Africa’s eHealth isn’t far behind South America and Mexico
Africa’s eHealth has a different profile to the average for South America and Mexico, but it’s not trailing significantly. Comparing findings from the WHO and GEO’s Global eHealth Survey 2015 shows similar simple coverage rates of just over a third. A global average’s near 50%.
Perhaps the most important difference’s the emphasis on Big Data. South America and Mexico are at about 12%. Africa’s at about 2%. The survey didn’t ask for data about Artificial Intelligence (AI) or coverage of cyber-security. It doesn’t provide data about the quality, sophistication or maturity of the coverage. It’s not easy data to assemble, quantify or analyse.
Suffice to say, it highlights the need for Africa’s health systems to catch up on AI. A first step may be using their existing data more extensively. A second may be supporting public health specialists and clinical teams in local AI initiatives. The comparison seems to indicate no need for a sudden rush. A steady, imaginative plod along the AI road should be sufficient.
- 479 views
- May 18, 2017
- Tom Jones
AI and Big Data will transform healthcare
There’s a substantial progression of digital capacity in which data is produced and stored. In 2013, the amount of available digital data encompassed 4.4 zettabytes and it is estimated to reach 44 zettabytes, which is 44 trillion gigabytes, or ten times more by 2020. There is no denying that the world of Big Data’s enormous. Healthcare’s challenge is how to make best use of it.
Artificial intelligence (AI) is a vital and increasing part of it. It’s quickly becoming a necessity for healthcare. AI’s already widely used in everyday life. It’s in cars, Google searches, Amazon suggestions and other devices, but is yet to extend towards large-scale, routine AI for sophisticated activities such as healthcare and its clinical decisions.
AI services such as Apple’s Siri, Microsoft’s Cortana, Google’s OK Google, and Amazon’s Echo can extract questions from speech using natural-language processing and perform limited set of useful things, such as looking for restaurants, provide directions, find an open slot for a meeting, or run a simple web search. In addition, a 19-year-old British programmer launched a bot last September which is successfully helping people to appeal their parking tickets. It’s an “AI lawyer” that sorts received parking tickets. In both London and New York, the bot has a success rate of 64%, which translate to 160,000 of 250,000 parking tickets successfully appealed.
The same efficiency is essential in healthcare. An article in Medical Futurist reports that in years to come, AI in healthcare and medicine may organise patient pathways and treatment plans, and provide doctors with all information they need to make better informed decision. Several companies have a stake in AI in healthcare. They include Dell, Hewlett-Packard, Apple, Hitachi Data Systems, Luminoso, Alchemy API, Digital Reasoning, Highspot, Lumiata, Sentient Technologies, Enterra, IPSoft and Next IT. Their ultimate goal is to transform medicine and healthcare in way that ensures that it’s widely available to the average, mainstream users and not only the richest medial institutions or to a handful of experts.
AI’s used in several areas in healthcare. It includes mining medical records, designing of medical plans and medication management. Googles AI research branch in cooperation with the Moorfields Eye Hospital NHS Foundation Trust in London has launched a Google Deepmind Health project. It mines medical records to help to provide better and faster health services.
This year, a British subscription, online medical consultation and health service launched . It offers medical AI consultation based on personal medical history and common medical knowledge. Users report the symptoms of their illness to the app, which checks them against a database of diseases using speech recognition. After taking into account the patients’ histories and circumstances, Babylon offers appropriate courses of action. The app also reminds patients to take their medication and finds out how they’re feeling.
Molly was the first virtual nurse developed by Sense.ly medical start-up. It aims to help people to monitor their condition and treatment. Nurses use machine learning to support patients with chronic conditions in-between doctor’s visits. Customised monitoring and follow-up care is part of its service too, with a strong focus on chronic diseases.
The AiCure app maintained by The National Institutes of Health monitors patients’ medication compliance. It uses a smartphone’s webcam and AI to confirm patients’ medication ingestion and helps them to manage their conditions.
AI still has a long way to go. It will be exciting to see how Africa’s health systems adopt it in their eHealth strategies and use it to transform health and healthcare.
- 758 views
- April 05, 2017
- Gontse Ramela
eHealth, Google and others are revolutionising healthcare in emerging markets
Access to basic healthcare information is a challenge in many parts of the world. It’s especially demanding in developing countries. Google’s latest move in India may help increase access to healthcare information for millions of people.
An article in The Market Mogul says Google identified this gap in Indian and has added health information to its Knowledge Graph. It’s a sematic search base that Google uses to supplement organic search results with summarised information.
