• mHealth
  • mHealth lessons may not be easy to transfer

    As the volume of the mHealth initiatives across the world expand, transferring the successes offers an effective way to make use of scarce mHealth development skills. It’s a valuable concept, but “may as readily translated to a country like India as proponents of mHealth might assume.” It’s a conclusion of a study from Durham University in the UK. If it’s a challenge for India, it may prevail across Africa too.

    “MHealth and the management of chronic conditions in rural areas : (sic) a note of caution from Southern India” draws from fieldwork to explored challenges facing mHealth implementation in Andhra Pradesh. It reviewed mHealth in chronic medical conditions, type 2 diabetes and depression. The research:

    • Identified ways people in a rural area access medical treatment
    • Assessed how adults use mobile phones in daily life to gauge the realistic chances of mHealth uptake
    • Identifies different pathways to care for the two medical conditions
    • Emphasised the importance to the rural population of healthcare outside the formal health system, and provided by Registered Medical Practitioners (RMP) who are neither registered nor trained
    • Demonstrate the limited use of basic mobiles by most of the older adult population
    • Examine how promoting self-management by patients may not be as readily translated to a country like India as mHealth proponents of might assume. 

    These combine into significant mHealth inhibitors. An important finding’s that it can be difficult to identify a clinical partner for patients or their carers for mHealth designed to help manage chronic ill-health in rural India.  

    While mHealth offers an effective potential response for better public health surveillance and healthcare, a more appropriate perspective’s is its probability of success. Invariably, probability has a lower socio-economic return on investment. The study raises a note of caution for India’s rural communities, suggesting that some more ambitious hopes for mHealth may be hard to realise. Factors at play include:

    • Tendency diabetics to avoid the government or formal health sector as a whole
    • The role of RMPs are central to such choices
    • Difficulties in seeking and sustaining treatment for depression
    • The viability of patients managing their own healthcare to realise benefits of self-management.

    Health workers often acknowledged communication problems between clinics and patients, but tend to assume it’s more straightforward to identify appropriate clinical end of the communication. The study challenges this assumption. The hypothetical self-managing individual fits well with popular western notions of self-actualisation, but may not transfer to India’s remote rural communities. Does this description fit Africa’s remoted rural communities too? The study’s cautious about generalisation across India, but does emphasise social and systemic challenges in addition to the technical features. So, while mHealth may not readily transfer across rural communities, the challenge to maximise mHealth’s health and healthcare benefits might.

  • More mHealth strategies are in place

    As mHealth expands across Africa, a report from Spok identifies an expansion of mHealth strategies. It’s improving, but there’s still plenty to do. From 2012 to 2017, healthcare organisations with mHealth strategies have increased from 34% to 65%. The Evolution of Mobile Strategies in Healthcare also identifies areas for improvement. 

    While many healthcare organisations have explicit healthcare development goals for clinical and working practices, it seems that mHealth’s contribution’s lagging behind. Spok’s findings are:


    Stated goal

    In mHealth strategy

    Physician-to-physician communications                 



    Nurse-to-physician communications    



    Nurse-to-nurse communications



    Code team or rapid response team communication



    Communication with health professionals networks




    Critical test results management



    Nurse call and patient monitoring alerts to mobile devices



    Patient satisfaction scores



    Patient throughput        



    ER and bed turnover



    Alarm fatigue    



    The findings provide a lesson for Africa’s health systems to ensure their mHealth plans and initiatives aren’t left outside conventional healthcare improvement projects. It seems it’s easy to overlook mHealth’s potential.

  • Patients in EDs have faster treatments when lab results use mHealth

    Being in ED isn’t a preferred way to spend quality time. Waiting longer than necessary makes it worse. Using mHealth can make shorter times feasible. A Canadian study in Annals of Emergency Medicine found that ER patients with chest pain spent 26 minutes less waiting to be discharged when doctors received the lab results on their smartphone. It took longer when doctors waited for results to show in EHRs. The approach, a push-alert system, sends all laboratory results simultaneously to both EHRs and an ED server. The server continuously searches for test results in the push-alert programme, such as troponin levels. When it finds them, it sends an email with patients names and test results to the most responsible doctors’ smartphones. An audible alert enables doctors to access the results as soon as they can. Only push-alert emails are sent to these phones.

