A mobile application for postoperative education of caregivers of children with congenital hypospadias: Requirement analysis.

Background and Aims: Hypospadias, a congenital anomaly, can have long-term effects on sexual, urinary, and reproductive functions, making proper postoperative care essential for desirable outcomes, which could be facilitated through a mobile application for diseases with long-term complications. The aim of this study was to investigate the data and functional requirements or minimum data set of a postoperative education mobile application for caregivers of children with hypospadias. Methods: A literature review of papers published until April 2023 using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement was conducted to determine the data and functional requirements of a mobile application that provides postoperative education to caregivers of children with congenital hypospadias. Based on the results, a questionnaire was prepared, and its content validity and reliability were evaluated by CVI and CVR. Additionally, data was examined by 30 residents, specialists, and subspecialists in pediatric surgery using the Delphi approach. Results: The study identified 28 data elements in three main categories: demographic data, clinical data, and application function. Functional requirements of the mobile application were suggested for use in designing the application. Also, the most critical data elements included the definition of disease, the importance of treatment, surgical preparation, bandage, hygiene, symptoms and infection, bleeding, and emergency condition. Conclusion: The study will pave the way for developing postoperative educational applications for caregivers of children with congenital hypospadias. M-Health app developers and clinician specialists can utilize these findings to design practical applications that assist caregivers in managing the care of hypospadias patients.

The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials.

AIMS: Type 2 diabetes (T2D) is rising worldwide. Self-care prevents diabetic complications. Lack of knowledge is one reason patients fail at self-care. Intelligent digital health (IDH) solutions have a promising role in training self-care behaviors based on patients' needs. This study reviews the effects of RCTs offering individualized self-care training systems for T2D patients. METHODS: PubMed, Web of Science, Scopus, Cochrane Library, and Science Direct databases were searched. The included RCTs provided data-driven, individualized self-care training advice for T2D patients. Due to the repeated studies measurements, an all-time-points meta-analysis was conducted to analyze the trends over time. The revised Cochrane risk-of-bias tool (RoB 2.0) was used for quality assessment. RESULTS: In total, 22 trials met the inclusion criteria, and 19 studies with 3071 participants were included in the meta-analysis. IDH interventions led to a significant reduction of HbA1c level in the intervention group at short-term (in the third month: SMD = - 0.224 with 95% CI - 0.319 to - 0.129, p value < 0.0; in the sixth month: SMD = - 0.548 with 95% CI - 0.860 to - 0.237, p value < 0.05). The difference in HbA1c reduction between groups varied based on patients' age and technological forms of IDH services delivery. The descriptive results confirmed the impact of M-Health technologies in improving HbA1c levels. CONCLUSIONS: IDH systems had significant and small effects on HbA1c reduction in T2D patients. IDH interventions' impact needs long-term RCTs. This review will help diabetic clinicians, self-care training system developers, and researchers interested in using IDH solutions to empower T2D patients.

Evaluation Methods in Clinical Health Technologies: A Systematic Review.

Background: This study was conducted to classify the types of evaluation methods in clinical health technologies based on a systematic review method. Methods: An electronic search was conducted in three scientific databases including Scopus, PubMed and ISI. The search strategy was performed in Jul to Nov 2021 and based on the three main concepts of "evaluation", "technology", "health. This search has been restricted to 10 years (2011-2021). Moreover, it only was limited to English and papers published in journals and conferences proceeding. Results: Overall, 8149 references were identified for title and abstract screening. Full text screening was performed for 2674 articles, with 174 meeting the criteria for study inclusion. Conclusion: Most of the technologies evaluated in these articles were associated with PC-based systems (N=107), and there have been fewer mobile apps (N=67). Most of used technologies were with goals of treatment (43%, N=74) and education (26%, N=45). Among all the methods, the most and the least used methods were usability (66%, N=115) and qualitative (1%, N=2) method, respectively. The most method for health clinical technologies is usability method especially in telemedicine field.

Requirements, Challenges, and Key Components to Improve Onboard Medical Care Using Maritime Telemedicine: Narrative Review.

