Development and evaluation of an anesthesia module for electronic medical records in the operating room: an applied developmental study.

Developing an anesthesia module in the operating room is one of the significant steps toward the implementation of electronic medical records (EMR) in health care centers. This study aimed to develop and evaluate the web based-anesthesia module of an electronic medical record Sciences, in the operating room of the Namazi Medical Training Center of Shiraz University of Medical Iran. This developmental and applied study was conducted in steps including determining the functional and non-functional requirements, designing and implementing the anesthesia module, and usability evaluation. 3 anesthesiologists, 3 anesthesiologist assistants, and 12 anesthetist nurses were included in the study as a research community. React.js, Node.js programming language to program this module, Mongo dB database, and Windows server for data management and USE standard questionnaire were used. In the anesthesia module, software quality features were determined as functional requirements and non-functional requirements included 286 data elements in 25 categories (demographic information, surgery information, laboratory results, patient graphs, consults, consent letter, physical examinations, medication history, family disease records, social record, past medical history, type of anesthesia, anesthesia induction method, airway management, monitoring, anesthesia chart, blood and fluids, blood gases, tourniquets and warmers, accessories, positions, neuromuscular reversal, transfer the patient from the operating room, complications of anesthesia and, seal/ signature). Also, after implementing the anesthesia module, results of the usability evaluation showed that 69.1% of the users agreed with the use of this module in the operating room and considered it user-friendly.

Tele-dentistry, its trends, scope, and future framework in oral medicine; a scoping review during January 1999 to December 2021.

BACKGROUND: Tele-dentistry has been increasingly used for different purposes of visit, consultation, triage, screening, and training in oral medicine. This study aims to determine the main facilitators, barriers, and participants` viewpoints of applying tele-dentistry in oral medicine and develop a framework indicating the input, process, output, and feedback. METHOD: This was a scoping review conducted in 2022 applying Arksey and O'Malley (2005) approach. Four databases including ISI web of science, PubMed, Scopus, and ProQuest were searched from January 1999 to December 2021. Inclusion criteria consisted of all original and non-original articles (reviews, editorials, letters, comments, and book chapters), and dissertations in English with a full text electronic file. Excel2016 was used for descriptive quantitative analysis and MAXQDA version 10 was applied for qualitative thematic analysis. A thematic framework was developed customizing the results of the review in a virtual mini expert panel. RESULTS: Descriptive results show that among 59 included articles, 27 (46%) have addressed the various applications of tele-dentistry during COVID-19 pandemic in the field of oral medicine. From geographical distribution perspective, most of the papers were published in Brazil (n = 13)/ 22.03%, India (n = 7)/11.86% and USA (n = 6)/10.17%. Thematic analysis shows that seven main themes of "information", "skill", "human resource", 'technical", "administrative', 'financial', and 'training and education' are explored as facilitators. 'Individual', 'environmental', 'organizational', 'regulation', 'clinical', and 'technical barriers' are also identified as main barriers of tele-dentistry in oral medicine. CONCLUSION: According to the results for using tele-dentistry services in oral medicine, a diverse category of facilitators should be considered and at the same time, different barriers should be managed. Users` satisfaction and perceived usefulness of tele-dentistry as final outcomes can be increased considering the system`s feedback and applying facilitator incentives as well as decreasing the barriers.

Evaluating the success of Iran Electronic Health Record System (SEPAS) based on the DeLone and McLean model: a cross-sectional descriptive study.

