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Background Mobile health (mHealth) has continuously been used as a method in behavioral research to improve self-management in patients with chronic diseases. However, the evidence of its effectiveness in chronic disease management in the adult population is still lacking. We conducted a systematic review to examine the effectiveness of mHealth interventions on process measures as well as health outcomes in randomized controlled trials (RCTs) to improve chronic disease management. Methods Relevant randomized controlled studies that were published between January 2005 and March 2016 were searched in six databases: PubMed, CINAHL, EMBASE, the Cochrane Library, PsycINFO, and Web of Science. The inclusion criteria were RCTs that conducted an intervention using mobile devices such as smartphones or tablets for adult patients with chronic diseases to examine disease management or health promotion. Results Of the 12 RCTs reviewed, 10 of the mHealth interventions demonstrated statistically significant improvement in some health outcomes. The most common features of mHealth systems used in the reviewed RCTs were real-time or regular basis symptom assessments, pre-programed reminders, or feedbacks tailored specifically to the data provided by participants via mHealth devices. Most studies developed their own mHealth systems including mobile apps. Training of mHealth systems was provided to participants in person or through paper-based instructions. None of the studies reported the relationship between health outcomes and patient engagement levels on the mHealth system. Conclusions Findings from mHealth intervention studies for chronic disease management have shown promising aspects, particularly in improving self-management and some health outcomes.

\"The name of Karl Benz, one of the father figures in the automotive industry, is quoted more than once in this book. This is not only because of his undoubted contribution during the initial phase of developments, but also because of the contrast of expectations by key figures such as himself against the established beliefs and practices of today. Common perception of what the automobile is and whom it is addressed to was significantly different back then. From the very few who could afford and the handful of those skilled enough to control such machines, within a few decades we were led to the generalization of the automobile, first in the US, then in Europe and post-WWII Japan\"-- Provided by publisher.

Background The advancement of mobile technology had positively influenced healthcare services. An emerging subfield of mobile technology is mobile health (m-Health) in which mobile applications are used for health purposes. The aim of this study was to analyze and assess literature published in the field of m-Health. Methods SciVerse Scopus was used to retrieve literature in m-Health. The study period was set from 2006 to 2016. ArcGIS 10.1 was used to present geographical distribution of publications while VOSviewer was used for data visualization. Growth of publications, citation analysis, and research productivity were presented using standard bibliometric indicators. Results During the study period, a total of 5465 documents were published, giving an average of 496.8 documents per year. The h- index of retrieved documents was 81. Core keywords used in literature pertaining to m-Health included diabetes mellitus, adherence, and obesity among others. Relative growth rate and doubling time of retrieved literature were stable from 2009 to 2015 indicating exponential growth of literature in this field. A total of 4638 (84.9%) documents were multi-authored with a mean collaboration index of 4.1 authors per article. The United States of America ranked first in productivity with 1926 (35.2%) published documents. India ranked sixth with 183 (3.3%) documents while China ranked seventh with 155(2.8%) documents. VA Medical Center was the most prolific organization/institution while Journal of Medical Internet Research was the preferred journal for publications in the field of m-Health. Top cited articles in the field of m-Health included the use of mobile technology in improving adherence in HIV patients, weight loss, and improving glycemic control in diabetic patients. Conclusion The size of literature in m-Health showed a noticeable increase in the past decade. Given the large volume of citations received in this field, it is expected that applications of m-Health will be seen into various health aspects and health services. Research in m-Health needs to be encouraged, particularly in the fight against AIDS, poor medication adherence, glycemic control in Africa and other low income world regions where technology can improve health services and decrease disease burden.

As the U.S. healthcare system transforms its care delivery model to increase healthcare accessibility and improve health outcomes, it is undergoing changes in the context of ever-increasing chronic disease burdens and healthcare costs. Many illnesses disproportionately affect certain populations, due to disparities in healthcare access and social determinants of health. These disparities represent a key area to target in order to better our nation’s overall health and decrease healthcare expenditures. It is thus imperative for policymakers and health professionals to develop innovative interventions that sustainably manage chronic diseases, promote preventative health, and improve outcomes among communities disenfranchised from traditional healthcare as well as among the general population. This article examines the available literature on Mobile Health Clinics (MHCs) and the role that they currently play in the U.S. healthcare system. Based on a search in the PubMed database and data from the online collaborative research network of mobile clinics MobileHealthMap.org , the authors evaluated 51 articles with evidence on the strengths and weaknesses of the mobile health sector in the United States. Current literature supports that MHCs are successful in reaching vulnerable populations, by delivering services directly at the curbside in communities of need and flexibly adapting their services based on the changing needs of the target community. As a link between clinical and community settings, MHCs address both medical and social determinants of health, tackling health issues on a community-wide level. Furthermore, evidence suggest that MHCs produce significant cost savings and represent a cost-effective care delivery model that improves health outcomes in underserved groups. Even though MHCs can fulfill many goals and mandates in alignment with our national priorities and have the potential to help combat some of the largest healthcare challenges of this era, there are limitations and challenges to this healthcare delivery model that must be addressed and overcome before they can be more broadly integrated into our healthcare system.