Introduction: Telemedicine has been able to bring healthcare services to all people in far locations such as the sea. Our main objective was to overview the main features, challenges, and requirements of applying telemedicine at sea. Methods: The electronic search includes all types of papers published in English. It was performed in four databases with keywords to Feb 2023. Next, main categories were defined to extract major concepts. By mapping extracted themes, maritime telemedicine concepts were represented in two conceptual models. Results: After screening the papers based on title and abstract, 18 articles remained. They can be divided into 13 categories based on their clinical domains. Out of 18 reviewed articles, six articles were published in 2020. The greatest number of studies with five articles was conducted in France. Evidence showed that maritime telemedicine service can be provided to all kinds of ships. Regarding clinical domains, the greatest demand belonged to primary care problems (5 papers) and general health assessment (4 papers). Challenges were divided into four main categories. Moreover, the required services and equipment in four categories were described too. Finally, a conceptual model is represented for providing telemedicine services at sea using satellite Internet. Conclusion: Despite the existing challenges in providing the required equipment and resources for the implementation of maritime medicine, it has an important role in providing better care for seafarers without time limitations.

Predicting the toxicity of nanoparticles using artificial intelligence tools: a systematic review.

Nanoparticles have been used extensively in different scientific fields. Due to the possible destructive effects of nanoparticles on the environment or the biological systems, their toxicity evaluation is a crucial phase for studying nanomaterial safety. In the meantime, experimental approaches for toxicity assessment of various nanoparticles are expensive and time-consuming. Thus, an alternative technique, such as artificial intelligence (AI), could be valuable for predicting nanoparticle toxicity. Therefore, in this review, the AI tools were investigated for the toxicity assessment of nanomaterials. To this end, a systematic search was performed on PubMed, Web of Science, and Scopus databases. Articles were included or excluded based on pre-defined inclusion and exclusion criteria, and duplicate studies were excluded. Finally, twenty-six studies were included. The majority of the studies were conducted on metal oxide and metallic nanoparticles. In addition, Random Forest (RF) and Support Vector Machine (SVM) had the most frequency in the included studies. Most of the models demonstrated acceptable performance. Overall, AI could provide a robust, fast, and low-cost tool for the evaluation of nanoparticle toxicity.

Evaluation of overweight control applications with cognitive-behavioral therapy approach: A systematic review.

Background and Aims: Overweight and obesity lead to the development of physical diseases. Cognitive factors play a vital role in controlling one's weight. Currently, cognitive-behavioral therapy (CBT) interventions are recognized as a subcategory of lifestyle modification programs that can be implemented to control weight and modify eating patterns as well as physical activity. Nowadays, smartphone-based applications are utilized to implement behavioral interventions. The main purpose of this study is to evaluate the quality of CBT-based smartphone applications available on Google Play and the App Store in the field of overweight control. Methods: Smartphone-based utility applications available on Google Play and App Store were identified in March 2021. Weight control smartphone applications were obtained based on inclusion and exclusion criteria. The app name, platform, version, number of downloads, password protection, affiliations, and features of retrieved apps were tabulated. The Mobile Application Rating Scale was utilized to evaluate the quality of the identified apps. Results: Seventeen CBT-based weight control smartphone apps were retrieved. The average engagement, functionality, aesthetics, and information quality scores were 3.65, 3.92, 3.80, and 3.91, respectively. Also, the average score in an aspect containing the usefulness of the app, frequency of using the application, cost, and user satisfaction was 3.5. Conclusion: Future applications related to this field can be improved by providing a personalization program according to the needs of users and the possibility of online chatting with the therapist. Further improvements can be achieved by improving the areas of engagement, aesthetics, and subjective quality as well as having appropriate privacy policies.

Remote Monitoring of Colorectal Cancer Survivors Using a Smartphone App and Internet of Things-Based Device: Development and Usability Study.