So, the next time someone in India uses Google to search common health conditions, it’ll show information cards illustrated with images. This information will include typical symptoms, details on how common the condition is, whether it’s critical, if it’s contagious and which age groups it affects. Google said that it’ll provide a condensed version if users have limited Internet connections. This goes some way to deal with India’s slow and intermittent mobile connections.
An article in TechCrunch says Google’s initiative is in response to start-ups dedicated to democratising India’s healthcare. Lybrate, an online, web-based healthcare service’s an example. It aims to increase access to doctors and quality healthcare information. It’s app service allows users to ask doctors questions online, search surgeries nearby and make and manage appointments.
Other developing countries benefit from mHealth initiatives too. Successful start-ups include Docway, Beep Health and Dr Vem! in Brazil. These use apps and the web to connect patients and doctors. Doctors have to be registered with the app, and set their own consultation rates. Users can also browse doctor’s resumes before deciding to book appointments. Most users are parents looking for paediatricians. The next big group of users are elderly people with limited mobility.
Are these online initiatives coming to Africa on a big scale? A more appropriate question may be when will they be available?
- 624 views
- March 20, 2017
- Hlobisile Vilakazi
Big Data is not big in Africa’s eHealth - unpacking the 3rd Global Survey on eHealth
As a relatively new part of eHealth, Big Data has a negligible effect on Africa’s health systems and eHealth programmes. Big Data insights are in Chapter 8 of the WHO and Global Observatory for eHealth (GOe) publication eHealth Report of the third global survey on eHealth Global diffusion of eHealth: Making universal health coverage achievable. WHO Global Survey 2015 provides the data source for the report.
It hasn’t taken off globally yet. Fewer than a fifth of countries say they have a national policy or strategy for regulating Big Data in health and healthcare. In Africa, it’s about 2%. This Big Data deficit isn’t much of a cause for concern. As the eHNA posts about WHO’s report show, Africa’s health systems have many other eHealth priorities. One that wasn’t included in WHO’s survey is stepping up cyber-security. Acfee’s report from its African eHealth Forum (AeF) our priorities include cyber-security and others, such as Interoperability (IOp), cloud computing, eHealth governance, regulation and capacity building are well ahead of Big Data.
WHO found that a lack of integration, privacy and security are major barriers to Big Data adoption. It’s constructive that Africa’s health systems are focusing on these as part of their expanded eHealth initiatives. Acfee’s activities in 2017 will support them.
- 874 views
- March 01, 2017
- Sean Broomhead
Big Data needs analytics tools and skills
Africa’s not yet investing much in Big Data compared to the global trend. It’s revealed in the WHO Global eHealth Survey 2015. An article in Healthcare Informatics, by Joe Mario, founder of Healthcare Integration Strategies, sets out two requirements for success that Africa’s health systems should adopt:
- Capture useful data in the proper format needed
- Have the analytic tools needed to extract meaningful information.
He also implies that healthcare organisation’s need to set up a data mining unit. He could’ve added a fourth requirement, having people with the analytic skills to design and run the data capture and use the analytic tools effectively. All four Big Data components are in short supply across Africa.
He sets out two organisational options. One is a centralised Big Data unit of analytic specialists supporting healthcare teams. The other’s decentralised, where each healthcare provider has its own team. For Africa, a decentralised model seems unrealistic until enough analytic specialists are available and affordable.
Setting up a centralised model needs a long-term plan to recruit, develop and retain analytic specialists. Success depends on health ministries working closely with universities to ensure a steady stream to build up a steady stream of health analytics specialists. The pace and scale needs to match the equivalent endeavour for health informatics specialists and the availability of data sources such as EHRs.
There are many other competing demands for these eHealth resources and tight affordability constraints. These combine to create a scenario where Africa’s Big Data programmes are likely to be relatively small, highly focused and provided by small, centralised teams. A big step forward’s including something like this in the next round of eHealth strategies.
- 574 views
- September 06, 2016
- Tom Jones
Big Data's transforming health and healthcare
Africa’s health systems will always need to adopt modern eHealth for disease surveillance, especially epidemics like Ebola and Zika. The recent WHO eHealth survey reported in eHNA found that Africa’s health systems are well behind in their Big Data and analytics strategies. Most countries have no Big Data strategy. A report on the Information Age shows why they have to catch up.
It says intelligent uses of Big Data in healthcare are helping to predict epidemics, find cures for disease, improve quality of life and avoid preventable deaths. These are big impacts, and even more important as Africa’s population increases and ages. Big Data can help to develop new and changing models of healthcare treatment and delivery.
