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Healthcare organizations must urgently prioritize interoperability to enhance the quality of care they provide. However, achieving this collaboration comes with numerous challenges, including differing approaches, data formats, and standards, as well as concerns about privacy, security, technical complexity, and legal and regulatory issues. To tackle these challenges, we determined a set of interoperability solutions. We also developed a comprehensive, component-based, data-driven framework for healthcare systems. Our study's approach involved three main steps: first, conducting a literature review to gather interoperability requirements and solutions from online databases and grey literature; second, carrying out a qualitative study to develop a framework based on the review results and focus group discussions; and third, using the Delphi method to validate the framework with experts. We extracted information from 36 articles during the screening and assessment process. Based on the proposed framework, we organized the identified themes into various categories, including architecture, architecture components, standards, platforms, policies, data sources, consumers, applications, level of interoperability, healthcare facilities, and considerations. Experts believe that establishing a comprehensive architecture for launching interoperability between health information systems can greatly facilitate this process. All framework components (totaling 197) received unanimous approval. The landscape of healthcare delivery is shifting from a focus on diseases to a patient-centered, data-driven approach. There is a growing demand for personalized healthcare systems, which necessitates increased interoperability among all healthcare stakeholders, particularly when dealing with diverse types of data. Our framework is designed to facilitate the implementation of various types of interoperability in healthcare systems., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Forward Head Posture (FHP) is one of the most commonly occurring musculoskeletal abnormalities. Despite exercise therapy being an effective approach for FHP treatment, it can be long, monotonous, and tedious. Virtual reality (VR) can be used as an innovative solution to address these challenges. We designed an affordable and immersive VR-based exercise therapy (VRET) system for FHP correction. The VRET contents (i.e., exercises and VR scenarios) were determined by physiotherapists and game designers at the focus group meetings. Hardware requirements include a VR box, smartphone, and sensors (i.e., a smartphone accelerometer and an affordable Inertial Measurement Unit (IMU)) to measure head motions and transfer them via Wi-Fi to the VRET system. The IMU was designed using the MPU6050, Arduino Nano, and ESP8266-01S. Gwet's AC1, Game Experience Questionnaires (GEQ), and System Usability Scale (SUS) were used to measure intra-rater reliability, user experience, and system usability, respectively. The determined exercises, including Capital Flexion-Extension and Chin Tuck, were designed in the form of a shooting game. A physiotherapist and twenty-one FHP individuals took part in evaluating the system. High precision was obtained for the designed IMU (i.e., pitch and roll < 0.1° and yaw < 1.3 °). Gwet's AC1 and SUS results showed very good intra-rater reliability (coefficient = 0.892) and excellent usability (score = 87.14), respectively. According to the mean scores of the GEQ, participants were confident about competence, immersion, flow, and positive affect components. The development of low-cost VRET systems for FHP correction is a step towards facilitating rehabilitation challenges by providing positive experiences for users as well as helping them perform therapeutic exercises correctly., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Asadzadeh et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Health care providers need a better understanding of virtual care to recognise and use it for service delivery., Aim: To provide a more comprehensive definition of the concept of virtual care., Method: This study was conducted based on Walker and Avant's concept analysis method. A comprehensive review of the published texts in English from 2012 to 2022 was performed using the PubMed, Web of Science, Scopus, ProQuest, Science Direct, Ovid, CINAHL and Google Scholar databases., Results: The main aspects and attributes of virtual care, including the use of any information and communication technology in various formats such as platforms, telephone calls, messages, email consultation, remote monitoring, secure and two-way digital communication between health care providers and patients, the possibility of providing remote care synchronously or asynchronously, more interaction between patients and caregivers, the possibility of transferring information between patients and health care providers and within the teams themselves, symptom management, sending diagnostic results in the form of video visits, and providing follow-up care, are attributes that distinguish virtual care from telehealth, telemedicine and other methods of providing remote healthcare services., Conclusion: Considering the positive and negative consequences of implementing virtual care, the findings of this study developed a basis for an operational definition of the concept so that providers can understand the meaning of virtual care and consider it when providing virtual care to patients. The findings of this study can be used in many international and national contexts in the health care system and in future studies on interventions to increase the use of virtual care., (© 2023 Nordic College of Caring Science.)