BACKGROUND: Patients with colorectal cancer who undergo surgery face many postoperative problems. These problems include the risk of relapse, side effects, and long-term complications. OBJECTIVE: This study sought to design and develop a remote monitoring system as a technological solution for the postdischarge care of these patients. METHODS: This research was conducted in 3 main steps: system feature extraction, system design, and evaluation. After feature extraction from a systematic review, the necessary features were defined by 18 clinical experts in Iran. In the next step, the architecture of the system was designed based on the requirements; the software and hardware parts of the system were embedded in the architecture, then the software system components were drawn using the unified modeling language diagrams, and the details of software system implementation were identified. Regarding the hardware design, different accessible hardware modules were evaluated, and suitable ones were selected. Finally, the usability of the system was evaluated by demonstrating it over a Skype virtual meeting session and using Nilsen's usability principles. RESULTS: A total of 21 mandatory features in 5 main categories, including patient information registration, periodic monitoring of health parameters, education, reminders, and assessments, were defined and validated for the system. The software was developed using an ASP.Net core backend, a Microsoft SQL Server database, and an Ionic frontend alongside the Angular framework, to build an Android app. The user roles of the system included 3 roles: physicians, patients, and the system administrator. The hardware was designed to contain an Esp8266 as the Internet of Things module, an MLX90614 infrared temperature sensor, and the Maxim Integrated MAX30101 sensor for sensing the heartbeat. The hardware was designed in the shape of a wristband device using SolidWorks 2020 and printed using a 3D printer. The firmware of the hardware was developed in Arduino with the capability of firmware over the air. In evaluating the software system from the perspective of usability, the system received an average score of 3.8 out of 5 from 4 evaluators. CONCLUSIONS: Sensor-based telemonitoring systems for patients with colorectal cancer after surgery are possible solutions that can make the process automatic for patients and caregivers. The apps for remote colorectal patient monitoring could be designed to be useful; however, more research regarding the developed system's implementation in clinic settings and hospitals is required to understand the probable barriers and limitations.

The application of wearable smart sensors for monitoring the vital signs of patients in epidemics: a systematic literature review.

Wearable smart sensors are emerging technology for daily monitoring of vital signs with the reducing discomfort and interference with normal human activities. The main objective of this study was to review the applied wearable smart sensors for disease control and vital signs monitoring in epidemics outbreaks. A comprehensive search was conducted in Web of Science, Scopus, IEEE Library, PubMed and Google Scholar databases to identify relevant studies published until June 2, 2020. Main extracted specifications for each paper are publication details, type of sensor, disease, type of monitored vital sign, function and usage. Of 277 articles, 11 studies were eligible for criteria. 36% of papers were published in 2020. Articles were published in 10 different journals and only in the Journal of Medical Systems more than one article was published. Most sensors were used to monitor body temperature, heart rate and blood pressure. Wearable devices (like a helmet, watch, or cuff) and body area network sensors were popular types which can be used monitoring vital signs for epidemic trending. 65% of total papers (n = 6) were conducted by the USA, Malaysia and India. Applying appropriate technological solutions could improve control and management of epidemic disease as well as the application of sensors for continuous monitoring of vital signs. However, further studies are needed to investigate the real effects of these sensors and their effectiveness.

Telemedicine for Patient Management in Remote Areas and Underserved Populations.

Access to care services in remote areas is challenging. The use of telemedicine technology in these areas facilitates access to health care. This study aimed to summarize the current research on telemedicine in remote areas such as mountains and forests. A systematic search was conducted in databases including Medline (through PubMed), Scopus, IEEE Xplore Digital Library, and ISI Web of Science to identify relevant studies published until May 12, 2021. Screening of retrieved articles for selection and inclusion in the study was performed based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes extension for Scoping Reviews (PRISMA-ScR) checklist. A total of 807 articles were identified after removing duplicates, from which 20 studies meeting our inclusion criteria were selected. Challenges, opportunities, and equipment required to use telemedicine in remote areas were extracted from the selected studies. The results revealed that telemedicine implementation in remote areas had many challenges, including harsh weather conditions, Internet connectivity problems, difficult equipment transportation, and ethical issues. Telemedicine also has many benefits, such as cost and time savings for patients, improving patients' quality of life, and improving patient satisfaction. Telemedicine for inhabitants of forested and mountainous areas facilitates rapid access to health care and enhances patient satisfaction. Distinguishing advantages and barriers as well as reducing restrictions will have an essential role in accelerating the use of this technology.

A systematic review of the predicted outcomes related to hematopoietic stem cell transplantation: focus on applied machine learning methods' performance.

