Background: Health care providers are adopting information and communication technologies (ICTs) to enhance their services. Telemedicine is one of the services that rely heavily on ICTs to enable remote patients to communicate with health care professionals; in this case, the patient communicates with the health care professional for a follow-up or for a consultation about his or her health condition. This communication process is referred to as an e-consultation. In this paper, telemedicine services refer to health care services that use ICTs, which enable patients to share, transfer, and communicate data or information in real time (ie, synchronous) from their home with a care provider—normally a physician—at a clinical site. However, the use of e-consultation services can be positively or negatively influenced by external or internal factors. External factors refer to the environment surrounding the system as well as the system itself, while internal factors refer to user behavior and motivation. Objective: This review aims to investigate the barriers and the facilitators that influence the use of home consultation systems in the health care context. This review also aims to identify the effectiveness of Home Online Health Consultation (HOHC) systems in improving patients’ health as well as their satisfaction with the systems. Methods: We conducted a systematic literature review to search for articles—empirical studies—about online health consultation in four digital libraries: Scopus, Association for Computing Machinery, PubMed, and Web of Science. The database search yielded 2518 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 45. A qualitative content analysis was performed to identify barriers and facilitators to HOHC systems, their effectiveness, and patients’ satisfaction with them. Results: The systematic literature review identified several external and internal facilitators and barriers to HOHC systems that were used in the creation of a HOHC framework. The framework consists of four requirements; the framework also consists of 17 facilitators and eight barriers, which were further categorized as internal and external influencers on HOHC. Conclusions: Patients from different age groups and with different health conditions benefited from remote health services. HOHC via video conferencing was effective in delivering online treatment and was well-accepted by patients, as it simulated in-person, face-to-face consultation. Acceptance by patients increased as a result of online consultation facilitators that promoted effective and convenient remote treatment. However, some patients preferred face-to-face consultation and showed resistance to online consultation. Resistance to online consultation was influenced by some of the identified barriers. Overall, the framework identified the facilitators and barriers that positively and negatively influenced the uptake of HOHC systems, respectively.

Health information systems (HISs) have immense value for healthcare institutions, as they provide secure storage, efficient retrieval, insightful analysis, seamless exchange, and collaborative sharing of patient health information. HISs are implemented to meet patient needs, as well as to ensure the security and privacy of medical data, including confidentiality, integrity, and availability, which are necessary to achieve high-quality healthcare services. This systematic literature review identifies various technologies and methods currently employed to enhance the security and privacy of medical data within HISs. Various technologies have been utilized to enhance the security and privacy of healthcare information, such as the IoT, blockchain, mobile health applications, cloud computing, and combined technologies. This study also identifies three key security aspects, namely, secure access control, data sharing, and data storage, and discusses the challenges faced in each aspect that must be enhanced to ensure the security and privacy of patient information in HISs.

Patient engagement is currently considered the cornerstone of a revolution in healthcare for its positive impact on health outcomes, health behaviors and healthcare costs. Patient engagement is focused on personalized care to consumers through providing knowledge, skills and confidence. Mobile health (mHealth) applications are an innovative means to facilitate patient engagement. Nevertheless, the extent to which the current mHealth applications are designed to engage patients in managing their chronic diseases is unclear. This paper aims to identify the Persuasive System Design (PSD) features present in current mHealth applications that increased the engagement of patients with chronic diseases. This review also aims to identify patient engagement-related outcomes of these features. This paper conducted a systematic literature review and meta-analysis to find relevant studies published from all years up to 2020 through six databases: PubMed, Scopus, Web of Science, Cinahl plus with full text, MEDLINE with full text, and Cochrane Library (Central register of controlled trials). The database search returned 4939 articles; after applying the inclusion and exclusion criteria, the number of included articles for the final review was 13. A qualitative content analysis was performed to identify PSD model features and their patient engagement-related outcomes. The quality assessment has been done through the Cochrane Risk of Bias tool for RCTs. The systematic literature review and meta-analysis identified eleven PSD features that can increase patient engagement through using mHealth applications. The identified PSD features have been shown to have various patient engagement-related outcomes. Behavior Change Techniques (BCTs) were combined with the identified PSD features. This paper identified persuasive features of mHealth application design that influence the engagement of patients with chronic diseases toward changing their behavior. The impact of these features is also analyzed in this review. The results show that an mHealth technology-mediated patient engagement model is needed.

Background: Overweight and obesity have been linked to several serious health problems and medical conditions. With more than a quarter of the young population having weight problems, the impacts of overweight and obesity on this age group are particularly critical. Mobile health (mHealth) apps that support and encourage positive health behaviors have the potential to achieve better health outcomes. These apps represent a unique opportunity for young people (age range 10-24 years), for whom mobile phones are an indispensable part of their everyday living. However, despite the potential of mHealth apps for improved engagement in health interventions, user adherence to these health interventions in the long term is low. Objective: The aims of this research were to (1) review and analyze mHealth apps targeting obesity and overweight and (2) propose guidelines for the inclusion of user interface design patterns (UIDPs) in the development of mHealth apps for obese young people that maximizes the impact and retention of behavior change techniques (BCTs). Methods: A search for apps was conducted in Google Play Store using the following search string: [“best weight loss app for obese teens 2020”] OR [“obesity applications for teens”] OR [“popular weight loss applications”]. The most popular apps available in both Google Play and Apple App Store that fulfilled the requirements within the inclusion criteria were selected for further analysis. The designs of 17 mHealth apps were analyzed for the inclusion of BCTs supported by various UIDPs. Based on the results of the analysis, BCT-UI design guidelines were developed. The usability of the guidelines was presented using a prototype app. Results: The results of our analysis showed that only half of the BCTs are implemented in the reviewed apps, with a subset of those BCTs being supported by UIDPs. Based on these findings, we propose design guidelines that associate the BCTs with UIDPs. The focus of our guidelines is the implementation of BCTs using design patterns that are impactful for the young people demographics. The UIDPs are classified into 6 categories, with each BCT having one or more design patterns appropriate for its implementation. The applicability of the proposed guidelines is presented by mock-ups of the mHealth app “Morphe,” intended for young people (age range 10-24 years). The presented use cases showcase the 5 main functionalities of Morphe: learn, challenge, statistics, social interaction, and settings. Conclusions: The app analysis results showed that the implementation of BCTs using UIDPs is underutilized. The purposed guidelines will help developers in designing mHealth apps for young people that are easy to use and support behavior change. Future steps involve the development and deployment of the Morphe app and the validation of its usability and effectiveness.