Background and Aims: Collaboration has become a crucial element of effective healthcare delivery in the emergency department (ED). In high-pressure environments, healthcare providers can prioritize patients by consulting with other specialists to gain diverse perspectives and arrive at a shared understanding of the best course of action. It was conducted for the purpose of designing and evaluating the collaborative decision-making application for patient care in the ED., Methods: The present applied research study was conducted between April 1, 2021 and May 31, 2023 at Imam Reza Hospital of Tabriz University of Medical Sciences. The study was conducted in three phases: exploration, development, and evaluation, utilizing modern technologies such as Flutter and Node.js to design and program the application. The effectiveness of the system was evaluated using established measures, including the think-aloud protocol, user experience questionnaire, and Likert-scale questionnaires developed by Ghadri et al., Results: The average scale for attractiveness was 2.03, perspicuity was 2.90, efficiency was 2.40, dependability was 1.93, stimulation was 2.48, and novelty was 2.78. Additionally, 71% of physicians gave a very good rating to the accessibility of necessary information at any time, motivation to use the system for accessing information, usefulness of the system compared to the time spent using it throughout the day. Furthermore, 57% of physicians gave a very positive rating to sharing information and knowledge, ease of using the search function and accessing the system, user control and monitoring, free access to the system, and support from colleagues and system users., Conclusion: The study suggests that introducing Information and Communication Technology such as medical apps can improve healthcare delivery by streamlining patient care, promoting effective teamwork, and reducing medical errors and treatment delays., Competing Interests: The authors declare no conflict of interest., (© 2024 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Background: One of the major challenges that hospitals and clinicians face is the early identification of newborns at risk for adverse events. One of them is neonatal respiratory distress syndrome (RDS). RDS is the widest spared respiratory disorder in immature newborns and the main source of death among them. Machine learning has been broadly accepted and used in various scopes to analyze medical information and is very useful in the early detection of RDS. Objective: This study aimed to develop a model to predict neonatal RDS and affecting factors using data mining. Materials and Methods: The original dataset in this cross-sectional study was extracted from the medical records of newborns diagnosed with RDS from July 2017-July 2018 in Alzahra hospital, Tabriz, Iran. This data includes information about 1469 neonates, and their mothers information. The data were preprocessed and applied to expand the classification model using machine learning techniques such as support vector machine, Naïve Bayes, classification tree, random forest, CN2 rule induction, and neural network, for prediction of RDS episodes. The study compares models according to their accuracy. Results: Among the obtained results, an accuracy of 0.815, sensitivity of 0.802, specificity of 0.812, and area under the curve of 0.843 was the best output using random forest. Conclusion: The findings of our study proved that new approaches, such as data mining, may support medical decisions, improving diagnosis in neonatal RDS. The feasibility of using a random forest in neonatal RDS prediction would offer the possibility to decrease postpartum complications of neonatal care., Competing Interests: The authors declare that there is no conflict of interest., (Copyright © 2023 Farshid et al.)

Aim: To assess the barriers to the implementation of virtual care for patients with chronic wounds from wound therapists' perspective., Design: A qualitative study., Methods: The study was conducted in two consecutive phases: (1) literature review, (2) descriptive qualitative study. In the first phase, texts published in English until 2023 were identified using international databases. The entire text of the selected studies was evaluated independently by two reviewers. Data analysis was carried out using textual content analysis. In the second phase of the study, twelve participants from Iranian wound care clinics participated. Data were collected through focus group discussion and analysed using conventional content analysis. Integration of both phases was conducted in the data analysis stage., Results: The most important barriers in providing virtual care to patients with chronic wounds were identified into five categories including lack of policymaking in virtual care, ethical challenges in virtual information and communication technology, social, economic and cultural issues, IT users' insufficient knowledge and limitation of virtual care scope of practice., Conclusion: The findings of the present study identified different barriers in the implementation of virtual care for patients with chronic wounds. In order to successfully develop a virtual care programme, it is necessary to adopt suitable policies regarding information and communication technology, provide the necessary legal frameworks, assign an adequate budget and consider the ethical, cultural, social and social issues., Implications for the Profession And/or Patient Care: Identifying barriers to developing a virtual care programme will help manage patients with chronic wounds at home., Impact: This study accurately identifies barriers to providing virtual care for patients with chronic wounds and helps plan to address these barriers and facilitate the development of a virtual care programme for these patients at home., Reporting Method: This research has adhered to the SRQR reporting guideline., No Patient or Public Contribution: The involvement of patients or the public in the design, or conduct, or reporting, or dissemination plans of this research was not suitable., (© 2023 The Authors. Nursing Open published by John Wiley & Sons Ltd.)