    A 26 minute shorter wait’s significant for patients. The time savings the difference between 68.5 minutes for doctors decisions using mHealth alerts compared to 94.3 minutes for doctors who didn’t, but used EHRs. It also means EDs can be less crowded. The study dealt only with troponin tests, but it seems a reasonable assumption that other test results send to mHealth services under the right circumstances may yield equivalent results. 

    These results offer significant mHealth investment opportunities for Africa’s very busy EDs. The productivity and patient gains are attractive.

  • Bouy determines a person’s medical condition

    Doctors and computer scientists in Boston and New York have developed Buoy, a free AI platform. It helps people to use their symptoms to determine their medical conditions and make better decisions. The eHealth tool began in 2014 at the Innovation Laboratory at Harvard. Buoy’s co- founder and CEO, Andrew Le says currently, medical information provided by simplistic web symptom checkers are often risky and unreliable. To overcome these limitations, Buoy leverages advanced machine learning algorithms to provide personalised and accurate analyses and diagnoses to users so they can quickly and easily have more control of their healthcare.

    Bouy asks users to enter their ages, genders, and symptoms. It then asks a few questions, such as the severity of their symptoms and their durations. It uses this information to analyse against millions of medical records to generate other important, more specific questions. After two to three minutes of analysis, Buoy has an accurate and detailed understanding of users’ conditions. It will then recommend appropriate healthcare alternatives. If immediate treatment’s needed, it provides directions on how to connect with a nearby healthcare providers.

    An article in eHealth news says Bouy’s been through a battery of quality control tests. The result’s that it can accurately analyse a wide range of symptoms, such as common colds, abdominal pains and how a change of running shoes has created muscular or skeletal issues.

    The study tried to determine how Buoy interprets a cough compared the top five web-based symptom checkers. It examined 100 standardised cases involving 33 different diagnoses with severity ranging from life-threatening pulmonary embolisma to benign, normal cough. Prevalence was assessed too, ranging from rare histoplasmosis to common cold. Results were that Buoy’s analyses were 92% accurate as compared to WebMD at 56%, Healthline at 53%, Mayo Clinic at 38% and Isabel at 28%. Buoy has over 5,000 users and is available as an app on Apple store and directly from Buoy.

  • An mHealth app increases smoking cessation chances

    Globally, over 1.1 billion people smoked tobacco. That’s an estimate for 2015 from the WHO. Many more men smoke than women. Tobacco is the only legal drug that kills many of its users when it is used exactly as its manufacturers intended. WHO has estimated  that tobacco use, both smoking and smokeless, causes about six million deaths a year across the world. Many of these are premature. It includes approximately 600,000 people estimated to die from the effects of second-hand smoke.

    Clickotine, is an mHealth app that aims to help reduce the number of smokers. It emphasises the chances of successful rehabilitation from tobacco use. Research in the Journal of Medical Internet Research  (JMIR) shows that a personalised app for smoking cessation can help smokers who wish to quit, but who prefer using less intensive clinical intervention.

    An article in mHealth Intelligence says Clickotine offers a user-friendly way for patients to engage with their needs. It is developed with effective personalisation and engagement features of a smartphone app but includes components to support personal intervention complying with US clinical practice guidelines (USCPG). A questionnaire starts up when Clickotine is opened. It probes users to record their smoking behaviours and quitting goals. They also create a user profile with their unique smoking behaviours and input for personalised updates and messages.

    A log tool allows users to record smoking behaviours like cravings, sentiments, and number of cigarettes smoked. It is one of the app’s most popular features.  An article published in PubMed.gov says people between 18 and 65 used the app to start quitting on their own. About 45% abstained for seven days. Almost 27% abstained for 30 days. It seems that mHealth apps could provide a good step towards smoking  cessation across Africa. However, they need more testing.  Will this app have the same effect in All Low and Middle Income (LMIC) countries?

