Assessing the Landscape of Telehealth Interventions for Women's Health: An Umbrella Review of Recent Advances Post-Pandemic.

This umbrella review aims to provide a comprehensive overview of the use of telehealth services for women after the COVID-19 pandemic. The review synthesizes findings from 21 reviews, covering diverse topics such as cancer care, pregnancy and postpartum care, general health, and specific populations. While some areas have shown promising results, others require further research to better understand the potential of digital health interventions. The review identifies gaps in knowledge and highlights the need for more rigorous and comprehensive research to address the limitations and gaps identified in the current evidence base. This includes prioritizing the use of standardized guidelines, quality assessment tools, and meta-analyses, as well as exploring the comparative effectiveness of different digital health interventions, the experiences of specific populations, and the cost-effectiveness of these technologies. By addressing these gaps, this umbrella review can inform future research and policy decisions, ultimately improving women's health outcomes in the post-pandemic era.

Telehealth interventions during COVID-19 pandemic: a scoping review of applications, challenges, privacy and security issues.

BACKGROUND: The COVID-19, caused by the SARS-CoV-2 virus, proliferated worldwide, leading to a pandemic. Many governmental and non-governmental organisations and research institutes are contributing to the COVID-19 fight to control the pandemic. MOTIVATION: Numerous telehealth applications have been proposed and adopted during the pandemic to combat the spread of the disease. To this end, powerful tools such as artificial intelligence (AI)/robotic technologies, tracking, monitoring, consultation apps and other telehealth interventions have been extensively used. However, there are several issues and challenges that are currently facing this technology. OBJECTIVE: The purpose of this scoping review is to analyse the primary goal of these techniques; document their contribution to tackling COVID-19; identify and categorise their main challenges and future direction in fighting against the COVID-19 or future pandemic outbreaks. METHODS: Four digital libraries (ACM, IEEE, Scopus and Google Scholar) were searched to identify relevant sources. Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) was used as a guideline procedure to develop a comprehensive scoping review. General telehealth features were extracted from the studies reviewed and analysed in the context of the intervention type, technology used, contributions, challenges, issues and limitations. RESULTS: A collection of 27 studies were analysed. The reported telehealth interventions were classified into two main categories: AI-based and non-AI-based interventions; their main contributions to tackling COVID-19 are in the aspects of disease detection and diagnosis, pathogenesis and virology, vaccine and drug development, transmission and epidemic predictions, online patient consultation, tracing, and observation; 28 telehealth intervention challenges/issues have been reported and categorised into technical (14), non-technical (10), and privacy, and policy issues (4). The most critical technical challenges are: network issues, system reliability issues, performance, accuracy and compatibility issues. Moreover, the most critical non-technical issues are: the skills required, hardware/software cost, inability to entirely replace physical treatment and people's uncertainty about using the technology. Stringent laws/regulations, ethical issues are some of the policy and privacy issues affecting the development of the telehealth interventions reported in the literature. CONCLUSION: This study provides medical and scientific scholars with a comprehensive overview of telehealth technologies' current and future applications in the fight against COVID-19 to motivate researchers to continue to maximise the benefits of these techniques in the fight against pandemics. Lastly, we recommend that the identified challenges, privacy, and security issues and solutions be considered when designing and developing future telehealth applications.

Artificial Intelligence for Detecting and Quantifying Fatty Liver in Ultrasound Images: A Systematic Review.

BACKGROUND: Non-alcoholic Fatty Liver Disease (NAFLD) is growing more prevalent worldwide. Although non-invasive diagnostic approaches such as conventional ultrasonography and clinical scoring systems have been proposed as alternatives to liver biopsy, their efficacy has been called into doubt. Artificial Intelligence (AI) is now combined with traditional diagnostic processes to improve the performance of non-invasive approaches. OBJECTIVE: This study explores how well various AI methods function and perform on ultrasound (US) images to diagnose and quantify non-alcoholic fatty liver disease. METHODOLOGY: A systematic review was conducted to achieve this objective. Five science bibliographic databases were searched, including PubMed, Association for Computing Machinery ACM Digital Library, Institute of Electrical and Electronics Engineers IEEE Xplore, Scopus, and Google Scholar. Only peer-reviewed English articles, conferences, theses, and book chapters were included. Data from studies were synthesized using narrative methodologies per Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. RESULTS: Forty-nine studies were included in the systematic review. According to the qualitative analysis, AI significantly enhanced the diagnosis of NAFLD, Non-Alcoholic Steatohepatitis (NASH), and liver fibrosis. In addition, modalities, image acquisition, feature extraction and selection, data management, and classifiers were assessed and compared in terms of performance measures (i.e., accuracy, sensitivity, and specificity). CONCLUSION: AI-supported systems show potential performance increases in detecting and quantifying steatosis, NASH, and liver fibrosis in NAFLD patients. Before real-world implementation, prospective studies with direct comparisons of AI-assisted modalities and conventional techniques are necessary.