Background: Accurate segmentation of stroke lesions on MRI images is very important for neurologists in the planning of post-stroke care. Segmentation helps clinicians to better diagnose and evaluation of any treatment risks. However, manual segmentation of brain lesions relies on the experience of neurologists and is also a very tedious and time-consuming process. So, in this study, we proposed a novel deep convolutional neural network (CNN-Res) that automatically performs the segmentation of ischemic stroke lesions from multimodal MRIs., Methods: CNN-Res used a U-shaped structure, so the network has encryption and decryption paths. The residual units are embedded in the encoder path. In this model, to reduce gradient descent, the residual units were used, and to extract more complex information in images, multimodal MRI data were applied. In the link between the encryption and decryption subnets, the bottleneck strategy was used, which reduced the number of parameters and training time compared to similar research., Results: CNN-Res was evaluated on two distinct datasets. First, it was examined on a dataset collected from the Neuroscience Center of Tabriz University of Medical Sciences, where the average Dice coefficient was equal to 85.43%. Then, to compare the efficiency and performance of the model with other similar works, CNN-Res was evaluated on the popular SPES 2015 competition dataset where the average Dice coefficient was 79.23%., Conclusion: This study presented a new and accurate method for the segmentation of MRI medical images using a deep convolutional neural network called CNN-Res, which directly predicts segment maps from raw input pixels., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background and Objective: A treatment approach that is widely used as a permanent and natural replacement for missing or extracted teeth is dental implants .VR is a computer-generated simulation that creates a three-dimensional (3D) image or environment. Advances in VR -based learning allow learners and students to practice and also help professionals plan a wide variety of surgical procedures, including the correct placement of dental implants. Therefore, in this systematic review, our aim was to investigate and evaluate the available virtual reality tools for dental implants and their effectiveness., Materials and Methods: Studies published up to 01/30/2023 which report the applications of using virtual reality technology in dental implants, were reviewed in three databases, including PubMed, Web of Science, and Scopus. All studies with evidence reporting the role of virtual reality technology in the field of dental implants were included in our analyses, written in English and published in peer-reviewed form, are included. Theoretical articles, and letters that did not provide original data, as well as studies that reported incomplete information, were excluded. Two reviewers independently assessed search results, extracted data, and assessed the quality of the included studies, and decisive agreement was reached by discussion and consultation with the third researcher. Narrative synthesis was undertaken to summarize and report the findings., Results: Out of 1633 initial search results, nine were included in the present study based on the inclusion criteria. The focus of seven studies was on teaching and learning, and two studies have examined the implant planning procedure. The most commonly used hardware and software were head-mounted display and Unity3D, respectively. In almost all studies, the results showed that the use of virtual reality-based systems improves and enhances the skills of users, including dental students and specialists., Conclusions: Our findings showed that VR is an effective method for teaching and planning the implant process. Although the use of VR technology is limited for various reasons such as cost, it can increase the skills of dental professionals in performing dental implants., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background: Neonatal sepsis, particularly gram-negative (GN) bacteria-induced, is a significant cause of morbidity and mortality in newborns. Healthcare professionals find this issue challenging because of antibiotic resistance. This study aims to combine findings to identify the prevalence of GN bacteria and their antibiotic resistance in Iranian neonates with sepsis., Methods: This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The literature search was performed through international databases, including (PubMed/MEDLINE, EMBASE, Scopus, and Web of Science), Iranian local databases (Magiran, Iranmedex, Irandoc, Scimed, and SID), and the first 100 records of Google Scholar. Analytical cross-sectional study checklist from the Joanna Briggs Institute (JBI) was used for the quality assessment of included studies. Comprehensive Meta-Analysis Software Version 2 was used to conduct the meta-analysis. The between-study heterogeneity was investigated by I 2 statistics., Results: The prevalence of GN bacteria was estimated to be 53.6% [95% CI: 45.9- 61.1: P = 0.362] in Iranian neonates with sepsis, based on 31 studies with a sample size of 104,566. klebsiella pneumoniae (K.pneumonia) (23.2% [95% CI: 17.5-30.0, P < 0.001]) followed by Escherichia coli (E.coli) (13.5% [95% CI: 9.4-18.9, P < 0.001]) were more prevalent among GN bacteria. The highest resistance in K.pneumoniae was observed in Cefixime (80.6%, [95% CI: 56.3-93.1, P = 0.018]). E.coli showed greater resistance to Ampicillin (61.8%, [95% CI: 44.2-76.5, P = 0.188]. The prevalence of GN bacteria in Iranian neonates with sepsis has a decreasing trend based on the year, as shown by a meta-regression model (P < 0.0004)., Conclusion: GN pathogens, particularly K.pneumoniae, and E.coli, are the leading cause of neonatal sepsis in Iran. GN bacteria showed the highest resistance to Third-generation cephalosporin and Aminoglycosides., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Background and Aims: Conventional medical training routes of bronchoscopy may decrease patients' comfort and increase procedure-related morbidity. Virtual reality (VR)-based bronchoscopy is a beneficial and safe solution for teaching trainees. The aim of this systematic review was to study the effectiveness of VR-based bronchoscopy simulators on the learning outcomes of medical trainees., Methods: Well-known sources (i.e., Scopus, ISI Web of Science, and Medline via PubMed) were systematically searched using Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines on December, 2021. Peer-reviewed English papers that used VR-based simulation for bronchoscopy training were included. The articles that were studying other technologies, or those that were unrelated to the topic, were excluded. The risk of bias was assessed using the Joanna Briggs Institute checklists for quasi-experimental studies and randomized controlled trials (RCTs)., Results: Out of 343 studies, 8 of them met our inclusion criteria. An appropriate control group and statistical analysis were the most common and unavoidable sources of bias in included non-RCTs, and lack of blinding in participants was the most common source of bias in RCTs. The included studies evaluated learning outcomes regarding dexterity ( N  = 5), speed ( N  = 3), the accuracy of procedures ( N  = 1), and the need for verbal assistance ( N  = 1). Based on the results, 100% (5/5) and 66% (2/3) of studies showed that the use of VR-based simulation on the learning outcomes of medical trainees led to improvement in manual ability (i.e., dexterity) and swiftness of execution (i.e., speed in performance), respectively. Additionally, improving the accuracy of subjects' performance, and reducing the need for verbal guidance and physical assistance was reported in studies that evaluated these variables., Conclusion: VR bronchoscopy simulator as a training method for teaching medical trainees, especially for novices has the potential to improve medical trainees' performance and reduce complications. Further studies are needed to evaluate the positive effects of VR-based simulation on the learning outcomes of medical trainees., Competing Interests: The authors declare no conflict of interest., (© 2023 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

For virtual care models to be able to improve the safety and quality of care, it is essential to identify the strengths and weaknesses of virtual care. In this Scoping review, literature published on virtual care was identified using international databases. The results of the included studies were summarized using a predefined taxonomy. In total, 20 studies were included in the present review. Extracting the findings of the articles showed four main topics, including "virtual care delivery models," "Video conference software platforms to provide virtual care," "virtual care delivery challenges," and "virtual care implementation facilitators." Therefore, with the development of emerging digital technologies, unique opportunities to provide virtual care and improve the provision of health services have been created in the health care system worldwide. Multifunctional video conference software platforms using specific models for each scope of care practice should be considered.