Big Data blood supply, its data, is expanding rapidly. More data’s been created in the last two years than in the entire previous history of the human race. It’s not stopping. By 2020, about 1.7 megabytes of new information will be created every second for every person on the planet. By then, data’s accumulated digital universe will’ve grown from 4.4 zettabytes today to around 44 zettabytes, or 44 trillion gigabytes, a ten-fold increase in just four years.
Whether it’s the megas, zettas or trillios is less important than adopting, developing and using Big Data for its benefits. Understanding more about individual patients as early in their life as possible offers opportunities to find warning signs of serious illness early enough so treatments can be easier, simpler, cheaper and more successful than later diagnoses.
Big Data’s not a simple solution. It has several challenges. Storing and managing needs big archives to preserve large volumes of data for future research. Security and compliance challenges run alongside this. Ben Rossi, the article’s author suggests that pathology services offer a good way for healthcare organisations to deal with this.
Pathology services are regularly adopting new digital technologies that offer new Big Data opportunities. eHealth’s helping pathology labs to benefit from digital workflows that foster innovation that can transform patient care. A modest pathology lab with one small slide scanner will generate over 15 terabytes of data a year.
It could be a way into Big Data for some African health systems. When will all African countries start on Big Data?
- 1,082 views
- May 19, 2016
- Tom Jones
Analytics can help with medication compliance
Once patients are back home, complying with medication regimes seems an continuing intractable challenge for many of them. SMSs have played a valuable role. Now, analytics has emerged on the scene.
A report in Health Analytics says Sanofi has partnered with Duke Clinical Research Institute (DCRI), Massachusetts General Hospital and its Center for Assessment Technology and Continuous Health (CATCH) to improve medication adherence rates for Type 2 diabetes patients. The team’ll use Big Data analytics tools developed by DCRI and CATCH.
Using all available data, including demonstrated behaviour, is seen as an innovation to direct personalised care and engagement programmes and practical tools and services so people with diabetes can engage more proactively with their treatment. Better outcomes are the planned benefits. They’ll be achieved by healthcare provider anticipating medication adherence rates for individual patients, then intervening as needed with appropriate actions.
The project’s part of a trend. Medical researchers are relying increasingly on predictive analytics to improve chronic disease management, especially medication compliance. Failure to comply has a high costs. In the USA, it’s estimated that it cost the healthcare industry approximately US$337b in 2013. It’s also associated with unsatisfactory population health management programmes.
A data challenge’s that healthcare providers are reluctant to integrate data about medication adherence into EHRs, mainly due to data overload. There’s also some dissatisfaction with value of patients’ data from pharmacies and health insurers.
A solution’s seen as semantic data analytics tools. Healthcare providers and Big Data scientists are relying more on semantic databases for comprehensive insights on population health management. They draw from different data sets, such as patient information, socio-economic data and pharmacy information to produce more accurate and reliable predictions about patients’ outcomes. These are from connections of different concepts rather than displayed rows of specific information.
As US healthcare strives to move Big Data ahead, Africa’s health systems can begin to develop their Big Data strategies. WHO’s latest eHealth survey, reported on eHNA, showed a marked lack of progress.
- 626 views
- May 18, 2016
- Tom Jones
How can Africa catch up with Big Data?
Big Data offers big promises. Even if it’s not true, Big Data does offer new opportunities. eHNA has reported that WHO’s 2015 eHealth Survey found that out of 33 African countries, only one’s started to deal with Big Data.
IBM Watson has released its white paper Social and behavioural determinants of health A look at fundamental drivers of health and disease to help improve population health and reduce costs. It has valuable constructs that can help Africa’s health systems build their Big Data and analytics strategies, plans and services.
It proposes a shift in the approach to Population Health Management (PHM) from a context of patient populations to communities where people live, work and play. Many factors comprising Social Determinants of Health (SDH), such as employment, healthy food and people’s physical environment are beyond doctors’ and hospital’s control, but healthcare organisations can work with communities to help patients deal with SDH factors that affect their health and access to healthcare. A current limitation to progress is knowing how to do it.
The white paper explains:
- What SDHs are
- How they influence people’s health
- What healthcare organisations can do to improve population health
- How behavioural health affects physical health
- Why it should be integrated with primary care
- A new concept of service delivery integrating healthcare with social services
- The kind of eHealth needed to support these.
Five are set out as:
- Model 1: targeting health behaviours where doctors and healthcare teams try to induce
- patients to modify their health behaviour
- Model 2: referral to community services, especially community health centres care for people o lower incomes
- Model 3: limited social support in healthcare frameworks
- Model 4: patient-centred medical homes that emphasise SDH
- Model 5: holistic care management that integrates healthcare and social services.
