Ameera Hamid

eLearning Specialist and Disruptive Innovator in eHealth

  • Competitive telemedicine platform to help achieve UHC

    AfriDOKTA is passionate about transforming the delivery of healthcare in Africa through people, processes and technology. They have developed a telemedicine mHealth platform dedicated to Sustainable Development Goal 3, “Ensuring healthy lives and promoting well-being for all at all ages”. Anyone with a smart phone or internet access can easily download the AfriDOKTA app and would have immediate access to quality outpatient care.


    The Kenyan government is the first African country that has supported the roll-out of AfriDOKTA as part of a nationwide campaign towards universal healthcare. The roll out is supported at the community level by community health workers (CHWs) that train users on how to access health services using the AfriDOKTA app. Users can easily create a personal profile and an electronic medical record to store details of consultations received. The app also gives users referrals to vetted pharmacies and labs with certified medical professionals. 


    A unique design feature of the AfriDOKTA app is that it complies with international data security standards and adheres to the US-based Health Insurance Portability and Accountability Act (HIPAA). The architecture also applies Health Level 7 (HL7), SNOMED, and DICOM standards. These are international principles used for the transfer of clinical data between various software and electronic applications.


    AfriDOKTA's use of international standards for storing, accessing, and processing medical images and related information, their plans for strategic collaboration and relevant product benefits make it a strong competitive differentiator in the market. This solid technical foundation should position the platform to support our Universal Health Coverage (UHC) aspirations too.


  • Successful eHealth needs better business models

    eHealth is a complex business type, integrating many stakeholders acting across interwoven networks. Yet the characteristics of successful business models remain understudied.

    Despite the promise of eHealth to overcome healthcare access challenges, reduce costs and improve quality , successful implementation is low, especially in developing countries.  In fact, over 50% of eHealth businesses find it difficult to sustain their implementations sustainably beyond the pilot phase. I have been investigating these dynamics and will be sharing them over the next few weeks in a series of eHNA pieces.

    Recurring challenges of eHealth include;

    • Financial institutions unwillingness to fund eHealth start-ups
    • High start-up costs and ongoing maintenance costs
    • Regulatory legislation that lags behind technology development
    • Resistance from end-users to adopt new innovations
    • eHealth technologies lack user experience design
    • Poor scalability of eHealth technologies after their pilot phase
    • Poor ICT infrastructure in the environment
    • Lack of leadership and political support
    • Lack of research.

    To overcome these challenges, change is required in both the micro and macro eHealth environment. I’ll be sharing ideas on what changes are needed in my next piece.


  • African countries setup Country Health Situation Rooms for better health monitoring

    Two weeks ago, I was fortunate to participate in a workshop in Ethiopia hosted by the African Union, Africa CDC and UNAIDS.  The workshop aimed at strengthening the Country Health Situation Room initiative and roll-out across African countries.  Its goal is to support better use of health data and help countries keep populations healthier by improving their response to infectious diseases and epidemics.  


    Kenya was the first African country to adopt the Situation Room in 2015.  A further six countries – Cote d’Ivore, Lesotho, Namibia, Zambia, Uganda and Zimbabwe – have launched their Situation Rooms and are currently at different stages of scale-up and roll-out. 


    The Situation Room software integrates health data from multiple sources such as the DHIS2 and logistics management information systems (LMIS) at a country level.  Data are presented visually to help countries track progress and identify gaps in key health indicators.  The customisable interface allows countries to design their Situation Room around their health areas of interest and user types. 


    Matthew Greenall’s case study on the Country Health Situation Rooms describes the progress so far. Achievements include; 


    • Enhanced collaboration between different health programmes
    • Improvements in health decision making
    • Improvements in data quality
    • Increased data use for decision making
    • Improved data sharing between stakeholders at national and regional levels


    Important challenges are also identified, such as;


    • High turnover of staff and leadership compromised progress
    • Operational and budgeting constraints interrupted roll-out in some countries
    • Poor quality of data at sub-national levels
    • Ownership – a strong desire for countries to host the software themselves
    • Maintenance of the Situation Room software requires strong technical support


    The Health Situation Room is a bold step for the participating African countries. We look forward to reporting the progress of this important eHealth contribution to health systems strengthening.  



  • AXA Health Tech & You Awards wants bids for consumer-driven health innovation and excellence

    Driving proactive consumer engagement in health and supporting innovation are to success of the AXA Health Tech & You Programme. The current award has two categories, innovation and excellence. Applications close on 15 February 2019.


    AXA, an international health insurer, has focused the 2019 awards on celebrating entrepreneurs who provide the most valuable, trusted innovations for consumers in the market. The innovation and excellence categories will be underpinned by core values embracing diversity, health equality, and social inclusion.