Background: The lack of interoperability between health information systems reduces the quality of care provided to patients and wastes resources. Accordingly, there is an urgent need to develop integration mechanisms among the various health information systems. The aim of this review was to investigate the interoperability requirements for heterogeneous health information systems and to summarize and present them., Methods: In accordance with the PRISMA guideline, a broad electronic search of all literature was conducted on the topic through six databases, including PubMed, Web of science, Scopus, MEDLINE, Cochrane Library and Embase to 25 July 2022. The inclusion criteria were to select English-written articles available in full text with the closest objectives. 36 articles were selected for further analysis., Results: Interoperability has been raised in the field of health information systems from 2003 and now it is one of the topics of interest to researchers. The projects done in this field are mostly in the national scope and to achieve the electronic health record. HL7 FHIR, CDA, HIPAA and SNOMED-CT, SOA, RIM, XML, API, JAVA and SQL are among the most important requirements for implementing interoperability. In order to guarantee the concept of data exchange, semantic interaction is the best choice because the systems can recognize and process semantically similar information homogeneously., Conclusions: The health industry has become more complex and has new needs. Interoperability meets this needs by communicating between the output and input of processor systems and making easier to access the data in the required formats., (© 2023. The Author(s).)

Background: Despite growing evidence, there is still uncertainty about potentially modifiable risk factors for neonatal early-onset sepsis (EOS). This study aimed to identify potential clinical risk factors for EOS based on a literature review and expert opinions., Methods: A literature search was conducted in PubMed (MEDLINE), Cochrane, Embase, and Scopus databases. Articles in English, published up to May 2021, on clinical risk factors for neonatal EOS were included. Initially, a questionnaire on risk factors for EOS was developed and validated. The fuzzy Delphi method (FDM) was used to formulate the final version of the questionnaire. The validity of the risk factors was assessed using the Chi square test. P<0.05 was considered statistically significant., Results: In the review phase, 30 risk factors were approved by two neonatologists and included in the FDM phase. In total, 25 risk factors met the consensus criteria and entered the validation phase. During the observational study, 114 neonates (31 with and 83 without EOS) were evaluated for two months. The results of the Chi square test showed that cesarean section was not a significant risk factor for EOS (P=0.862). The need for mechanical ventilation and feed intolerance was observed in about 70% of neonates with EOS, and therefore considered significant risk factors for EOS (P<0.001). Finally, 26 potential clinical risk factors were determined., Conclusion: Neonatal-related risk factors for EOS were birth weight, one-min Apgar score, and prematurity. Maternal-related risk factors were gestational age and urinary tract infection. Delivery-related risk factors were premature rupture of membranes, chorioamnionitis, and intrapartum fever., Competing Interests: None declared., (Copyright: © Iranian Journal of Medical Sciences.)

Background and Aims: The COVID-19 pandemic has changed people's lifestyles as well as the way healthcare services are delivered. Undoubtedly, the difficulties associated with COVID-19 infection and rehabilitation and those associated with quarantine and viral preventive efforts may exacerbate the need for virtual reality to be used as a part of a complete rehabilitation strategy for these individuals. Thus, the present research aimed to evaluate the potential uses of virtual reality for the rehabilitation of individuals suffering from COVID-19., Methods: From 2019 to March 1, 2022, a systematic search was conducted in PubMed, Cochran Library, Scopus, Science Direct, ProQuest, and Web of Science databases. The papers were selected based on search terms and those that discussed the use of virtual reality in the rehabilitation of COVID-19 patients were reviewed. Each step of the study was reviewed by two authors., Results: A total of 699 papers were found during the first search. Three papers were chosen for further investigation after a thorough evaluation of the publications' titles, abstracts, and full texts. Cross-sectional studies, randomized controlled clinical trials, and case reports comprised 33%, 33%, and 33% of the publications, respectively. Based on the results, people suffering from COVID-19 were the focus of two papers (66%) that employed immersion virtual reality for cognitive rehabilitation, whereas one study (33%) used non-immersive virtual reality for physical rehabilitation. In two papers (66%), virtual reality was also offered to patients in the form of a game., Conclusion: According to the results of the present research, virtual reality games may enhance functional and cognitive consequences, contentment levels among patients, and their ability to take charge of their own health care. In light of the obstacles faced by COVID-19 patients, alterations in the delivery of healthcare, and the significance of rehabilitation in this group during quarantine, new techniques have been considered for these patients to maintain treatment, return to regular life, and enhance their standard of life., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Background and Aims: One of the barriers to effective communication between speaker and listeners is public speaking anxiety (PSA). Over recent years, PSA has become common among students as the most widespread social anxiety (SA). Virtual reality (VR) and counseling therapy help reduce PSA. Therefore, the present study aimed to investigate the effect of VR therapy and counseling on students' PSA and SA., Methods: This quasi-experimental study was conducted on 30 students at three levels of undergraduate, postgraduate, and PhD at Kerman University of Medical Sciences and Shiraz University of Medical Sciences (15 students in the intervention group and 15 in the control group). The intervention group observed four virtual classroom scenarios in a 30-min session, and the control group attended a 90-min group counseling session. Data were collected using by Personal Report of Public Speaking Anxiety, Liebowitz Social Anxiety Scale, and Igroup Presence Questionnaire. The data analysis was done using SPSS version 21. Descriptive analysis (frequency and percentage, mean, standard deviation, and quartiles) and analytical tests (paired t -test and independent t -test) were used to analyze the data., Results: The results showed that VR and counseling did not affect SA scores and statistical differences before and after the intervention were not statistically significant. However, VR and counseling reduced PSA. The mean of IPQ/IGP (physical presence) was 63.73. The participants' SA means (93.76) were higher than the mean PSA (73.4)., Conclusions: VR and counseling did not affect students' SA, but they reduced PSA. If the intervention duration in future studies are longer, the effect of VR and counseling on reducing SA is likely to become more apparent., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Health Science Reports published by Wiley Periodicals LLC.)