INTRODUCTION: Hematopoietic stem cell transplantation (HSCT) is a critical therapeutic procedure in blood diseases, and the investigation of HSCT data can provide valuable information. Machine learning (ML) techniques are useful data analysis tools which applied in many studies to predict HSCT survival and estimate the risk of transplantation. AREAS COVERED: A systematic review was performed with a search of PubMed, Science Direct, Embase, Scopus, and the European Society for Blood and Marrow Transplantation, the Center for International Blood and Marrow Transplant Research, and the American Society for Transplantation and Cellular Therapy publications for articles published by September 2020. EXPERT OPINION: 24 papers that met eligibility criteria were included in this study. The applied ML algorithms with the highest performance were Random Survival Forests (AUC = 0.72) for survival-related, Random Survival Forests and Logistic Regression (AUC = 0.77) for mortality-related, Deep Learning (AUC = 0.8) for relapse, L2-Regularized Logistic Regression (AUC = 0.66) for Acute-Graft Versus Host Disease, Random Survival Forests (AUC = 0.88) for sepsis, Elastic-Net Regression (AUC = 0.89) for cognitive impairment, and Bayesian Network (AUC = 0.997) for oral mucositis outcome. This review reveals the potential of ML techniques to predict HSCT outcomes and apply them to developing clinical decision support systems.

A Smartphone Remote Monitoring App to Follow Up Colorectal Cancer Survivors: Requirement Analysis.

BACKGROUND: Colorectal cancer survivors face multiple challenges after discharge. eHealth may potentially support them by providing tools such as smartphone apps. They have lots of capabilities to exchange information and could be used for remote monitoring of these patients. OBJECTIVE: In this study, we addressed the required features for apps designed to follow up colorectal cancer patients based on survivors' and clinical experts' views. METHODS: A mixed methods study was conducted. Features of related apps were extracted through the literature; the features were categorized, and then, they were modified. A questionnaire was designed containing the features listed and prioritized based on the MoSCoW (Must have, Should have, Could have, Won't have) technique and an open question for each category. The link to the questionnaire was shared among clinical experts in Iran. The answers were analyzed using the content validity ratio (CVR), and based on the value of this measure, the minimum feature set of a monitoring app to follow up patients with colorectal cancer was addressed. In addition, a telephone interview with colorectal cancer survivors was conducted to collect their viewpoints regarding a remote monitoring system for colorectal cancer cases. RESULTS: The questionnaire contained 10 sections evaluating 9 categories of features. The questionnaire was completed by 18 experts. The minimum set of features in the app was identified as patient information registration, sign and symptom monitoring, education, reminders, and patient evaluation (0.42 < CVR < 0.85). Features including physical activity, personalized advice, and social network did not achieve the minimum score (-0.11 < CVR < 0.39). We interviewed 9 colorectal cancer survivors. Information registration, sign and symptom monitoring, education, and personalized advice were the features with high priority from the survivors' perspectives. Scheduling, shopping, and financial support features were emphasized by survivors in the interview. CONCLUSIONS: The requirement set could be used to design an app for the targeted population or patients affected by other cancers. As the views from both survivors and clinical experts were considered in this study, the remote system may more adequately fulfill the need for follow-up of survivors. This eases the patients' and health care providers' communication and interaction.

Telecardiology interventions for patients with cardiovascular Disease: A systematic review on characteristics and effects.

INTRODUCTION: The prevalence and mortality of cardiovascular diseases are high worldwide. Telecardiology can be used to diagnose and treat these diseases. This paper aimed to review the effectiveness (positive and negative) of implemented telecardiology services in terms of clinical, economic, and patient-reported aspects. METHODS: A comprehensive search was conducted in Medline (through PubMed), Scopus, ISI web of science, and IEEE Xplore databases from inception to April 7, 2021. the studies that examined the effectiveness of telecardiology interventions were included. RESULTS: Fifty studies were included in this systematic review. Most investigations (22%) were conducted in the US. In 22% of studies, telecardiology intervention was used for patients with heart failure. Telecardiology has been used in most studies for tele-monitoring (n = 21, 42%) and tele-consultation (n = 17, 34%) and in 29 studies (58%), was applied for ECG transmission. The highest rate of effects reported by studies was clinical. Thirty-five studies (70%) reported the clinical effects; twenty-one studies reported the positive effects for the economic category, and fifteen studies reported the positive effect for patient-reported class. The most positive clinical effects of telecardiology were early diagnosis, early treatment, and mortality reduction. The most positive effect of the economic class was the reduction of health care costs. The most effects of the patient-reported category were improving the patient's quality of life and patient satisfaction. CONCLUSION: Telecardiology can help early diagnosis and treatment of cardiovascular diseases. It also has great potential in reducing health care costs and increasing quality of life and patient satisfaction.