BACKGROUND: Quality dimensions are the most important criteria for predicting the success of an information system. The current study aims to evaluate the success of the Iran Electronic Health Record System (SEPAS) based on the DeLone and McLean model for information system success. METHOD: This nationwide cross-sectional study was conducted in 2021. Participants were 468 health information management personnel who had working experience with SEPAS. Data were collected using a questionnaire based on the DeLone and McLean model. The validity and reliability of the questionnaire were confirmed. Data were analyzed using SPSS 22 through descriptive and analytic analysis including t-test and ANOVA. RESULTS: Most participants were female (70.9%) and almost half of the participants mean age was between 30 and 40 years old (49.6%). The total mean of SEPAS success was 3.42 ± 0.53. According to the participants' perspectives "system quality" was the most influencing factor on SEPAS success. The least influencing factor was SEPAS "benefits". There was a significant relationship between the mean score of SEPAS success and age (p value = 0.001), Education level (p value = 0.01), and Work experience (p value < 0.001). CONCLUSION: The total mean of system success was not acceptable. SEPAS has not been much successful in providing net benefits like provision of electronic services which locate patients in the center and improve the delivery of care to them. It sounds that SEPAS is not stable enough that means crashes sometimes. Hence, considering the required infrastructures for quick response and stability is more critical, especially when healthcare providers are supposed to use the SEPAS.

Effect of a Developed Nursing Stretch Break Application on Work-Related Musculoskeletal Complications and Fatigue among Nurses: An Interventional Study.

Objective: The present study aimed to develop Nursing Stretch Break (NSB) application to relieve work-related musculoskeletal complications and fatigue among hospital nurses. Methods: This interventional study was conducted among 71 nurses (15 men and 56 women with a mean age of 33.32 ± 6.42) employed in Shiraz governmental hospitals, Southwest Iran, for four months. In this study, NSB was developed; it includes eight main menus for the user, including (1) Registration, (2) Stretches, (3) User panel, (4) Questions from the researcher, (5) About us, (6) Contact us, (7) Reports, and (8) Answers to questions. Data were collected pre and post-intervention via the Persian version of the Nordic Musculoskeletal Questionnaire (P-NMQ), the Persian version of the Multidimensional Assessment of Fatigue (P-MAF) Scale, the Persian version of the Numeric Rating Scale (P-NRS), and the Persian version of the Usefulness, Satisfaction, and Ease of use (P-USE) questionnaire. Results: NSB application usability testing showed that the mean scores of P-USE subscales were high. The prevalence of work-related musculoskeletal symptoms (WMSs) in the last 7 days in nurses' body parts, except the elbows and knees, was significantly lower after the intervention than before. In addition, the intensity of work-related musculoskeletal pain/discomfort in all body parts, except the knees, was significant relief after the intervention compared to before. The results demonstrated that the difference in the mean score of the total fatigue and its subscales, except "degree of interference with activities of daily living," was significant after the intervention compared to before. Conclusions: NSB could be a low-cost and feasible ergonomic solution to improve the nurses' musculoskeletal health.

Usability of Iranian Primary Vitiligo Patient Registry (IPVPR): A Pilot Study.

BACKGROUND: Usability is essential for the acceptance and success of vitiligo patient registry system. Poor usability could decrease system efficiency and effectiveness, and have a negative impact on using the system and providing services. This study aims to evaluate the usability of vitiligo patient registry system. METHODS: This pilot study was conducted in 2021. In total, 17 users who were working in the vitiligo ward participated in the study. System usability scale (SUS) was used to evaluate the usability of vitiligo patient registry system. RESULTS: In the usability evaluation stage, the mean score of the system usability scale was obtained as 77.79. CONCLUSION: Developing vitiligo patient registry system with high usability and making decisions based on the registered data could provide better understanding of this disease and facilitate research in this field. Application of this system and its acceptance by users could decrease costs and increase effectiveness and quality of services.

Developing a minimum data set required to create a registry system for patients with vitiligo.