Background and Objective: Paranoia is an important psychiatric symptom with a remarkable effect on daily life. Virtual reality (VR)-based treatments are influential and safe for patients with paranoia. This study aimed to evaluate the effectiveness, and define the clinical and technical characteristics of available VR strategies for the treatment of patients with paranoia., Materials and Methods: Studies published up to 25/11/2021 reporting VR-based interventions for the treatment of patients with paranoia were reviewed in five databases, including PubMed, Embase, Web of Science, PsycINFO, and Scopus., Results: Out of 302 initial search results, eight were included in the present study based on the inclusion criteria. Six studies were randomized clinical trials with the interventions in the experimental group being based on VR, compared to routine interventions as controls. Two were before-after studies. The most commonly used hardware and software were head-mounted display and Unity3D, respectively. Interventions had a range of 1-16 sessions with follow-up durations of 0-6 months. All investigations showed positive results in the main target, including improved social participation, reduced level of anxiety, as well as diminished suspicious ideas and paranoid symptoms., Conclusions: Our findings demonstrated that VR-based interventions are effective treatments. Although the use of VR technology is limited for a variety of reasons, such as cost, it improves symptoms in patients with paranoia., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Pelvic organ prolapse (POP) and stress urinary incontinence (SUI) are common conditions affecting women's health and quality of life. In 50% of cases, SUI occurs after POP surgery, which is called de novo SUI. Predicting the risk of de novo SUI is a complex multi-attribute decision-making process. The current study made available a Decision Support System in the form of a fuzzy calculator web-based application to help surgeons predict the risk of de novo SUI., Materials and Methods: We first identified 12 risk factors and the diagnostic criteria for de novo SUI by means of a systematic review of the literature. Then based upon an expert panel, all risk factors were prioritized. A set of 232 fuzzy rules for the prediction of de novo SUI was determined. A fuzzy expert system was developed using MATLAB software and Mamdani Inference System. The risk prediction model was then evaluated using retrospective data extracted from 30 randomly selected medical records of female patients over the age of 50 without symptoms of urinary incontinence who had undergone POP surgery. Finally, the proposed results of the predictive system were compared with the results of retrospective medical record data review., Results: The results of this online calculator show that the accuracy of this risk prediction model, at more than 90%, compared favorably to other SUI risk prediction models., Conclusions: A fuzzy logic-based clinical Decision Support System in the form of an online calculator for calculating SUI prognosis after POP surgery in women can be helpful in predicting de novo SUI., Competing Interests: No conflict of interest has been declared by the author., (Copyright © 2021 The Authors. Published by Wolters Kluwer Health, Inc.)

Static and dynamic posture analysis was a critical clinical examination in physiotherapy and rehabilitation. It was a time-consuming task for clinicians, so a semi-automatic method can facilitate this process as well as provide well-documented medical records and strong infrastructure for deep learning scenarios. The current research presents a mechatronics platform for static and real-time dynamic posture analysis, which consisted of hybrid computational modules. Our study was a developmental and applied research according to a system development life cycle. The designed modules are as follows: (1) a mechanical structure includes patient place, 360-degree engine, mirror, laser, distance meter, and cams; (2) a software module includes data collection, electronic medical record, semi-automatic image analysis, annotation, and reporting, and (3) a network to exchange raw data with deep learning server. Patients were informed about the research by their healthcare provider and all data were transformed into a Fourier format, in which the patients remained autonomous without a bit of information. The results show acceptable reliability and validity of the instruments. Also, a telerehabilitation application was designed to cover the patients after diagnosis. We suggest a longer time for data acquisition. It will lead to a more accurate and fully automated dynamic posture analysis. The result of this study suggest that the designed mechatronics device used in conjunction with smartphone application is a valid tool that can be used to obtain reliable measurements., (© 2021. Australasian College of Physical Scientists and Engineers in Medicine.)