Timely Diagnosis of Acute Lymphoblastic Leukemia Using Artificial Intelligence-Oriented Deep Learning Methods.

BACKGROUND: Leukemia is fatal cancer in both children and adults and is divided into acute and chronic. Acute lymphoblastic leukemia (ALL) is a subtype of this cancer. Early diagnosis of this disease can have a significant impact on the treatment of this disease. Computational intelligence-oriented techniques can be used to help physicians identify and classify ALL rapidly. Materials and Method. In this study, the utilized dataset was collected from a CodaLab competition to classify leukemic cells from normal cells in microscopic images. Two famous deep learning networks, including residual neural network (ResNet-50) and VGG-16 were employed. These two networks are already trained by our assigned parameters, meaning we did not use the stored weights; we adjusted the weights and learning parameters too. Also, a convolutional network with ten convolutional layers and 2∗2 max-pooling layers-with strides 2-was proposed, and six common machine learning techniques were developed to classify acute lymphoblastic leukemia into two classes. RESULTS: The validation accuracies (the mean accuracy of training and test networks for 100 training cycles) of the ResNet-50, VGG-16, and the proposed convolutional network were found to be 81.63%, 84.62%, and 82.10%, respectively. Among applied machine learning methods, the lowest obtained accuracy was related to multilayer perceptron (27.33%) and highest for random forest (81.72%). CONCLUSION: This study showed that the proposed convolutional neural network has optimal accuracy in the diagnosis of ALL. By comparing various convolutional neural networks and machine learning methods in diagnosing this disease, the convolutional neural network achieved good performance and optimal execution time without latency. This proposed network is less complex than the two pretrained networks and can be employed by pathologists and physicians in clinical systems for leukemia diagnosis.

Evaluation of M-Health Applications Use in Epilepsy: A Systematic Review.

BACKGROUND: Epilepsy is a neurological disorder characterized by seizures and recurrent attacks. Self-management leads to seizure control and maximizes the quality of life in epileptic patients. The purpose of this study was to evaluate the quality of applications available in the epileptic google play store based on the rating features of MARS (Mobile Applications Rating Scale). METHODS: The search was conducted systematically using the keywords "epilepsy", "seizure", "mobile health" at the Android google play store. Data were extracted and analyzed from Feb 2018 to Apr 2019. RESULTS: Accordingly, 45 apps were identified potentially relevant of which 20 met inclusion criteria. Twenty-five apps were excluded because they were unrelated to epilepsy self-management, or not Development for people with epilepsy, not in English language or were not free and available. The total mean MARS score was 3.21 out of 5, and more than half of apps (17, 85%) had a minimum acceptability score of 3.0. The mean of apps' items were 3.27 in Engagement, 3.96 in function, 3.30 in Aesthetics, 2.96 in Information and 2.73 in subjective quality items. CONCLUSION: Few apps meet prespecified criteria for quality, content, and functionality for epilepsy self-management. Despite the rapid evolution of self-management apps, lack of validation studies is a significant concern that limits the clinical value of these apps. Moreover, having a guideline and benchmarking in the field of mobile application development, in epilepsy management, can help analyze the content of established applications.

Management of the essential data element in the differential diagnosis of oral medicine: An effective step in promoting oral health.

BACKGROUND: Oral soft tissue diseases include a broad spectrum, and the wide array of patient data elements need to be processed in their diagnosis. One of the biggest and most basic challenges is the analysis of this huge amount of complex patient data in an increasing number of complicated clinical decisions. This study seeks to identify the necessary steps for collecting and management of these data elements through establishing a consensus-based framework. METHODS: This research was conducted as a descriptive, cross-sectional study from April 2016 to January 2017, which has been performed in several steps: literature review, developing the initial draft (v. 0), submitting the draft to experts, validating by an expert panel, applying expert opinions and creating version v.i, performing Delphi rounds, and creating the final framework. RESULTS: The administrative data category with 17 and the historical data category with 23 data elements were utilized in recording data elements in the diagnosis of all of the different oral diseases. In the paraclinical indicator and clinical indicator categories, the necessary data elements were considered with respect to the 6 main axes of oral soft tissue diseases, according to Burket's Oral Medicine: ulcerative, vesicular, and bullous lesions; red and white lesions of the oral mucosa; pigmented lesions of the oral mucosa; benign lesions of the oral cavity and the jaws; oral and oropharyngeal cancer; and salivary gland diseases. CONCLUSIONS: The study achieved a consensus-based framework for the essential data element in the differential diagnosis of oral medicine using a comprehensive search with rich keywords in databases and reference texts, providing an environment for discussion and exchange of ideas among experts and the careful use of the Delphi decision technique.