Background Lack of usability can be a major barrier for the rapid adoption of mobile services. Therefore, the purpose of this paper is to investigate the usability of Mobile Health applications in Bangladesh. Method We followed a 3-stage approach in our research. First, we conducted a keyword-based application search in the popular app stores. We followed the affinity diagram approach and clustered the found applications into nine groups. Second, we randomly selected four apps from each group (36 apps in total) and conducted a heuristic evaluation. Finally, we selected the highest downloaded app from each group and conducted user studies with 30 participants. Results We found 61% usability problems are catastrophe or major in nature from heuristic inspection. The most (21%) violated heuristic is aesthetic and minimalist design. The user studies revealed low System Usability Scale (SUS) scores for those apps that had a high number of usability problems based on the heuristic evaluation. Thus, the results of heuristic evaluation and user studies complement each other. Conclusion Overall, the findings suggest that the usability of the mobile health apps in Bangladesh is not satisfactory in general and could be a potential barrier for wider adoption of mobile health services.

Less than 30% of people in Africa received a dose of the COVID-19 vaccine even 18 months after vaccine development 1 . Here, motivated by the observation that residents of remote, rural areas of Sierra Leone faced severe access difficulties 2 , we conducted an intervention with last-mile delivery of doses and health professionals to the most inaccessible areas, along with community mobilization. A cluster randomized controlled trial in 150 communities showed that this intervention with mobile vaccination teams increased the immunization rate by about 26 percentage points within 48–72 h. Moreover, auxiliary populations visited our community vaccination points, which more than doubled the number of inoculations administered. The additional people vaccinated per intervention site translated to an implementation cost of US $33 per person vaccinated. Transportation to reach remote villages accounted for a large share of total intervention costs. Therefore, bundling multiple maternal and child health interventions in the same visit would further reduce costs per person treated. Current research on vaccine delivery maintains a large focus on individual behavioural issues such as hesitancy. Our study demonstrates that prioritizing mobile services to overcome access difficulties faced by remote populations in developing countries can generate increased returns in terms of uptake of health services 3 . A cluster randomized controlled trial in Sierra Leone shows that targeting access to vaccines in remote areas increases uptake, an approach that can be used to improve vaccine equity in developing countries.

Background Daily doses of pre-exposure prophylaxis (PrEP) can reduce the risk of acquiring HIV by more than 95 %. In sub-Saharan Africa, adolescent girls and young women (AGYW) are at disproportionately high risk of acquiring HIV, accounting for 25 % of new infections. There are limited data available on implementation approaches to effectively reach and deliver PrEP to AGYW in high HIV burden communities. Methods We explored the feasibility and acceptability of providing PrEP to AGYW (aged 16–25 years) via a community-based mobile health clinic (CMHC) known as the Tutu Teen Truck (TTT) in Cape Town, South Africa. The TTT integrated PrEP delivery into its provision of comprehensive sexual and reproductive health services (SRHS). We analyzed data from community meetings and in-depth interviews with 30 AGYW PrEP users to understand the benefits and challenges of PrEP delivery in this context. Results A total of 585 young women started PrEP at the TTT between July 2017 – October 2019. During in-depth interviews a subset of 30 AGYW described the CMHC intervention for PrEP delivery as acceptable and accessible. The TTT provided services at times and in neighborhood locations where AGYW organically congregate, thus facilitating service access and generating peer demand for PrEP uptake. The community-based nature of the CMHC, in addition to its adolescent friendly health providers, fostered a trusting provider-community-client relationship and strengthened AGYW HIV prevention self-efficacy. The integration of PrEP and SRHS service delivery was highly valued by AGYW. While the TTT’s integration in the community facilitated acceptability of the PrEP delivery model, challenges faced by the broader community (community riots, violence and severe weather conditions) also at times interrupted PrEP delivery. Conclusions PrEP delivery from a CMHC is feasible and acceptable to young women in South Africa. However, to effectively scale-up PrEP it will be necessary to develop diverse PrEP delivery locations and modalities to meet AGYW HIV prevention needs.