Background: Vitiligo can be psychologically devastating and stigmatizing, with significant impacts on patients. As such, the early treatment and understanding of the profound psychosocial impact of this skin disease cannot be overstated. A standardized method of data collection with consistent definitions is a prerequisite for vitiligo management. Against this background, this study aimed to develop a minimum data set (MDS) for the vitiligo registry system. Materials and methods: The study was conducted in four steps in 2020 in Iran. After a comprehensive literature review to find relevant resources in English, medical records of patients with vitiligo were examined to assess the status quo of the country. Then, a model was developed from the data obtained in the previous step and through interviews. To reach a consensus on the data items, the Delphi technique was applied using a questionnaire, and the mean of expert judgments on each data item was calculated. Results: A total of 127 data elements were developed through two rounds of the Delphi technique. The MDS was divided into an administrative part with three sections and 18 data items, and a clinical part with seven sections and 109 data items. Conclusion: This study is the first step towards establishing a registry system for patients with vitiligo. Accurate identification of data items, such as MDSs, can be useful in establishing a vitiligo registry, planning, and improving the quality of patient care.

Comparison of wavelet transformations to enhance convolutional neural network performance in brain tumor segmentation.

INTRODUCTION AND GOAL TO BACKGROUND: Due to the importance of segmentation of MRI images in identifying brain tumors, various methods including deep learning have been introduced for automatic brain tumor segmentation. On the other hand, using a combination of methods can improve their performance. Among them is the use of wavelet transform as an auxiliary element in deep networks. The analysis of the requirements of such combinations has been addressed in this study. METHOD: In this developmental study, different wavelet functions were used to compress brain MRI images and finally as an auxiliary element in improving the performance of the convolutional neural network in brain tumor segmentation. RESULTS: Based on the results of the tests performed, the Daubechies1 function was most effective in enhancing network performance in segmenting MRI images and was able to balance the performance and computational overload. CONCLUSION: Choosing the wavelet function to optimize the performance of a convolutional neural network should be based on the requirements of the problem, also taking into account some considerations such as computational load, processing time, and performance of the wavelet function in optimizing CNN output in the intended task.

Work-related musculoskeletal symptoms among Iranian nurses and their relationship with fatigue: a cross-sectional study.

BACKGROUND: The present study aimed to determine the prevalence of work-related musculoskeletal symptoms (WMSs), identify potential factors associated with WMSs, and determine the association between WMSs and fatigue among nurses. METHODS: This cross-sectional study was carried out among 500 Iranian nurses. Data was gathered by the 1) Persian version of the Nordic musculoskeletal questionnaire (P-NMQ) to examine WMSs, and 2) Persian version of the Multidimensional Assessment of Fatigue (P-MAF) Scale to evaluate fatigue among the study population. Then, data was analyzed by SPSS version 21 using the χ2 test, multiple logistic regression for detection of potential factors associated with WMSs, and multiple linear regression for detection of potential factors associated with fatigue. RESULTS: Ankles/feet, lower back, knees, and shoulders had the highest prevalence of WMSs among nurses within the last 12 months prior to the study. Independent variables including age, job tenure, gender, smoking, shift work, and type of employment were significantly associated with WMSs in different body regions with odds ratios (ORs) ranging from 1.635-2.835. Moreover, WMSs in some body regions were associated with subscales of fatigue and total fatigue. CONCLUSIONS: Ergonomic and organizational interventions for fitting the job to the nurses considering demographic/occupational characteristics are highly essential to improve musculoskeletal system health and relieve fatigue.

Prediction of salivary cortisol level by electroencephalography features.

Change in cortisol affects brain EEG signals. So, the identification of the significant EEG features which are sensitized to cortisol concentration was the aim of the present study. From 468 participated healthy subjects, the salivary samples were taken to test the cortisol concentration and EEG signal recording was done simultaneously. Then, the subjects were categorized into three classes based on the salivary cortisol concentration (<5, 5-15 and >15 nmol/l). Some linear and nonlinear features extracted and finally, in order to investigate the relationship between cortisol level and EEG features, the following steps were taken on features in sequence: Genetic Algorithm, Neighboring Component Analysis, polyfit, artificial neural network and support vector machine classification. Two classifications were considered as following: state 1 categorized the subjects into three groups (three classes) and the second state put them into two groups (group 1: class 1 and 3, group 2: class 2). The best classification was done using ANN in the second state with the accuracy=94.1% while it was 92.7% in the first state. EEG features carefully predicted the cortisol level. This result is applicable to design the intelligence brain computer machines to control stress and brain performance.