Challenges and Practical Considerations in Applying Virtual Reality in Medical Education and Treatment.

Despite the benefits of using virtual reality (VR) in medical education and treatment, some challenges and limitations result in the uselessness or misuse of this technology. Therefore, recognizing potential challenges related to VR might be helpful in the strategic decision-making process to implement and develop this technology in the healthcare field. Accordingly, our review aimed to determine the challenges associated with the application of VR in the field of medical education and treatment. We searched Science Direct, Google Scholar, and PubMed databases for relevant papers using a defined search query. We restricted the search to articles in English or Persian language published by the end of 2018. The main challenges of developing and using VR with educational and therapeutic objectives are categorized as general and specific. General challenges include reduced face-to-face communications, education, cost challenges, users' attitudes, and specific challenges such as designing, safety considerations, VR side effects, evaluation, and validation of VR applications. Challenges related to VR will have different effects, thus identifying each of them helps to determine the solutions for each challenge. Also, it is suggested to develop and update laws, standards, and protocols, which play an important role in increasing the effective application of VR at the national level.

Supporting colorectal cancer survivors using eHealth: a systematic review and framework suggestion.

PURPOSE: eHealth could potentially support colorectal cancer survivors; however, little is known regarding the overall recent eHealth systems for colorectal cancer survivors. The present study was conducted to address which types of eHealth supports have been provided to colorectal cancer survivors in the past two decades. METHODS: An electronic search was conducted in four databases including Scopus, PubMed, Embase, and Web of Science. The search query was based on two concepts: the first concept represented colorectal cancer and the second one comprised of information technology tools. The search was limited to 20 years (from 19 January 1999 to 19 January 2019). Obtained results were tabulated and represented as a framework. RESULTS: Fifteen papers were included in this systematic review. Information including intervention type, eHealth tools, main features of the system, and outcomes were extracted from selected papers. Obtained results were characterized using a four-layer framework. This framework included layers of hardware, software, service (educating the patient, medication intake, physical activity, health status monitoring, hospital visit reminder, and discussion group), and outcome. Outcome layer was composed of the following domains: quality of life, psychological and cognitive, physical activity, physical functioning, symptoms, engagement, and the outcome of the process and IT tools. CONCLUSION: eHealth could provide useful services for supporting colorectal cancer survivors. Represented framework might be used for a better understanding of current technology and services provided to support these survivors. Also, this framework may be used as a basis for designing eHealth applications for colorectal cancer survivors after further validations.

Requirement Specification and Modeling a Wearable Smart Blanket System for Monitoring Patients in Ambulance.

BACKGROUND: Nowadays, the role of smart systems and developed tools such as wearable systems for monitoring the patients and controlling their conditions consistently has increased significantly. The present research sought to identify the factors which are essential for designing a wearable smart blanket system and modeling the proposed systems. METHODS: To this aim, the requirements for creating the proposed system in ambulance were described after determining the features related to wearable systems by conducting on a comparative study. First, some studies were performed to identify the wearable system development. Then, the elicited questionnaire was given to the physicians and medical informatics specialists. Finally, the extracted requirements were implemented for modeling a smart blanket system. RESULTS: Based on the results, the wearable smart blanket system includes some specific characteristics such as monitoring the important signs, communicating with the surroundings, processing the signals instantly, and storing all important signs. In addition, they should involve some nonfunctional characteristics such as easy installment and function, interactivity, error fault tolerance, low energy consumption, and the accuracy of sign stability. Then, based on the requirements and data elements extracted from the questionnaire, the system was modeled as a detailed design of the proposed technical blanket system. Based on the results, the architecture of the designed system could provide expected scenarios by using the Active Review for Intermediate Design-oriented scenario-based evaluation method. CONCLUSION: Today, smart systems and tools have considerably developed in terms of monitoring the patients and controlling their conditions. Therefore, wearable systems can be implemented for monitoring the health status of patients in ambulance.

Design of Infertility Monitoring System: Minimum Data Set Approach.

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.