Since their introduction with the Digital Care Act in 2019, selected digital health apps (DiGA) have been a part of the German statutory health care system. In order to become a DiGA, digital health apps have to complete a certification process covering both technical and evidence-related aspects. After completion, DiGA are added to the DiGA directory, containing a list of all reimbursable DiGA within German statutory health insurance. The first apps were added at the end of 2020, with the number steadily increasing. The novelty of this digital health care service and the fast implementation led to problems and barriers to optimal use along the way, which are studied from different stakeholder perspectives in this paper. The aim of this survey was to identify problems and barriers in the context of the admission, financing, and service provision of DiGA in the statutory health care system in Germany. We used semistructured expert interviews to evaluate the perspective of stakeholders of the German health care system on DiGA. The interview guide was developed according to Helfferich. The interviews were transcribed and analyzed using the qualitative content approach by Mayring, with the adjustments by Kuckartz. We conducted web-based interviews with stakeholders between February and June 2022. The stakeholder collective consisted of DiGA, statutory health insurance, physician, patient, technological, and quality assurance representatives. To identify problems from stakeholder perspectives regarding the admission, financing, and service distribution of DiGA, 21 interviews were conducted. The interviewed stakeholders reported problems with the authorization of DiGA and the corresponding process, for example, the duration of the DiGA Fast Track process. DiGA prices and the different negotiation positions were criticized, and financial challenges for smaller DiGA manufacturers were noted. Another problem was seen in the reimbursement of DiGA, independent of actual use by the patients. Within service provision, the participants reported superordinate aspects, for example, the negative public perception of DiGA and negative statements from stakeholders. In relation to the direct care process, technical problems (eg, with activation codes or software surrounding DiGA prescription) and insufficient knowledge and skills on the side of the patients, as well as the medical providers, were mentioned. Digital health apps have the potential to improve health care by addressing health problems in new, innovative ways. Since the evidence-based and regulated use of this technology is relatively new, problems and barriers limiting the optimized, patient-centered use arose throughout the first years. This study provides an overview of problems and barriers in the context of DiGA in Germany from different stakeholder perspectives. Nevertheless, with these problems being continuously addressed, digital health apps are trending toward becoming a contributing factor to health care in Germany. Since other countries showed interest in implementing a federally regulated approach similar to Germany, valuable implications can be drawn from this survey.

Background Mobile Health Clinics (MHCs) are an alternate form of healthcare delivery that may ameliorate current rural–urban health disparities in chronic diseases and have downstream impacts on the health system by reducing costs. Evaluations of providers’ time allocation on MHCs are scarce, hindering knowledge transfer related to MHC implementation strategies. Methods Retrospective economic cost was assessed using business ledgers and expert assessments in 2023 US Dollar (USD) from 2022 to 2023. Time motion observational study assessed nurse practitioner (NP) and community health worker (CHW) time allocation and compared them between patients residing in isolated rural areas (hereafter isolated rural patients) and patients experiencing houselessness (PEH) sub-populations. Procedure codes were assessed retrospectively for each patient encounter ( n  = 1,981) over one year (April 2022 to April 2023). We used statistical significance tests (chi-square and Fisher’s Exact) to evaluate difference across sub-populations. Results Intervention start-up and operational costs totaled 275,000USD and 308,000USD, respectively, with the largest allocations to the modified recreational vehicle (RV) unit and labor. NP attributed 32% of time on direct care (mean = 153.00 min (SD = 37.80 min)), 38% on indirect care (186.0 (53.40)), and 21% on MHC tasks (104.00 (23.94)). CHW spent 47% of time on MHC tasks (182.00 (29.46)), 22% on medical care tasks (85.01 (SD 81.97)), and 22% on social needs tasks (87.70 (86.71 min)). NP time allocation did not differ significantly between isolated rural patients and PEH ( p  > 0.01), but CHW time did ( p  < 0.01). Of all procedures, 31.3% were vaccinations ( N  = 438), 27.0% were Covid-19 related ( N  = 377), 12.8% were outside referrals ( N  = 179), and 11.8% were point of care testing. Healthcare utilization varied between patient sub-populations, with Isolated Rural patient use dominated by Covid-19 and Influenza vaccines whereas PEH use was dominated by point of care testing ( p  < 0.01). Conclusion Patient sub-populations require varying provider time in different tasks and variable economic resources for interventions. As local policy makers balance resources and community health needs, a complete understanding of the resources required to operate an MHC and use of provider time is essential for informed decision making and successful implementation in underserved communities.