    It’s seeking two types of solutions. One’s standalone solutions that help citizens take charge of their health and wellbeing. The other’s smart applications that enrich relationships between people and their careers, whether health professionals, friends or family. 


    The results could offer Africa’s health systems transformation models for some of their health promotion and community services. It’s worth looking out for the results.


  • A roadmap for AI in healthcare can help set its trajectory

    It seems that AI’s popping up in lots of healthcare settings. It’s trajectory becoming a bit random? If it is, does it need a roadmap? An article available from xtelligence Healthcare Media says it does and describes several AI initiatives. It seems more a scan of AI’s horizon that how to reach it.


    Eduardo Galeano, the Uruguayan journalist and  writer, identified horizon’s dynamic that fits AI and eHealth. “Utopia is on the horizon. I move two steps closer; it moves two steps further away. I walk another ten steps and the horizon runs ten steps further away.” 


    AI in Healthcare’s perspectives and initiatives include: 


    • Tapping the value of data at the right place, in real time; top questions for healthcare leaders
    • Welcome to the age of intelligence: matching mind and machine
    • Healthcare researchers using AI: don’t let data access derail clinical breakthroughs
    • An inside-out look at AI in outpatient radiology
    • Challenges in AI for radiology
    • When will AI be added to radiology training?
    • Enterprise imaging infrastructure
    • Greenlighting medical AI apps
    • Inside healthcare’s research revolution. 


    Two important roles for AI are seen as: 


    • Personalised, precision medicine
    • Clinical research.


    These are already transforming healthcare. The potential and opportunities need health systems to implement effective strategies for 


    • AI and eHealth
    • Health and healthcare transformation.


    AI reinforces the need for tight integration of eHealth strategies and health and healthcare strategies. It’s widely recognised as important. AI needs it strengthening. It’s a challenge for Africa’s health systems.


  • Medical imaging’s the big gainer from AI and ML

    AI’s not new. It emerged in the 1960s. A blog from PLOS Speaking of Medicine says advertising hyperbole has led to scepticism and misunderstanding of what’s possible with machine learning (ML) and what’s not with. The blog sets about providing an accessible, scientifically and technologically accurate portrayal of ML’s current state in clinical translation.


    Medical imaging workflows are seen as benefiting most in the short-term. ML algorithms automatically processing two or three-dimensional scans to identify clinical signs of conditions, such as tumours and lesions, and determining likely diagnoses have been published. Some are progressing through regulatory steps toward the market. 


    Many use deep learning. It’s a form of ML based on layered representations of variables, ML’s neural networks. It’s benefited ophthalmology. A major UK eye hospital has used deep learning to deal with a clinically-heterogeneous set of three dimensional optical Coherence Tomography (CT) scans. Referral recommendations reached or exceeded experts’ decisions.


    Radiologic diagnoses are another ML beneficiary. An algorithm detected 14 clinically important pathologies from frontal-view chest radiographs. They included:


    • Pneumonia
    • Pleural effusion
    • Pulmonary masses and nodules.


    ML’s performance matched practicing radiologists. Another 


    There’s several other clinical activities where ML can benefit healthcare. They include: 


    • Triage and prevention
    • Clustering for discovery of disease sub-types
    • Anomaly detection to reduce medication errors
    • Augmented doctors.


    The blog’s an advance report. Its final version’ll be in PLOS Medicine at the end of December. It’s a valuable guide for Africa’s health systems’ eHealth strategies. An initial step’s to lay down data foundations.


  • Babylon’s AI is embedded in Rwanda’s primary care, and other countries

    Succeeding with UHC depends on extra healthcare resources. It depends on efficient and effective use of resources too. eHealth’s part of the solution. 


    Babylon Health uses AI to improve access to primary care. It’s planning to expand into chronic care. In England, it’s restricted geographically to London.  Regulations seem to prevent Babylon’s AI from providing diagnoses. Instead, it provides health information.  This could change as hard evidence becomes available.


    A review, reported in Digital Health, says Babylon’s AI claims lack convincing evidence. Babylon Health doesn’t agree. A report claims its AI beat human doctors’ average score of 72% in a range of 64% to 94%. Babylon scored 81% in a Royal College of General Practitioners (RCGP) exam using a representative sample of questions from the final assessment for GPs in training. The results have not been peer-reviewed.


    In Rwanda, it’s called Babyl. It uses AI to provide:


    • Consultations with doctors and nurses
    • Lab tests
    • Prescriptions
    • Referrals.