Virtual reality games for rehabilitation of upper extremities in stroke patients.

INTRODUCTION: Stroke is one of the main causes of physical disability in which doing frequent and early exercise is imperative for rehabilitation. Virtual reality gaming has a high potential in rehabilitation leading to increased performance of patients. This study aimed to develop, validate and examine virtual reality games in chronic stroke patients. METHODS: This was a single before-after study. To determine the movements and content of games, 9 physiotherapists and 11 game designers were asked to participate in a questionnaire-based survey. Then, to evaluate the impact of games on rehabilitation, patients (N = 10; mean age = 52 ± 4.38) with chronic stroke were asked to play the games three times a week for four weeks. Outcomes included measurement of the ability to perform shoulder, elbow and wrist movements was performed using goniometric instrument, Modified Motor Assessment Scale (MMAS) was used to assess the functional ability of patients and muscle spasticity, and brunnstrom's stages of recovery test was also used to assess spastic and involuntary muscle movement. RESULTS: Games have positive effects on the horizontal abduction of shoulder (16.26 ± 23.94, P = 0.02), horizontal adduction of shoulder (59.24 ± 74.76, P = 0.00), supination of wrist (10.68 ± 53.52, P = 0.02), elbow flexion (0.1 ± 1.5, P = 0.00), and wrist flexion (0.06 ± 1.34, P = 0.03). However, they had no effects on the flexion of shoulder, flexion of elbow, extension of elbow, and extension of wrist (p-value> 0.05). CONCLUSIONS: The results showed that games improve the range of motion of the participants in terms of horizontal abduction and abduction of the shoulder, elbow flexion, and supination and flexion of the wrist. Due to the small sample size in this study, we recommend more studies with larger samples and a control group.

A machine learning approach identified a diagnostic model for pancreatic cancer through using circulating microRNA signatures.

Late diagnosis of pancreatic cancer (PC) due to the limited effectiveness of modern testing approaches, causes many patients to miss the chance of surgery and consequently leads to a high mortality rate. Pivotal improvements in circulating microRNA expression levels in PC patients make it possible to diagnose and treat patients at earlier stages. A list of circulating miRNAs was identified in this study using bioinformatics methods in association with pancreatic cancer through analyzing four GEO microarray datasets. The value of top miRNAs was then assessed via using a machine learning method. Taking the advantage of a combinatorial approach consisting of Particle Swarm Optimization (PSO) + Artificial Neural Network (ANN) and Neighborhood Component Analysis (NCA) iterations on a collection of top differentially expressed circulating miRNAs in PC patients, facilitated ranking them by significance. MiRNA's functional analysis in the final index was performed by predicting target genes and constructing PPI networks. Remarkably, the final model consist of miR-663a, miR-1469, miR-92a-2-5p, miR-125b-1-3p and miR-532-5p showed great diagnostic results on investigated cases and the validation set (Accuracy: 0.93, Sensitivity: 0.93, and Specificity: 0.92). Kaplan-Meier survival assessments of the top-ranked miRNAs revealed that three miRNAs, hsa-miR-1469, hsa-miR-663a and hsa-miR-532-5p, had meaningful associations with the prognosis of patients with pancreatic cancer. This miRNA index may serve as a non-invasive and potential PC diagnostic model, although experimental testing is needed.

Promotion of prehospital emergency care through clinical decision support systems: opportunities and challenges.