The pandemics of major infectious diseases often cause public health, economic, and social problems. Virtual reality (VR) and augmented reality (AR), as two novel technologies, have been used in many fields for emergency management of disasters. The objective of this paper was to review VR and AR applications in the emergency management of infectious outbreaks with an emphasis on the COVID-19 outbreak. A search was conducted in MEDLINE (PubMed), Embase, IEEE, Cochrane Library, Google Scholar, and related websites for papers published up to May 2, 2020. The VR technology has been used for preventing or responding to infections by simulating human behaviors, infection transmission, and pathogen structure as a means for improving skills management and safety protection. Telehealth, telecommunication, and drug discovery have been among the other applications of VR during this pandemic. Moreover, AR has also been used in various industries, including healthcare, marketing, universities, and schools. Providing high-resolution audio and video communication, facilitating remote collaboration, and allowing the visualization of invisible concepts are some of the advantages of using this technology. However, VR has been used more frequently than AR in the emergency management of previous infectious diseases with a greater focus on education and training. The potential applications of these technologies for COVID-19 can be categorized into four groups, i.e., 1) entertainment, 2) clinical context, 3) business and industry, and 4) education and training. The results of this study indicate that VR and AR have the potential to be used for emergency management of infectious diseases. Further research into employing these technologies will have a substantial impact on mitigating the destructive effects of infectious diseases. Making use of all the potential applications of these technologies should be considered for the emergency management of the current pandemic and mitigating its negative impacts., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors.)

Competing Interests: Conflict of interest The authors declare that there is no conflict of interest.

Objective: Stress urinary incontinence (SUI) is a common problem in women that affects their quality of life. According to the current evidence, 15%-50% of severe pelvic organ prolapse (POP) surgeries lead to de novo urinary incontinence (UI). This study aimed at determining the risk factors and characteristics of de novo SUI after POP surgeries in a systematic review., Material and Methods: We conducted a systematic search of articles in English related to the risk of UI after POP surgery published until December 2019 in the selected bibliographic databases, including PubMed, EMBASE, Scopus, Cochrane Library, and ProQuest., Results: The initial search resulted in 2,363 studies, and after reviewing the titles and abstracts, 146 studies were identified. Moreover, 2 independent reviewers, using the Joanna Briggs Institute checklists, evaluated the risk of biases in the selected studies. Finally, 40 studies met the inclusion criteria. The most important predictors of UI after POP surgery were positive pessary testing, age >50 years, and maximum urethral closure pressure (MUCP) <60 cmH 2 O., Conclusion: Positive pessary testing, older age, and low MUCP were the most important risk factors for de novo incontinence after POP surgeries.

Objectives: A timely, accurate assessment and decision-making process is essential for the diagnosis and treatment of the acute stroke, which is the world's third leading cause of death. This process is often performed using the traditional method that increases the complexity, duration, and medical errors. The present study aimed to design and evaluate an intelligent system for improving adherence to the guidelines on the assessment and treatment of acute stroke patients., Methods: Decision-making rules and data elements were used to predict the severity and to treat patients according to the specialists' opinions and guidelines. A system was then developed based on the intelligent decision-making algorithms. The system was finally evaluated by measuring the accuracy, sensitivity, specificity, applicability, performance, esthetics, information quality, and completeness and rates of medical errors. The segmented regression model was used to evaluate the effect of systems on the level and the trend of guideline adherence for the assessment and treatment of acute stroke., Results: Fifty-three data elements were identified and used in the data collection and comprehensive decision-making rules. The rules were organized in a decision tree. In our analysis, 150 patients were included. The system accuracy was 98.30%. Evaluation results indicated an error rate of 1.69% by traditional methods. Documentation quality (completeness) increased from 78.66% to 100%. The average score of system quality was 4.60 indicating an acceptable range. After the system intervention, the mean of the adherence to the guideline significantly increased from 65% to 99.5% ( P < 0.0008)., Conclusion: The designed system was accurate and can improve adherence to the guideline for the severity assessment and the determination of a therapeutic trend for acute stroke patients. It leads to physicians' empowerment, significantly reduces medical errors, and improves the documentation quality., Competing Interests: Conflicts of interest None declared., (Copyright: © 2020 Turkish Journal of Emergency Medicine.)

Background: Physical limitations, distance, and time are major obstacles to access to mental health services for veterans and soldiers. This study was aimed at comparing the efficacy of telepsychiatry and face-to-face consultation as methods of treating post-traumatic stress disorder (PTSD). The comparison was based on treatment costs, access to health services, completion of therapy sessions, and patient satisfaction as variables., Methods: This research was a double blinded clinical trial supported by Tabriz University of Medical Sciences and conducted in 2015 to 2016 in Tabriz, Iran. Totally, 60 patients were included in the study. Through simple randomization, the patients were divided into experimental and control groups, both of whom were treated through face-to-face consultations for the first 3 sessions. Six follow-up sessions were then held remotely with the experimental group and face to face with the control group. Data were collected using a self-designed and reliable questionnaire and entered in SPSS, version 16. Intergroup comparisons were performed using descriptive statistical measures. Finally, the results were tested using the t test method., Results: A significant relationship was found between the use of information technology and increased patient satisfaction, completion of therapy sessions, and reduction in treatment costs; however, no significant difference was found between the groups in terms of reduction in waiting time and access to a psychiatrist., Conclusion: Telepsychiatry is an effective means of delivering mental health services to psychiatric outpatients living in remote areas with limited resources. The results provide preliminary support for the use of telepsychiatry in treating PTSD and improving access to care. Trial Registration Number: IRCT2016020826449N1.

