BackgroundTelemedicine applications have been increasing due to the development of new computer science technologies and of more advanced telemedical devices. Various types of telerehabilitation treatments and their relative intensities and duration have been reported.ObjectiveThe objective of this review is to provide a detailed overview of the rehabilitation techniques for remote sites (telerehabilitation) and their fields of application, with analysis of the benefits and the drawbacks related to use. We discuss future applications of telerehabilitation techniques with an emphasis on the development of high-tech devices, and on which new tools and applications can be used in the future.MethodsWe retrieved relevant information and data on telerehabilitation from books, articles and online materials using the Medical Subject Headings (MeSH) “telerehabilitation,” “telemedicine,” and “rehabilitation,” as well as “disabling pathologies.”ResultsTelerehabilitation can be considered as a branch of telemedicine. Although this field is considerably new, its use has rapidly grown in developed countries. In general, telerehabilitation reduces the costs of both health care providers and patients compared with traditional inpatient or person-to-person rehabilitation. Furthermore, patients who live in remote places, where traditional rehabilitation services may not be easily accessible, can benefit from this technology. However, certain disadvantages of telerehabilitation, including skepticism on the part of patients due to remote interaction with their physicians or rehabilitators, should not be underestimated.ConclusionsThis review evaluated different application fields of telerehabilitation, highlighting its benefits and drawbacks. This study may be a starting point for improving approaches and devices for telerehabilitation. In this context, patients’ feedback may be important to adapt rehabilitation techniques and approaches to their needs, which would subsequently help to improve the quality of rehabilitation in the future. The need for proper training and education of people involved in this new and emerging form of intervention for more effective treatment can’t be overstated.

Background: Telemedicine involves medical practice and information and communications technology. It has been proven to be very effective for remote health care, especially in areas with poor provision of health facilities. However, implementation of these technologies is often hampered by various issues. Among these, ethical and legal concerns are some of the more complex and diverse ones. In this study, an analysis of scientific literature was carried out to identify the ethical and legal challenges of telemedicine. Materials and Methods: English literature, published between 2010 and 2019, was searched on PubMed, Scopus, and Web of Science by using keywords, including ''Telemedicine,'' ''Ethics,'' ''Malpractice,'' ''Telemedicine and Ethics,'' ''Telemedicine and Informed consent,'' and ''telemedicine and malpractice.'' Different types of articles were analyzed, including research articles, review articles, and qualitative studies. The abstracts were evaluated according to the selection criteria, using the Newcastle-Ottawa Scale criteria, and the final analysis led to the inclusion of 22 articles. Discussion: From the aforementioned sample, we analyzed elements that may be indicative of the efficacy of telemedicine in an adequate time frame. Ethical aspects such as informed consent, protection data, confidentiality, physician's malpractice, and liability and telemedicine regulations were considered. Conclusions: Our objective was to highlight the current status and identify what still needs to be implemented in tele-medicine with respect to ethical and legal standards. Gaps emerged between current legislation, legislators, service providers, different medical services, and most importantly patient interaction with his/her data and the use of that data.

Background and Objectives: The term “telepharmacy” indicates a form of pharmaceutical care in which pharmacists and patients are not in the same place and can interact using information and communication technology (ICT) facilities. Telepharmacy has been adopted to provide pharmaceutical services to underserved areas and to address the problem of pharmacist shortage. This paper has reviewed the multi-faceted phenomenon of telepharmacy, summarizing different experiences in the area. Advantages and limitations of telepharmacy are discussed as well. Materials and Methods: A literature analysis was carried out on PubMed, using as entry term “telepharmacy” and including articles on the topic published between 2012 and 2018. Results: The studies reviewed were divided into three categories of pharmacy practice, namely (1) support to clinical services, (2) remote education and handling of “special pharmacies”, and (3) prescription and reconciliation of drug therapies. In general, different telepharmacy services were effective and accompanied by a satisfaction of their targets. Conclusions: Nowadays, the shortage of health personnel, and in particular pharmacists, is a challenging issue that the health systems have to face. The use of a new technology such as telepharmacy can represent a possible option to solve these problems. However, there are unsolved limitations (e.g., legal implications) that make greater diffusion of telepharmacy difficult. Stronger data on the effectiveness of this area of pharmacy care, together with a critical evaluation of its limits, can make actors involved aware about the potentialities of it and could contribute to a larger diffusion of telepharmacy services in the interest of communities and citizens.

This paper reviews applications of machine learning (ML) predictive models in the diagnosis of chronic diseases. Chronic diseases (CDs) are responsible for a major portion of global health costs. Patients who suffer from these diseases need lifelong treatment. Nowadays, predictive models are frequently applied in the diagnosis and forecasting of these diseases. In this study, we reviewed the state-of-the-art approaches that encompass ML models in the primary diagnosis of CD. This analysis covers 453 papers published between 2015 and 2019, and our document search was conducted from PubMed (Medline), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) libraries. Ultimately, 22 studies were selected to present all modeling methods in a precise way that explains CD diagnosis and usage models of individual pathologies with associated strengths and limitations. Our outcomes suggest that there are no standard methods to determine the best approach in real-time clinical practice since each method has its advantages and disadvantages. Among the methods considered, support vector machines (SVM), logistic regression (LR), clustering were the most commonly used. These models are highly applicable in classification, and diagnosis of CD and are expected to become more important in medical practice in the near future.

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