Advantages of integrating healthcare and social care
It’s shown to produce measurable benefits. They include:
- Twice as effective at treating depression
- Improves physical and social functioning and quality of life
- When behavioural health is engaged, healthcare organisations seeking to address SDH must work with social services and other community resources
- Reduces overall healthcare costs.
An integrated service needs a wider range of information than segmented services. This’s where Big Data’s needed. The range of sources is considerable, and includes:
- Social services adult and child teams
- Functional assessment surveys, even though they’re currently uncommon in mainstream healthcare
- Health insurance databases
- EHRs and administrative systems
- Places of residence
- Administrative records
- Distances to nearest clinics, health centres and food stores from geographical information systems
- Living situations, such as living alone, from social service agencies and public records
- Physical disabilities, from EHRs and disability insurance records
- Employment status from unemployment insurance and social security records
- Environmental hazards, such as poor housing from building reports
- Air quality from weather reports
- Diet and exercise from health risk assessments
- Medication compliance, from prescription records and mHealth reminders.
As African countries are still at the Big Data starting gate, planning to achieve all these isn’t realistic. A more modest approach’s needed to make a start, and communities with potentially high levels of SDH or poor access to healthcare may offer the best returns. These could be urban populations living in poor housing and remote rural communities. From a small start, Africa’s health systems and can learn and grow their Big Data skills, priorities and benefits.
- 842 views
- April 19, 2016
- Tom Jones
Where can Big Data have the biggest impact?
Corporates are increasingly harnessing the power of Big Data and analytics to improve productivity, gain market share and a competitive edge. While many have embraced Big Data and its benefits, there are sectors that lag behind by not fully capitalising on its potential to produce actionable insights says an article in IT-Online. Healthcare still has along way to go.
According to Yudhvir Seetharam, head of analytics at First National Bank (FNB) Business, global business challenges and developments put more pressure on sectors that are sensitive to economic cycles. As a result, Big Data’s insights can help solve some of the biggest business challenges.
He says there are five sectors in South Africa that should consider incorporating Big Data analytics into their operations. They’re:
- Financial services
Healthcare’s always looking for new ways to increase accessibility and affordability while maintaining costs. Big Data can play a big role in making that happen. It can be used to determine the best geographic location for new hospitals, and provide insight into trends and potential solutions in medical research. Identifying and predicting epidemics, help in finding cures for diseases and an overall increase in the quality of care can be extracted from Big Data and its analytics.
Big Data uptake in many African countries has been slow for healthcare. It’s not that governments or hospitals don’t relealise the benefits but the fact they have a long list of challenges to address before they can use it. Big Data and analytics are also competing for very limited resources and many countries struggle to justify the cost when they desperately need the money to buy more drugs or hire more staff.
Although several implementation challenges remain for African countries, including limited resources and basic infrastructure shortfalls, healthcare may be coming to the point where it is not longer a matter of if, but rather when. The potential for using Big Data seems too big to miss out on. The challenge is integrating into a long list of other eHealth priorities, especially the long list of long-standing challenges identified in Advancing eHealth in Africa.
- 979 views
- March 16, 2016
- Lesley Dobson
Big Data has big potential for your health
Big Data’s still a young methodology. It’s reasonable to expect that its initial potential will convert into wide-scale benefits.
A recent post in the Wall Street Journal (WSJ) highlighted Big Data’s potential to bring about revolutionary advances in finding effective cancer treatments. It describes analysing vast genetic and clinical data from hospitals and doctors to personalise cancer prevention and treatment based on the genetic characteristics of patients’ tumors, family history and other unique characteristics. The result is to minimise unwanted treatments and their often serious side effects.
In Africa, an article in Fortune highlights using Big Data in Mozambique to improve HIV testing services for infants to allow timely initiation of life saving anti-retroviral therapy. Investigators found that by analysing enough data from shipments between clinics and laboratories, they could reorganise testing facilities and their locations to speed up HIV test results. The result’s increased efficiency in processing tests.
Big Data has considerable potential to improve other population and patient outcomes, so ensure more healthy Africans. Effectively mining the vast insights hidden in Big Data to improve our health remains an exciting frontier to follow closely. Initiatives such as IBM's Watson fighting Ebola or mobile phone data to track rubella in Kenya are making a start. African countries can build on the early gains to move into a position where they can exploit Big Data for their own health transformation.
- 799 views
- February 19, 2016
- Sean Broomhead
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