Background: Scoliosis is a three-dimensional deformity of the spine. It is usually assessed by measuring Cobb angle. Nowadays, due to increasing effectiveness of image processing and machine vision, willingness to apply these methods has improved considerably in determining scoliosis of Cobb angle., Methods: In accordance with the PRISMA guideline, a broad electronic search of all English language literature was conducted on the topic through four databases, including MEDLINE, Web of Science, Scopus, and the Cochrane Library from 2012 (last search date from earlier review) to 30 March 2017., Results: Twelve studies were included. 90% labeled high-quality were selected for analysis. Eighty percent of the selected studies were published in the period between 2012 and 2017. Three new procedures were used to measure the Cobb angle. One study used automated procedure (7%), two studies used smartphone procedure (14%), and nine studies used the semiautomatic procedure of Cobb measurement (79%). Seven studies reported reproducibility and repeatability. Reproducibility range was 0.72 to 1 in reporting of ICC. Repeatability has a high range in three separated methods., Conclusion: Computerized assessment method (Automatic and Semi-automatic) is most commonly performed in Cobb measurement. Semi-automatic is an effective measurement option for computerized assessment Cobb angle. There is no significant difference between manual, computer- based, and smartphone-based methods in described measures., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background: Success of infection treatment depends on the availability of accurate, reliable, and comprehensive data, information, and knowledge at the point of therapeutic decision-making. The identification of a national minimum data set will support the development and implementation of an effective surveillance system. The goal of this study was to develop a national antimicrobial resistance surveillance minimum data set., Methods: In this cross-sectional and descriptive study, data were collected from selected pioneering countries and organizations which have national or international antimicrobial resistance surveillance systems. A minimum data set checklist was extracted and validated. The ultimate data elements of the minimum data set were determined by applying the Delphi technique., Results: Through the Delphi technique, we obtained 80 data elements in 8 axes. The resistance data categories comprised basic, clinical, electronic reporting, infection control, microbiology, pharmacy, World Health Organization-derived, and expert-recommended data. Relevance coding was extracted based on the Iranian electronic health record coding system., Conclusion: This study provides a set of data elements and a schematic framework for the implementation of an antimicrobial resistance surveillance system. A uniform minimum data set was created based on key informants' opinions to cover essential needs in the early implementation of a global antimicrobial resistance surveillance system in Iran.

Introduction: Neonatal intensive care units (NICUs) have complex patients in terms of their diagnoses and required treatments. Antimicrobial treatment is a common therapy for patients in NICUs. To solve problems pertaining to empirical therapy, antimicrobial stewardship programs have recently been introduced. Despite the success of these programs in terms of data collection, there is still inefficiency in terms of analyzing and reporting the data. Thus, to successfully implement these stewardship programs, the design of antimicrobial resistance (AMR) surveillance systems is recommended as a first step. As a result, this study aimed to design an AMR surveillance system for use in the NICUs in northwestern Iranian hospitals to cover these information gaps., Methods: The recommended system is compatible with the World Health Organization (WHO) guidelines. The business intelligence (BI) requirements were extracted in an interview with a product owner (PO) using a valid and reliable checklist. Following this, an AMR surveillance system was designed and evaluated in relation to user experiences via a user experience questionnaire (UEQ). Finally, an association analysis was performed on the database, and the results were reported by identifying the important multidrug resistances in the database., Results: A customized software development methodology was proposed. The three major modules of the AMR surveillance are the data registry, dashboard, and decision support modules. The data registry module was implemented based on a three-tier architecture, and the Clinical Decision Support System (CDSS) and dashboard modules were designed based on the BI requirements of the Scrum product owner (PO). The mean values of UEQ measures were in a good range. This measures showed the suitable usability of the AMR surveillance system., Conclusion: Applying efficient software development methodologies allows for the systems' compatibility with users' opinions and requirements. In addition, the construction of interdisciplinary communication models for research and software engineering allows for research and development concepts to be used in operational environments., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objectives: Fast and accurate patient triage for the response process is a critical first step in emergency situations. This process is often performed using a paper-based mode, which intensifies workload and difficulty, wastes time, and is at risk of human errors. This study aims to design and evaluate a decision support system (DSS) to determine the triage level., Methods: A combination of the Rule-Based Reasoning (RBR) and Fuzzy Logic Classifier (FLC) approaches were used to predict the triage level of patients according to the triage specialist's opinions and Emergency Severity Index (ESI) guidelines. RBR was applied for modeling the first to fourth decision points of the ESI algorithm. The data relating to vital signs were used as input variables and modeled using fuzzy logic. Narrative knowledge was converted to If-Then rules using XML. The extracted rules were then used to create the rule-based engine and predict the triage levels., Results: Fourteen RBR and 27 fuzzy rules were extracted and used in the rule-based engine. The performance of the system was evaluated using three methods with real triage data. The accuracy of the clinical decision support systems (CDSSs; in the test data) was 99.44%. The evaluation of the error rate revealed that, when using the traditional method, 13.4% of the patients were miss-triaged, which is statically significant. The completeness of the documentation also improved from 76.72% to 98.5%., Conclusions: Designed system was effective in determining the triage level of patients and it proved helpful for nurses as they made decisions, generated nursing diagnoses based on triage guidelines. The hybrid approach can reduce triage misdiagnosis in a highly accurate manner and improve the triage outcomes., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objectives: The threat of antimicrobial resistance (AMR) is growing rapidly, perhaps more dramatically in developing countries. A demand to monitor, surveil and predict AMR has prompted the design and implementation of AMR surveillance systems (AMRSSs) at all geographic levels, especially in the national context. This study reviewed AMRSSs in leading countries and organisations in order to customise a comprehensive framework for a national system in Iran., Methods: The research was conducted in two phases: a review of the literature and comparative analysis; and a knowledge, attitude and practice study. In the first phase, the AMRSSs of pioneering organisations and countries were reviewed by examining related documents. In the second phase, important components for the Iranian national system were determined on the basis of the World Health Organization's Global Antimicrobial Resistance Surveillance System (WHO GLASS)., Results: This study determined the surveillance methods, priority specimens and pathogens, testing methods, reporting protocols and scheduling, recommended data sets, and tools and information flow necessary for the Iranian system. On this basis, a national framework was developed using the class and activity diagrams in Unified Modelling Language. A context diagram was also designed on the basis of a generic biosurveillance architecture., Conclusions: The design and implementation of a national AMRSS for Iranian healthcare facilities is critically required because of irrational antimicrobial use in Iran and insufficient data regarding its consequences., (Copyright © 2017 International Society for Chemotherapy of Infection and Cancer. Published by Elsevier Ltd. All rights reserved.)

