New technology and illness self-management: Potential relevance for resource-poor populations in Asia (original) (raw)
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Appropriate mHealth technologies for low and middle income countries
2017
Background: The number of people with diabetes has risen from 108 million in 1980 to 422 million in 2014. Diabetes prevalence and burden of disease have been rising more rapidly in low and middle income countries (LMICs), mainly due to obesity and lack of physical activity. If properly delivered, diabetes education can lead patients to self-manage their disease and successfully avoid its complications. Mobile technology presents a simple way to reach a larger population since mobile phones have exceptionally exceeded other infrastructure in LMICs. SMS messages have the advantage of reaching a higher percentage of the population since they are supported by all types of mobile phones. With this continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth, seeking to explore more into mobile devices and wireless communication. Objectives: This thesis aims to examine the mHealth literature in search of an application area, a target disease, and an mHealth technology type that are most appropriate for LMICs. It also develops an mHealth solution suitable for Egypt as an exemplary country, and evaluates the developed solution in a real-life clinical trial implementation in an Egyptian healthcare facility. The trial examines the use of SMS technology in educating and monitoring diabetic patients, and assesses the impact of unidirectional educational text messages on their glycemic control and ability to self-manage their diabetes. Methods: The 2011 WHO mHealth report was reviewed and a combination of search terms, all including the word "mHealth", was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Retrieved articles were tested against inclusion and exclusion criteria and cross-referencing was performed on included articles. A 12-week randomized controlled trial (RCT) was then designed and conducted at the teaching hospital of Misr University for Science & Technology (MUST) in Cairo Egypt. Referred to as MUST Diabetes Awareness Program (DiabAwPro), patients were included if they had diabetes, owned a mobile phone, and were able to read SMS messages or lived with someone that could read for them. Intervention group patients received daily SMS messages and xvi weekly reminders addressing healthy diet, exercise, foot care, complications, medications, among others. They were expected to experience greater improvement in glycemic control as opposed to patients of the control group who only received paper-based educational material. All participants were invited to attend interviews, complete questionnaires, and undergo follow-up tests throughout the study. The primary outcome was the change in HbA1c levels; measured primarily by the difference between endpoint and baseline values, and further explored by the number of patients who experienced a reduction of at least 1% from baseline to endpoint. Secondary outcomes included blood glucose levels, body weight, treatment and medication adherence, diabetes self-efficacy, diabetes knowledge, rate of hospital/ER visits and stays, average frequency of blood glucose measurement, rate of regular exercise, patients' confidence in healthcare provider, patient satisfaction, and healthcare provider's reputation. Data were analyzed using ANCOVA, t-test, and chi-square test. Results: 842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the most number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternalandchild'shealth(MCH)(n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), telemedicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short periods. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence. xvii 34 intervention and 39 control patients completed the study. Over 12 weeks, a total of 3880 SMS messages were sent. Each intervention group patient received 97 messages comprised of 84 educational and 12 reminder messages in addition to one welcome message. The primary outcome, the change in HbA1c from baseline, did not differ significantly (Δ 0.290; 95% CI-0.402 to 0.983; p=0.406) between groups after three months, demonstrating a mean drop of-0.69% and-1.05% in the control and intervention group respectively. However, 16 intervention patients managed to achieve the targeted 1% drop as opposed to only six controls, suggesting a clear relationship between belonging to one of the study groups and accomplishing a 1% HbA1c drop (chi-square=8.655; df=1; p=0.003). All secondary outcomes appeared distinguishing of the intervention group after three months, with considerable improvements in treatment and medication adherence, diabetes knowledge, and self-efficacy scores. Participants indicated full satisfaction with the program, said they would recommendittoothers,andbelieveditcouldimprovethehospital'sreputation. Conclusions: SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in the developed world. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. SMS technology appears to be a promising method for improving glycemic control among Egyptian diabetics. Yet, whether it is more effective than traditional paper-based materials remains a topic for further research. In the MUST study, SMS messages resulted in higher HbA1c reductions than an instruction booklet after three months, but the most sizeable improvements were observed in secondary outcomes and self-management behaviors. Further, SMS messages were preferred to traditional methods in educating patients about their diabetes and sustaining their motivation to adhere to treatment.
