance systems. The MDS questionnaire was designed based on a review of the publications and experts' opinions. The final data elements of the CASS were determined using the Delphi technique by visiting pediatricians. Results: In total, 147 data elements were included in the Delphi survey. The data elements of the CASS were classified into seven categories as follows: demographic data, incident related data, medical history, diagnostic tests, incident nature, therapeutic measures, and other required data. Conclusion: The existence of national MDS as the core of the child abuse surveillance program is essential and leads to appropriate decisions in this regard. The MDS can meet the needs of Zahra Karbasi and Maliheh Kadivar should be considered joint first author.

One of the main health problems in many societies is the increased opium abuse, which was found to be correlated with many problems like cardiovascular disease. This study aimed to evaluate the correlation of opium use with blood lipoproteins as the risk factor of CVD. This was a cross-sectional study conducted on participants of the first phase of the PERSIAN Cohort study who were aged between 35 and 70 years old. Demographic characteristics; history of smoking, alcohol, and opium consumption; medical history; and medications were asked and the related checklists were filled out. The levels of physical activity and fat intake were also registered. As well, lipoprotein profiles were investigated by blood sampling. The linear and logistic regression was used to analyze the relationship between opium and lipid profile and the statistical significant level was considered as < 0.05. Among 9300 participants with a mean age of 48.06 ± 9.44 years old, 49.6% of them were men. About 24.1% of the participants used opium. In the linear regression models, unlike TG (β = 2.2, p = 0.36), total cholesterol (β = − 2.5, p = 0.02), LDL (β = − 2.0, p = 0.04), and HDL (β = − 1.0, p = 0.04) were significantly lower in people who used opium compared to the others. In the logistic regression models, abnormal level of LDL (OR = 0.78, p = 0.003) and total cholesterol (OR = 0.82, p = 0.008) were less in people who used opium compared to the others. This study showed that there is a correlation between opium usage and lower levels of total cholesterol and LDL; however, the lower level of HDL in normal range was seen in opium users. Considering the current evidences, most of them showed the increased risks of ischemic heart disease, heart attack, hypertension, cerebrovascular disease, and cancer in opium users. Therefore, Healthcare providers and patients should be noticed about the deleterious effects of opium consumption on various vascular events. In addition, it is necessary for managers and policy makers of the health care system to take the necessary measures to raise the level of awareness and health literacy of the general public about the high-risk side effects of opium use and to take necessary and effective strategies to prevent and reduce its use.

This study attempted to review the evidence for or against the effectiveness of mobile health (m-health) interventions on health outcomes improvement and/or gestational diabetes mellitus (GDM) management. PubMed, Web of Science, Scopus, and Embase databases were searched from 2000 to 10 July 2018 to find studies investigating the effect of m-health on GDM management. After removing duplications, a total of 27 articles met our defined inclusion criteria. m-health interventions were implemented by smartphone, without referring to its type, in 26% (7/27) of selected studies, short message service (SMS) in 14.9% (4/27), mobile-based applications in 33.3% (9/27), telemedicine-based on smartphones in 18.5% (5/27), and SMS reminder system in 7.1% (2/27). Most of the included studies (n=23) supported the effectiveness of m-health interventions on GDM management and 14.3% (n=4) reported no association between m-health interventions and pregnancy outcomes. Based on our findings, m-health interventions could enhance GDM patients' pregnancy outcomes. A majority of the included studies suggested positive outcomes. M-health can be one of the most prominent technologies for the management of GDM.

Introduction: Ingestion of acidic or alkaline substances and its long-term effects on digestive system indicates is a common health problem worldwide. To identify the root causes of injuries, standard data collection is required. Aim: The present study was conducted to determine the data requirements for the establishment of information management system for poisoning with acidic and alkaline substances in Iran. Methods: This is a descriptive and cross-sectional study conducted in 2017. First, we attended at the hospitals affiliated to Iran, Tehran and Shahid Beheshti universities of medical sciences, which had poisoning wards; we studied all forms, reports and medical records of people who had been poisoned by acidic or alkaline substances. In the next step, a comprehensive literature review was carried out to retrieve related resources. Data were collected using data extraction form and Delphi method was used to survey them. Validity of the questionnaire was evaluated through content validity and its reliability checked by the test-retest method and Cronbach’s alpha. Results: A minimum data set (MDS) of alkaline and acid poisoning divided into two categories: administrative with three classes including 35 data elements, and clinical with 6 classes including 145 data elements. Conclusion: Comprehensive and uniform data elements about alkaline and acid poisoning was not available in Iran. Development of a MDS resulted in standardization and effective management of the data through providing uniform and comprehensive data elements for alkaline and acid poisoning and comparability of information in various levels and made effective decision-making and policy-making possible.

Reproductive health is vital for human and infertility is also one of the most important challenges in the reproductive system. Infertility is one of the most common chronic health disorders, regardless of age. The Minimum Data Set (MDS) helps to manage infertility by monitoring and evaluating infertility interventions based on collecting data. The development of MDS is an essential objective in order to implement an infertility monitoring system for the creation of standardized and effective data management through the provision of comprehensive and identical data elements for infertility. This is a descriptive cross-sectional study conducted in 2017. The data has been collected from infertility clinics in the world, as well as WHO, CDC, ASRM, and ESHRE reports. In order to decide on data elements, the Delphi technique was used using a questionnaire that contained data elements which were distributed among 12 experts including one reproductive endocrinology and infertility fellow, six obstetrician-gynecologists, two reproductive biologists, two urologists and one community medicine specialist using the 5 point Likert scale. The questionnaire was divided into two categories: managerial and clinical, each with 4 sections, and 60 and 940 data elements, respectively. MDS is an essential tool for evaluating the infertility process. Using this tool will provide an opportunity to develop a set of quality care criteria that can be used to ensure the quality of infertility care.

BackgroundSince there is no specific treatment for coronavirus, there is an urgent need for global monitoring of people with Covid-19. The use of e-health services should be compatible with the diagnosis and control of the outbreak of zoonotic infectious diseases. The aim of this study is to provide a conceptual model based on health information technology services for Covid-19 disease management.MethodsThe present study is an applied descriptive study that was performed on a cross-sectional basis in a COVID-19 Center Hospital in Fars province of IRAN country in April 2020. The main tool of this research is a questionnaire that has been compiled by reviewing related articles in databases and surveying with experts in order to determine the necessary services in the management and control model of the prevalence of Covid19 disease. Then, in order to determine the necessary services in the conceptual model, this questionnaire was given to various specialists in the COVID-19 Center Hospital. Finally, based on the results of the questionnaire, a comprehensive conceptual model for the management and control of COVID 19 diseases is presented.ResultsThe proposed model consisted of three layers of cloud computing, fog and data acquisition. All services were approved by the surveyed participants. Among the services, Tele- monitoring for home quarantine, Electronic self-assessment, Telepsychology of patients in home and hospital quarantine, Tele prescription, Tele- information Tele- training have the highest agreement rate. proposed model is an integrated model. The innovation that can be mentioned in this research is the use of priority queue service as a service of the fog layer.ConclusionInformation communication technology tools have an important role in all aspects of contagious diseases management.

This study was attempted to review the evidence for or against the effectiveness of m-health interventions on health outcomes improvement and/or GDM management. Based on our findings, m-health interventions could enhance GDM patients' pregnancy outcomes. M-health can be one of the most prominent technologies for the management of GDM.