Competing Interests: Conflict of Interests The authors declare that there is no conflict of interests.

Background: Data mining, a new concept introduced in the mid-1990s, can help researchers to gain new, profound insights and facilitate access to unanticipated knowledge sources in biomedical datasets. Many issues in the medical field are concerned with the diagnosis of diseases based on tests conducted on individuals at risk. Early diagnosis and treatment can provide a better outcome regarding the survival of lung cancer patients. Researchers can use data mining techniques to create effective diagnostic models. The aim of this study was to evaluate patterns existing in risk factor data of for mortality one year after thoracic surgery for lung cancer. Methods: The dataset used in this study contained 470 records and 17 features. First, the most important variables involved in the incidence of lung cancer were extracted using knowledge discovery and datamining algorithms such as naive Bayes, maximum expectation and then, using a regression analysis algorithm, a questionnaire was developed to predict the risk of death one year after lung surgery. Outliers in the data were excluded and reported using the clustering algorithm. Finally, a calculator was designed to estimate the risk for one-year post-operative mortality based on a scorecard algorithm. Results: The results revealed the most important factor involved in increased mortality to be large tumor size. Roles for type II diabetes and preoperative dyspnea in lower survival were also identified. The greatest commonality in classification of patients was Forced expiratory volume in first second (FEV1), based on levels of which patients could be classified into different categories. Conclusion: Development of a questionnaire based on calculations to diagnose disease can be used to identify and fill knowledge gaps in clinical practice guidelines., (Creative Commons Attribution License)

Objective: To systematically review the current literature of simulation in healthcare including the structured steps in the emergency healthcare sector by proposing a framework for simulation in the emergency department., Methods: For the purpose of collecting the data, PubMed and ACM databases were used between the years 2003 and 2013. The inclusion criteria were to select English-written articles available in full text with the closest objectives from among a total of 54 articles retrieved from the databases. Subsequently, 11 articles were selected for further analysis., Results: The studies focused on the reduction of waiting time and patient stay, optimization of resources allocation, creation of crisis and maximum demand scenarios, identification of overcrowding bottlenecks, investigation of the impact of other systems on the existing system, and improvement of the system operations and functions. Subsequently, 10 simulation steps were derived from the relevant studies after an expert's evaluation., Conclusion: The 10-steps approach proposed on the basis of the selected studies provides simulation and planning specialists with a structured method for both analyzing problems and choosing best-case scenarios. Moreover, following this framework systematically enables the development of design processes as well as software implementation of simulation problems.

Background: Chronic Obstructive Pulmonary Disease (COPD) is the most common known complication of exposure to mustard gas. Thus, all clinical guidelines have provided some recommendation for diagnosis, clinical management and treatment of this disease. Decision support systems are used to increase the acceptance of clinical guidelines. The purpose of this research is to develop a CDSS to determine the severity of COPD in chemical injured victims., Objectives: Development of a decision support system to determine the severity of COPD., Patients and Methods: First, the variables influencing to determining the severity of the disease was classified through studying the clinical guidelines. Then, the fuzzy model was implemented. To testing the system, the data from 50 patients were used., Results: the overall accuracy in determining the severity of the injury is equal to 92%, these indicators reflect the proper functioning of the system to assist the physician regarding the diagnosis of chronic obstructive pulmonary disease and determining its severity., Conclusions: The CDSS has efficient results and satisfactory performance. Although, the medical expert systems cannot be expected to provide 100 percent correct responses, however, they can be useful in the areas of patient management, diagnosis and treatment planning.

More than 9 million neonatal deaths are reported through out the world each year happening in the early weeks of life most of which relate to developing countries. Thus it is very important to present a better way to keep the infants healthy which could be possible by accessing accurate information at any time required during hospitalization of infants. Therefore the required data should be collected, stored and analyzed before which is best possible by using computer. The main objective of this research is enabling researchers and clinicians quick access to the data of the babies admitted in NICU. This study involves the stage of developing a system design and its implementation following the evaluation of the electronic records which is done in a query form. By defining the neccessary terminology and designing a data model, the database and user interface are developed by using a programing language and data base tools. Finally, the system has been evaluated by user satisfaction showing to be about 85% As a result we suggest the hospitals take serious in buying the suitable technology for the NICU ward along with teaching the staffs how to work with it.