    It’s a core UHC component for the country. Where access isn’t feasible with conventional healthcare, Babyl seems crucial in meeting health and healthcare needs.


    Babylon’s AI uses machine learning created by a team of research scientists, engineers, doctors and epidemiologists. They have access to large data volumes from the medical community. Learning’s continuous through feedback from Babylon’s experts.


    It comprises: 


    • A knowledge graph
    • A user graph
    • An inference engine
    • Natural Language Processing (NLP). 


    It seems like a solution for all Africa. On its own, it may not be enough. Increasing referrals may need investment in extra healthcare capacity.



  • Nigeria uses mHealth to improve blood donations

    Blood shortages are common in many health systems. An initiative in Nigeria uses mHealth to create a community of voluntary blood donors, and connects hospitals with blood banks, and blood banks with donors. Life Bank, a Lagos start-up also provides a discovery platform on for hospitals to order blood


     LifeBank delivers requested blood in less than 45 minutes, in a WHO Blood Transfusion Safety compliant cold chain. An article in Disrupt Africa says it’ll add other medical products such as oxygen, vaccines and rare drugs to its services.


    Its founder, Giwa-Tubosun, began a non-profit service to encourage people to donate blood. She then moved on to address supply shortages and poor logistics. Two main goals are: 


    • Increasing access to blood
    • Reducing the number of Nigerian women who die from birth complications. 


    LifeBank’s resources include: 


    • AI
    • Blockchain
    • Cold chain
    • mHealth
    • Motorbikes.


    These combine to provide information about blood availability and avoid health workers’ wasted time and frustration seeking blood products. They also minimise ineffective blood transports that result in bacteria proliferation and consequences of health complications.


     Supporters include:



    Its impact is considerable. To date, LifeBank’s delivered some 11,000 products for over 400 hospitals. Over 6,300 people are registered as voluntary blood donors, with over 20% donating blood in the last two years. The result: over 2,100 lives saved.


    A challenge is convincing blood bank partners to use LifeBank. As this is  overcome, it’s it easy to envisage LifeBank eventually operating across Africa.


  • Heidelberg University launches an eHealth policy course.


    Three entities have combined to create a five-day residential course on eHealth policy at Heidelberg University. The other two are evaplan, a University Hospital Heidelberg consultancy, and the Institute for Global Health.


    Developing national digital health policy: Laying the Foundations is designed for health planners and policy advisers. It will help them to explain eHealth’s national requirements for success. A specific emphasis is on low and middle income countries. It aims to help participants to:


    • Understand how well-crafted eHealth strategies support smart investment
    • Use available toolkits to design and improve country’s eHealth policies
    • Strengthen participants’ eHealth adviser roles
    • Support decision making for interoperable eHealth and avoid further fragmentation
    • Understand organisational and behavioural changes needed to maximise eHealth benefits.


    The curriculum for the first four days includes: 


    • Health Strategies and eHealth strategies in developing countries
    • Developing eHealth strategies
    • Planning for interoperability
    • Management and behavioural change. 


    The dates are 4 to 8 February 2019 at the university’s Internationales Wissenschaftsforum Heidelberg (IWH), Germany. The final day includes a guided tour of Heidelberg and time for mentoring and networking. Presenters are Peter Drury and Michael Stahl, The course is in English. Applications close on 15 November 2018.


  • How far into the future should eHealth strategies look?

    By definition, eHealth strategies are about investing in the future. They’re also about taking existing eHealth investments forward, either by switching, enhancing and rolling out further. In 2006, Rosabeth Kanter identified several lesson for innovation strategies. They included an “innovation pyramid” where:

    • Not every innovation idea has to be a blockbuster
    • Sufficient numbers of small or incremental innovations can lead to big gains
    • Big bets at the top that get most of the investment
    • A portfolio of promising midrange ideas in test stage
    • A broad base of early stage ideas or incremental innovations.

    The last one’s relevant for a perspective set out in an eBook from Oracle. Technology Takes Healthcare to Next Level proposes strategies for disruptive technologies of:

    • AI
    • Blockchain
    • Chatbots
    • IoT. 


    Each one offers promise for healthcare. Combined, Oracle sees the sum of the parts as greater than the whole. Combining blockchain and IoT allows frictionless data exchange. AI and machine learning put data in motion with minimal human intervention. AI tools can study blockchain’s large volumes of data to find patterns that need responses


    For Africa’s health systems, investment in ICT foundations and patients’ clinical and demographic data’s needed to. The strategic challenge is to choose between sequential investment and progress in an innovation pyramid where these four technologies start their journey. While leaving the disruptive technologies into the future, it can defer the costs. It will also defer the benefits.