BMC Medicine
Background: The prevalence of non-communicable diseases (NCDs) is increasing in sub-Saharan Africa. At the same time, the use of mobile phones is rising, expanding the opportunities for the implementation of mobile phone-based health (mHealth) interventions. This review aims to understand how, why, for whom, and in what circumstances mHealth interventions against NCDs improve treatment and care in sub-Saharan Africa. Methods: Four main databases (PubMed, Cochrane Library, Web of Science, and Google Scholar) and references of included articles were searched for studies reporting effects of mHealth interventions on patients with NCDs in sub-Saharan Africa. All studies published up until May 2015 were included in the review. Following a realist review approach, middle-range theories were identified and integrated into a Framework for Understanding the Contribution of mHealth Interventions to Improved Access to Care for patients with NCDs in sub-Saharan Africa. The main indicators of the framework consist of predisposing characteristics, needs, enabling resources, perceived usefulness, and perceived ease of use. Studies were analyzed in depth to populate the framework. Results: The search identified 6137 titles for screening, of which 20 were retained for the realist synthesis. The contribution of mHealth interventions to improved treatment and care is that they facilitate (remote) access to previously unavailable (specialized) services. Three contextual factors (predisposing characteristics, needs, and enabling resources) influence if patients and providers believe that mHealth interventions are useful and easy to use. Only if they believe mHealth to be useful and easy to use, will mHealth ultimately contribute to improved access to care. The analysis of included studies showed that the most important predisposing characteristics are a positive attitude and a common language of communication. The most relevant needs are a high burden of disease and a lack of capacity of first-contact providers. Essential enabling resources are the availability of a stable communications network, accessible maintenance services, and regulatory policies. Conclusions: Policy makers and program managers should consider predisposing characteristics and needs of patients and providers as well as the necessary enabling resources prior to the introduction of an mHealth intervention. Researchers would benefit from placing greater attention on the context in which mHealth interventions are being implemented instead of focusing (too strongly) on the technical aspects of these interventions.
The quality of healthcare in developing countries remains a critical issue, due in part to the limited infrastructure and resources available. The development of mHealth systems has been proposed as a possible solution. These systems extend the reach of medical care into rural areas by integrating smartphones and other mobile devices. Yet it is not clear how mHealth solutions designed and tested for use in one developing region can be adapted for use in others. This researchin- progress study frames this problem using a sociomaterial/coping perspective. A case study is proposed to extend and refine this model.
Global health action, 2018
In low-and-middle-income countries, epidemiologic transition is taking place very rapidly from communicable diseases to non-communicable diseases. NCDs mortality rates are increasing faster and nearly 80% of NCDs deaths occur in LMICs. Existing weak health systems of LMICs are undergoing a devastating human and economic toll as a result of increasing treatment costs and losses to productivity from NCDs. At the same time, the increasing penetration of mobile phone technology and the spread of cellular network and infrastructure have led to the introduction of the mHealth field. While mHealth field offers a great promise to prevent and control non-communicable diseases in low-and-middle-income countries: there is a great debate going on to explore health systems readiness for adopting mHealth technology to address NCDs in LMICs. There are a number of factors which determine health systems readiness and response for adoption of mHealth technology including preparedness of healthcare in...
Lancet
National health systems need strengthening if they are to meet the growing challenge of chronic diseases in lowincome and middle-income countries. By application of an accepted health-systems framework to the evidence, we report that the factors that limit countries' capacity to implement proven strategies for chronic diseases relate to the way in which health systems are designed and function. Substantial constraints are apparent across each of the six key health-systems components of health fi nancing, governance, health workforce, health information, medical products and technologies, and health-service delivery. These constraints have become more evident as development partners have accelerated eff orts to respond to HIV, tuberculosis, malaria, and vaccine-preventable diseases. A new global agenda for health-systems strengthening is arising from the urgent need to scale up and sustain these priority interventions. Most chronic diseases are neglected in this dialogue about health systems, despite the fact that noncommunicable diseases (most of which are chronic) will account for 69% of all global deaths by 2030 with 80% of these deaths in low-income and middle-income countries. At the same time, advocates for action against chronic diseases are not paying enough attention to health systems as part of an eff ective response. Eff orts to scale up interventions for management of common chronic diseases in these countries tend to focus on one disease and its causes, and are often fragmented and vertical. Evidence is emerging that chronic disease interventions could contribute to strengthening the capacity of health systems to deliver a comprehensive range of services-provided that such investments are planned to include these broad objectives. Because eff ective chronic disease programmes are highly dependent on well-functioning national health systems, chronic diseases should be a litmus test for health-systems strengthening.
