eHealth Articles (1,988)

Gontse Ramela shares her eHealth insights on local radio

On 2 March, Gontse Ramela, an Acfee intern, had the opportunity to talk about eHealth and its role in strengthening healthcare systems in an interview with JOZI FM, a local radio channel in Soweto, Johannesburg, South Africa.

Gontse’s young, enthusiastic, ambitious and motivated. She’s passionate about opportunities that eHealth offer to promote health and prevent diseases. Having completed her Foundation Programme in Public Health in 2013, and completed her Bachelor’s degree in Public Heath with Criminology in 2016 at her elective at the University of Monash South Africa, she joined Acfee in 2017.

In her interview, Gontse discussed the potential of eHealth and its impact on patients. She explained that eHealth’s more than just health ICT. It’s about promoting and strengthening health systems, and stretches across people as users and patients and people in communities who benefit, changing healthcare’s clinical and working practices and improving the way healthcare organisations work together to improve their combined endeavours.

She went on to say that “eHealth helps to improve the quality of healthcare. The advances have allowed both patients and medical professionals to gain access to a variety of resources to improve people’s health and make healthcare more efficient and cost effective.” 

eHealth empowers patients to take an active role in their treatment, allowing them to gain a deeper understanding of their conditions and how to effectively manage them. It’s an exciting time for healthcare and eHealth has almost endless possibilities to help improve health and healthcare in Africa. Acfees’ delighted that Gontse will help to move it ahead.

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Mar 09, 2017
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Libratus AI has a good poker face

Artificial Intelligence (AI) may have a big role in Africa’s eHealth strategies. eHNA’s already posted that AI’s good at diagnosing cancer. An article in Wired says it’s hugely successful at poker too. It’s a big step forward for AI.

From the 1940s, chess was the test of AI. It’s a game of structured rules that computers could learn. AI for poker’s more demanding. To succeed, it has to outmanoeuvre other players’ bluffs and intuition and deal with only partial information about the state of each game too, which aren’t structured or rule-based. Libratus, built by Brown and Sandholm, two computer science researchers at Carnegie Mellon University, did it. More importantly, it learned while it was playing, using reinforcement learning, a method of extreme trial and error. It played numerous games against itself.

For twenty straight days, it played no-limit Texas Hold ‘Em, a complex poker with betting strategies stretching overs dozens of hands. It beat four of the world’s top players. Libratus relied on three different systems working together. This’s typical for modern AI that needs several technologies. During the games, a second system analysed the state of play and focused attention of the first system so it didn’t have to run through all the possible scenarios from the past. Libratus didn’t just learn before the match. It learned while it was playing.

Libratus’ could still win, but also be beaten by top class players who could find patterns of play from these two systems. A third system ran an algorithm that identified the patterns overnight and removed them.

The AI initiative’s seen as having an important, wide ranging role. One is in cyber-security. Clinical diagnostics are others. Is it the next big thing for Africa’s health and healthcare?

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Mar 09, 2017
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mHealth evidence’s still inadequate

The demand for evidence to steer more mHealth investment may not be fulfilled in the immediate future. A team from University of Washington and Columbia University has reviewed 39 mHealth economic evaluations and found several limitations. The report in PLOS One says there’s often inadequate evidence drawn from incomplete methodologies to support cost effectiveness claims.

While most studies address several of mHealth’s economic components, many also omit factors that could affect economic impact. The full range is in the Consolidated Health Economic Evaluations Reporting Standards (CHEERS) guidelines. They were developed by the International Society for Pharmacoeconomics and Outcomes Researcher (ISPOR).

  1. A simple summary is that:
  2. Evaluations included under 80% of the CHEERS guidelines
  3. Under a third of the studies were considered high quality using CHEERS guidelines as a measure.

The study’s firm evaluators should refrain from using the term cost-effectiveness in findings in the absence of rigorous economic evaluations. The same can be said for the term value for money (VFM), an equivalent economic concept that’s crept into management speak.

The value of economic evaluations is limited without a business case for comparison. An important goal’s comparing estimated actual performance with planned and required performance over time. The difference, and the reasons for it, provides valuable knowledge and learning for future mHealth decisions.