  • Medical Aid Films and Econet are transforming malaria health education in Zimbabwe

    Roughly 50% of Zimbabwe’s population live in areas with a high risk of malaria transmission. In response to the need for improved awareness about the disease, Medical Aid Films have been working with Econet Wireless on an innovative project to reach health workers and communities with vital information on their mobile phones. With over 9 million subscribers, Econet Wireless is Zimbabwe's biggest mobile operator, reaching over 65% of the mobile market.

    “This is an extraordinary opportunity to share free, easy-to-access information through animated films, which people can watch on their phones and share again and again, to improve knowledge and save lives.” Mr Douglas Mboweni, CEO Econet Wireless Zimbabwe.

    Produced with Zimbabwe’s Ministry of Health and Child Care and a team of experts, the mobile-friendly animations focus on the prevention, diagnosis and treatment of malaria and are available in English, Shona and Ndebele.

    The animations are available to watch for free on the zero-rated Econet Health website, with the link disseminated via blast SMS to all subscribers. They will also be shared with communities across Zimbabwe, supporting training and awareness-raising work of Zimbabwe’s National Malaria Control Programme.

    We are extremely proud to be working with Econet on this project – a fantastic example of the public and private sectors coming together to improve access to vital health information for people across Zimbabwe”. Chair of Medical Aid Films Board of Trustees, Richard Meredith 

    The films address Malaria Prevention, Diagnosis and Treatment.

  • mHealth can now control diabetes

    The change in mHealth emphasis from wearables that monitor to one’s that have clinical benefits, especially for chronic diseases, has taken a big leap forward. A study by a team in Shanghai, China in Science Translational Medicine, a publication of the American Association for the Advancement of Science, says its produced a device that can help to control diabetes. Smartphone-controlled optogenetically engineered cells enable semiautomatic glucose homeostasis in diabetic mice, includes a Swiss author, has used a combination of genetic engineering and optics with wireless technology to control remotely the release of glucose-lowering hormones by engineered, implanted cells. It’s seen as an “Elegant feat of synthetic biology.” 

    The technique implants hydrogel capsules that contain engineered cells and light-emitting diode light sources. These provide a semi-autonomous system that maintains glucose homeostasis over several weeks. A custom-designed home server SmartController processes wireless signals so a smartphone regulates hormone production. The eventual result is mHealth for cell-base therapies provided in clinics. 

    WHO has estimated that some 7 million people in Africa were diabetic in 2000. It expects that by 2030, more than 18 million people will suffer from it, up from about 0.6% of the population to 1.5%, an extra 370,000 people each year. The breakthrough for people’s very important for Africa.

  • mHealth economics and finance are separate and integrated

    As mHealth continues to expand, especially from narrowly focused wearables to sophisticated clinical data and Artificial Intelligence (AI), robust economic and financial profiles are more important.

    Underlying sequences and profiles over time reveal information than can help to modify existing mHealth services and plan investments. A team from Acfee , the Johns Hopkins Bloomberg School of Public Health (JHU) and Johns Hopkins University Global mHealth Initiative has constructed a stage-based process for integrating economic and financial evaluations into business cases and M&E.

    Published this month in Cost Effectiveness and Resource Allocation (CERA), “Defining a staged-based process for economic and financial evaluations of mHealth programs” describes how eeconomic evaluations generate evidence about value for money achieved by a project. Financial evaluations provide evidence on the financing required to initiate, sustain and expand programmes and assess their affordability. Integrated economic and financial evaluation has several advantages. It:

    • Demonstrates how mHealth can be implemented concurrently across lifecycle
    • Helps to manage progressions across stages of maturity
    • Improves the rigour of evidence, optimise allocations of scarce and finite resources
    • Facilitates programme planning, implementation, efficiency, effectiveness and sustainability.