Clinical decision support systems are interactive computer systems for situational decision making and can improve decision efficiency and safety of care. We investigated the role of these systems in enhancing prehospital care. This narrative review included full-text articles published since 2000 that were available in databases/e-journals including Web of Science, PubMed, Science Direct, and Google Scholar. Search keywords included "clinical decision support system," "decision support system," "decision support tools," "prehospital care," and "emergency medical services." Non-journal articles were excluded. We revealed 14 relevant studies that used such a support system in prehospital emergency medical service. Owing to the dynamic nature of emergency situations, decision timing is critical. Four key factors demonstrated the ability of clinical decision support systems to improve decision-making, reduce errors, and improve the safety of prehospital emergency activity: computer-based, offer support as a natural part of the workflow, provide decision support in the time and place of decision making, and offer practical advice. The use of clinical decision support systems in prehospital care resulted in accurate diagnoses, improved patient triage and patient outcomes, and reduction of prehospital time. By improving emergency management and rescue operations, the quality of prehospital care will be enhanced.

The challenges of E-learning system: Higher educational institutions perspective.

INTRODUCTION: The development of information technology (IT) in education has led to the expansion of new teaching and learning methods at universities. Implementation of E-learning programs at Iran's universities as well as assessing the prerequisites and level of preparation of learners to attend E-learning environments require extensive study. Therefore, this study examined to investigate the challenges of E-learning system at Tehran University of Medical Sciences. METHODOLOGY: This study was a descriptive and cross-sectional one that conducted in 2016_2017. The statistical populations were all of the students that have an E-learning course in Tehran University of Medical Sciences, from whom, 300 were selected to participate in the study using a stratified random sampling method. The tool of the study was a researcher-made questionnaire. The data were analyzed through SPSS software. RESULTS: According to the findings of this study, about half of the participants (40%) had problems accessing the technology, and only 26.4% of the participants had good preparation for the use of E-learning system. Furthermore, a significant difference was found between the challenges of skill and culture of the participants (P value = 0.01). CONCLUSION: Success in the implementation of E-learning educational system as one of the main approaches in managing knowledge and educational needs of higher education organization will not be achieved without identifying the different skill, technical and cultural challenges. To overcome this challenge, establishing IT infrastructure and standards, using experiences of the leading countries in the field of E-learning, creating proper culture, and familiarizing learners and teachers to the development and use of E-learning materials are necessary.

Performance comparison of machine learning techniques in sleep scoring based on wavelet features and neighboring component analysis.

INTRODUCTION: Sleep scoring is an important step in the treatment of sleep disorders. Manual annotation of sleep stages is time-consuming and experience-relevant and, therefore, needs to be done using machine learning techniques. METHODS: Sleep-EDF polysomnography was used in this study as a dataset. Support vector machines and artificial neural network performance were compared in sleep scoring using wavelet tree features and neighborhood component analysis. RESULTS: Neighboring component analysis as a combination of linear and non-linear feature selection method had a substantial role in feature dimension reduction. Artificial neural network and support vector machine achieved 90.30% and 89.93% accuracy, respectively. DISCUSSION AND CONCLUSION: Similar to the state of the art performance, the introduced method in the present study achieved an acceptable performance in sleep scoring. Furthermore, its performance can be enhanced using a technique combined with other techniques in feature generation and dimension reduction. It is hoped that, in the future, intelligent techniques can be used in the process of diagnosing and treating sleep disorders.

Quantitative EEG features selection in the classification of attention and response control in the children and adolescents with attention deficit hyperactivity disorder.

AIM: Quantitative EEG gives valuable information in the clinical evaluation of psychological disorders. The purpose of the present study is to identify the most prominent features of quantitative electroencephalography (QEEG) that affect attention and response control parameters in children with attention deficit hyperactivity disorder. METHODS: The QEEG features and the Integrated Visual and Auditory-Continuous Performance Test ( IVA-CPT) of 95 attention deficit hyperactivity disorder subjects were preprocessed by Independent Evaluation Criterion for Binary Classification. Then, the importance of selected features in the classification of desired outputs was evaluated using the artificial neural network. RESULTS: Findings uncovered the highest rank of QEEG features in each IVA-CPT parameters related to attention and response control. CONCLUSION: Using the designed model could help therapists to determine the existence or absence of defects in attention and response control relying on QEEG.