Building a cloud-based data sharing model for the Saudi national registry for implantable medical devices: Results of a readiness assessment.

BACKGROUND: Implantable medical device registries are used as a medium to conduct post-marketing surveillance. Little information is available on the development and implementation of implantable biomedical device registries in general and specifically in Saudi Arabia and the Middle East. OBJECTIVES: This study presents the experiences of building an implantable medical device registry in the Kingdom of Saudi Arabia. The work specifically addresses the early experiences of the Saudi Food and Drug Authority in the planning and development of a data sharing model for the implementation of a medical device registry at different hospital sites within the country. METHODS: A two-year case study in which 60 health professionals from 5 hospitals in Saudi Arabia participated in a readiness assessment survey. The readiness assessment examined system-level capacity, hospital workflow and operations, clinical staff-level engagement, and technological assessment as they relate to the implementation of the Implantable Medical Device Registry (IMDR). Both subjective and objective data were collected as part of the readiness assessment survey at each hospital site. Data was collected from participants either individually or as part of a group at each hospital site. Using Microsoft Excel, Microsoft Word, flip charts, and back-and-forth discussion, the data was descriptively summarized and synthesized to provide an overview of hospital readiness for IMDR implementation. RESULTS: Results show that there are large differences among Saudi hospitals in terms of their readiness for IMDR implementation due to a variety of factors relating to differences in hospital-wide organizational systems, clinical practice, technological infrastructure, and data sharing capabilities. Each of the hospitals surveyed in this study had differences in how clinical biomedical implantation policies and procedures were utilized. Manual entry into the cloud-based IMDR was recommended as the most optimal data sharing model that would mitigate the differences between hospital readiness for IMDR implementation. CONCLUSION: Registries play a major role in monitoring the effectiveness of implantable biomedical devices. National standardized policies, enforced regulations, and information technology infrastructure are needed to achieve this goal. Furthermore, due to differences in hospital readiness, building a cloud-based registry system through manual data entry into the IMDR was found to be the most appropriate data sharing model that can be implemented at the national level.

Developing an Evidence-Based Clinical Dataset for the Comprehensive Implantable Medical Device Registry (CIMDR).

Medical registries are in a need of a data set that is based on clinical evidence. In 2014, the Saudi Food and Drug Administration (SFDA) launched a plan to develop the national Comprehensive Implantable Medical Device Registry (CIMDR). One of the primary goals of the CIMDR is to develop a clinical -and population- based data set. The aim of this study is to report on the process of developing the data elements for the CIMDR. We used an iterative process of multi-stakeholder consultation over a two year period (2014-2016). The goal of the multi-stakeholder consultations was to build a dataset to address the need for device traceability, effectiveness, safety, and the recall of implantable medical devices. We investigated international and local standards for implantable medical device information capture, conducted a review of the literature, and consulted expert opinions in the development of the CIMDR dataset. The CIMDR data framework includes demographics, patient history, diagnosis, procedure information, and follow-up details for orthopedic and cardiac related implantable medical devices. Most of the dataset elements are logically validated with minimal free text entry to avoid human error and facilitate ease of entry. We use the International Classification for Diseases-Australian Modification as the standardized nomenclature for the CIMDR.

Developing a Policy and Procedure Framework and Manual for a National Comprehensive Implantable Medical Device Registry in Saudi Arabia.

Policy and procedure manuals provide guidance on the operation and governance of medical device registries. In Saudi Arabia, the Saudi Food and Drug Authority (SFDA) has been developing and implementing a comprehensive national registry for implantable medical devices to facilitate the monitoring of device outcomes through post-market surveillance studies. To help guide the operations of this registry, the SFDA developed a policy and procedure manual. This paper reports on the design of the framework used to develop that manual over the course of one year (2015-2016), using a variety of literature sources, and working with medical device registry and health systems experts. The policy and procedure manual included five key principal level categories, which led to the subsequent creation of seven policies and 28 relevant procedures. The five principal categories were: Staff Engagement, Information Governance, Quality and Auditing, Research, and Reporting. The results of this work could be used to guide the development of policies and procedures for other implantable medical device registries.