Mobile Health, Developing Countries
The International Encyclopedia of Health Communication., 2023
Mobile health (mHealth, m-health) technologies are poised to transform healthcare service delivery and self-care in low-resource environments of developing countries. Originally conceived of as a range of mobile, sensor, and wireless technologies for healthcare delivery, these technologies improved information exchange and communication services in countries encumbered by limited medical infrastructure, shortage of trained personnel, and high incidence of communicable diseases. In the introductory period, limitations to telecommunication access for the general population meant that mHealth interventions were primarily implemented by the formal healthcare system as an organizational-level solution. In developing countries, mobile devices and Internet-enabled systems enable the transfer of high-quality medical information and resources between areas with differential healthcare resources. Typically, mobile phone-based communications enable frontline healthcare workers in remote areas to reach health professionals in urban areas, allowing for coordination amongst widely dispersed medical personnel, training for community healthcare workers, remote monitoring of programs, and dissemination of information to the community (Agarwal et al., 2015). However, the unprecedented growth and ubiquitous spread of mobile phone accessibility to most of the global population, accompanied by increased affordability, has addressed concerns related to the digital divide. By the end of the second decade of the millennium, mobile networks cover almost the entire global population, with 93% being able to access mobile broadband networks. The organic adoption of mobile devices and solutions by individuals has led to mHealth increasingly being viewed in terms of its potential as a consumer-level health management tool. The notion is that by using mHealth technologies, such as texts, apps, and wearables, people can conveniently collect, analyze, and share their own health information.
BMJ Open
IntroductionImproving healthcare for all is one of the global health priorities, particularly in disease burdened settings such as sub-Saharan Africa (SSA). Considering the high penetration rate of mobile phones in SSA, mobile health (mHealth) could be used to achieve universal health coverage. The proposed study will map evidence on the availability and use of mHealth for disease diagnosis and treatment support by health workers in SSA.Methods and analysisThis review will be guided by Arksey and O'Malley’s scoping review framework and Levac et al’s recommendations and guidelines from the Joanna Briggs Institute. A scoping review will be conducted to explore what is known about mHealth for disease diagnosis and treatment support by health workers in SSA and to identify areas for future research. In addition to searching the grey literature, the following databases will be explored from PubMed, MEDLINE and CINAHL with full text via EBSCOhost and ScienceDirect databases. A search ...
Management of non-communicable disease in low and middle income countries
International Heart Journal
Non-communicable disease (NCD) comprising cardiovascular disease, stroke, diabetes, and chronic obstructive pulmonary disease are rising rapidly in low- and middle-income countries (LMIC). Some patients have access to the same treatments available in high-income countries, but most do not and different strategies are needed. Most research on NCD has been conducted in high-income countries, but the need for research in LMIC has been recognized. LMIC can learn from high-income countries but need to devise their own systems that emphasize primary care, the use of community health workers, and sometimes the use of mobile technology. The World Health Organization (WHO) has identified “best buys” that it advocates as interventions in LMIC. Non-laboratory based risk scores can be used to identify those at high risk. Targeting interventions to those at high risk of developing diabetes has been shown to work in LMIC. Indoor cooking with biomass fuels is an important cause of COPD in LMIC, an...
Journal of medical Internet research, 2015
The prevalence of non-communicable diseases is increasing throughout the world, including developing countries. The intent was to conduct a study of a preventive medical service in a developing country, combining eHealth checkups and teleconsultation as well as assess stratification rules and the short-term effects of intervention. We developed an eHealth system that comprises a set of sensor devices in an attaché case, a data transmission system linked to a mobile network, and a data management application. We provided eHealth checkups for the populations of five villages and the employees of five factories/offices in Bangladesh. Individual health condition was automatically categorized into four grades based on international diagnostic standards: green (healthy), yellow (caution), orange (affected), and red (emergent). We provided teleconsultation for orange- and red-grade subjects and we provided teleprescription for these subjects as required. The first checkup was provided to 1...