The opportunities of virtual reality in the rehabilitation of children with attention deficit hyperactivity disorder: a literature review.

Attention deficit hyperactivity disorder (ADHD) is one of the most common psychiatric disorders in childhood. This disorder, in addition to its main symptoms, creates significant difficulties in education, social performance, and personal relationships. Given the importance of rehabilitation for these patients to combat the above issues, the use of virtual reality (VR) technology is helpful. The aim of this study was to highlight the opportunities for VR in the rehabilitation of children with ADHD. This narrative review was conducted by searching for articles in scientific databases and e-Journals, using keywords including VR, children, and ADHD. Various studies have shown that VR capabilities in the rehabilitation of children with ADHD include providing flexibility in accordance with the patients' requirements; removing distractions and creating an effective and safe environment away from real-life dangers; saving time and money; increasing patients' incentives based on their interests; providing suitable tools to perform different behavioral tests and increase ecological validity; facilitating better understanding of individuals' cognitive deficits and improving them; helping therapists with accurate diagnosis, assessment, and rehabilitation; and improving working memory, executive function, and cognitive processes such as attention in these children. Rehabilitation of children with ADHD is based on behavior and physical patterns and is thus suitable for VR interventions. This technology, by simulating and providing a virtual environment for diagnosis, training, monitoring, assessment and treatment, is effective in providing optimal rehabilitation of children with ADHD.

The design and implementation of the software tracking cervical and lumbar vertebrae in spinal fluoroscopy images.

AIM: Manual analysis of neck kinematics is usually associated with measurement errors and it requires the use of software capabilities. Considering laboratory usage, software has been developed to solve the associated problems. MATERIALS & METHODS: Fluoroscopic images taken from 78 women were used to design and evaluate the performance of the software. The software was implemented using C# language, according to the case-based reasoning technique. RESULTS: The viewpoints of experts suggest accuracy of the software in tracking and calculations, which meets their information requirements. CONCLUSION: Using the software could help physiotherapists to accomplish their work in decreased time and with improved accuracy.

The power features of Masseter muscle activity in tension-type and migraine without aura headache during open-close clench cycles.

INTRODUCTION: Different types of headaches and TMJ click influence the masseter muscle activity. The aim of this study was to assess the trend of energy level of the electromyography (EMG) activity of the masseter muscle during open-close clench cycles in migraine without aura (MOA) and tension-type headache (TTH) with or without TMJ click. METHODS: Twenty-five women with MOA and twenty four women with TTH participated in the study. They matched with 25 healthy subjects, in terms of class of occlusion and prevalence of temporomandibular joint (TMJ) with click. The EMG of both masseter muscles were recorded during open-close clench cycles at a rate of 80 cycles per minute for 15 seconds. The mouth opening was restricted to two centimeters by mandibular motion frame. Signal processing steps have been done on the EMG as: noise removing, smoothing, feature extraction, and statistical analyzing. The six statistical parameters of energy computed were mean, Variance, Skewness, Kurtosis, and first and second half energy over all signal energy. RESULTS: A three-way ANOVA indicated that during all the cycles, the mean of energy was more and there was a delay in showing the peak of energy in the masseter of the left side with clicked TMJ in MOA group compared to the two other groups, while this pattern occurred inversely in the side with no-clicked TMJ (P < 0.009). The variation of energy was significantly less in MOA group compared to the two other groups in the no-clicked TMJ (P < 0.003). However, the proportion of the first or second part of signal energy to all energy showed that TTH group had less energy in the first part and more energy in the second part in comparison to the two other groups (P < 0.05). CONCLUSION: The study showed different changes in the energy distribution of masseter muscle activity during cycles in MOA and TTH. MOA, in contrast to TTH, had lateralization effect on EMG and interacted with TMJ click.