    Economic and financial data have some common features. It’s a theme important for Amnesty LeFevre from JHU, She says “There are so few high quality evaluations of digital health solutions, let alone ones that rigorously explore costs and consequences, particularly across sub-populations and geographic areas and consider the financial implications of sustaining and scaling up. Our article aims to promote evidence-based decision-making and encourage decision-makers to rely on a wider range of analyses to inform their decision on optimal resource uses.” It needs six stages:

    1.     Defining programme strategies and links with strategic outcomes

    2.     Effectiveness assessments

    3.     Full or partial economic evaluation

    4.     Sub-group analyses

    5.     Estimating resource requirements for expansion

    6.     Affordability assessment and identifying sustainable financing models.

    It recommends analysts:

    •  Prioritise activities within these stages based on programmes’ links with health outcomes
    • Align these with mHealth solutions’ broader stages of maturity and evaluation
    • Incorporate into M&E activities and match outputs to stakeholders’ evidence needs
    • Fit to time points of initiations and secure available evaluation resources for each stage.

    Acfee’s Sean Broomhead and a report author said “mHealth is a crucial and expanding part of Africa’s health systems. It’s vital we can show it’s worth it, affordable and sustainable. This rigorous methodology has an essential part to play in mHealth’s future.” Adopting the combined methodology will help to improve mHealth’s role in health systems.

  • Vodacom Siyakha launches mHealth for expecting mothers

    Siyakha means ‘we are building’ in isiZulu. It’s also a platform used by Vodacom South Africa, and offers prepaid customers free access to a range of zero-rated sites, including:

    • Vodacom insurance products
    • Free health content from the TV series Hello Doctor
    • Vodacom’s infotainment platform Video Play
    • Educational portals and careers and jobs websites.

    Vodacom Siyakha has an mHealth service for pregnant mothers too.  Mum and Baby builds on Siyakha’s health service to offer maternal support to pregnant mothers. It provides educational articles videos and health information containing stage-based pregnancy information and advice. An article in IT News Africa says Mum and Bay also provides free health information and videos for childhood development too, extending across children’s first five years. Expecting mothers receive three weekly SMS’s to keep them undated on the progress of their pregnancies. These videos and SMS’s cover a range of health topics including:

    • Sexual and reproductive health
    • Breastfeeding
    • Immunisation
    • Early childhood development
    • Mother and child bonding
    • Nutrition
    • HIV/AIDS.

    A publication at My News Room, says Mum and Baby’s available in several languages, making it more accessible. The solution targets expectant mothers who lack easy access to healthcare facilities, It can be used by family caregivers too, who’ll be empowered with information and tools to use in their daily work setting.

    Vodacom customers can access Mum and Baby by dialing *111*88#, a prepaid number, or visiting the Siyakha mobi site.

  • mHealth good practices can reduce avoidable readmissions

    Many people don’t like the prospect of being admitted to hospital. It’s tolerable when it’s unavoidable. Being readmitted when it’s avoidable’s not a pleasant step, both for patients and their families and friends. A report from Mobile Smith, an app platform provider, says about 70% of the US’s hospital readmissions are avoidable. It’s hard to find equivalent numbers for Africa’s health systems.

    How Mobile Apps Can Reduce Preventable Readmissions sets out efficient app strategies that lead to quick impact on reducing avoidable readmissions. They’re:

    •  Effective discharge communication to minimise poor communication with patients and families members at discharge, a main reason for readmissions arising from confusion about follow-up care and prescribed medications
    •  Better discharge procedures that include education, communications with patients and families, support after discharge and fewer unresolved medical issues needing action after discharge, all of which result in lower readmission and improved patient outcomes
    • Use an app for post-discharge with interactive functions that includes promoting self-reliance, empowering patients to take charge of their health, connections to EHRs’ messages, managing appointments, access to educational articles and storing documents and notes
    •  Improving prescription adherence, including knowledge of the purposes of their medications and interactions, to improve health outcomes by tracking medication doses and intervals receiving medication reminders and recording reactions.

    There are six good practices:

    •  Research, know and understand target patient groups
    • Start simple and iterate often
    • Polish user interfaces and experiences
    • Keep apps fresh
    • Establish secure data exchanges
    • Embrace analytics to track utilisation and understand positives and negatives.

    These are valuable requirements for all mHealth initiatives. Africa’s developers and users can benefit by adopting them.