Transferability of finding’s another important theme. The study says using an appropriate methodology and data collection strategy increases transferability of findings across locations. There are many other factors needed too, such as:

  1. Standards and functionalities of mHealth services, including networks and smartphone requirements, interoperability (IOp), cyber-security
  2. Healthcare resources available before mHealth
  3. Users and beneficiaries cultures
  4. Communities’ health and disease profiles, demographics and socio-economic profiles
  5. Healthcare models, especially for healthcare continuity
  6. For African communities, the number of secondary mobile phones as shared users.

Economic costs have a different definition to financial costs. Consequently, economic evaluations of mHealth don’t provide an accurate view of its affordability, in terms of both cash flow and income and expenditure. These are often the last hurdle in investment decisions, so critical. There’s a need for evidence about this aspect too, especially in Low and Middle Income Countries (LMIC), so Africa.

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Mar 08, 2017
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How can Africa monitor influenza during the upcoming season?

In 2009, Sweden was one of the countries affected by A (H1N1) influenza, commonly called swine flu. Two minor peaks occurred during summer and winter. Starting among school children, the main epidemic occurred in late September and peaked in mid-November. It affected most parts of the country. An article in British Medical Journal (BMJ) says it leads to a debate on the level of the country’s preparedness.

During this time, the epidemic was monitored using data from eHealth records and eSurveillance systems. A report supporting evidence-based strategies for eHealth system development in infectious diseases was published in the Journal of Medical Internet Research (JMIR). The study’s primary objective was to examine correlations between data from:

  1. Google Flu Trends (GFT), an Internet-based software system using aggregated data from Google to estimate influenza activity
  2. Computer support for tele-nursing centres
  3. Health service websites
  4. Influenza case rates during seasonal and pandemic outbreaks.

Results indicated important correlations. These are between GFT, tele-nursing data and website visits. All influenza case data showed large effect sizes.

With the influenza season due in May and June in Southern Africa, it’s essential to review other eHealth surveillance systems to help prepare countries for likely outbreaks. eHealth innovators can then design initiatives to ensure the region’s prepared to deal with influenza.

351 Views
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Mar 08, 2017
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Keep health analytics simple, for now

Claims for Big Data’s and analytics’ benefits are considerable for commercial enterprises. For health and healthcare, it seems a bit more complicated, and sometimes bewildering. Where and how to start is a challenge.

In an article in Health Analytics, Dr Danyal Ibrahim, emergency physician and Chief Data and Analytics Officer at Saint Francis Care in Connecticut, invokes the wisdom of the ancient Chinese philosopher Lao Tzu, who famously said “A journey of a thousand miles begins with a single step.”

He sees the first step towards health analytics as a daunting leap of faith. Succeeding depends on:

  1. Clinical leadership and champions
  2. The right partnerships
  3. A strong, diverse Big Data analytics team
  4. Create an analytics infrastructure that delivers actionable, meaningful data to points of care
  5. Identify and break down data silos and develop a Big Data roadmap.

The last point holds the key to creating a streamlined data analytics infrastructure that reveals comprehensive and meaningful patients’ stories. These lead on to help make better and timely decisions. While healthcare data’s supposed to be connected around individual patients, it isn’t. It ends up in different siloes, creating a big barrier to using data to improve care.

From the streamlined data, the next steps are:

  1. Bring all the data stewards together
  2. Redesign the analytics team to focus on value for better care, more cost effective care and better patients’ experiences for patients

Effective analytics teams comprise a wide range of skills. They include, clinical, financial analytics, SQL development, data warehousing and data science, including statistical modelling and natural language processing. For Africa’s health systems, all these skills and knowledge may not be readily available. Analytics teams will need structured, integrated and technical development, so a sustainable training budget.

Lao Tzu’s proposed first step of analytics costs has a second step of producing valuable outputs that healthcare teams can use for measurable, proven patient benefits. Analytics will then justify itself.

429 Views
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Mar 07, 2017
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mHealth helps diabetes management

As diabetes spreads across Africa, an encouraging study reported in Diabetes Care found the mHealth helps deal with it. A team from Cardiff University in Wales investigated 14 mHealth services used in glycaemic control,  HbA1c in diabetes 2 self-management by 1,360 users.

Results are encouraging for Africa’s mHealth initiatives. The mean reduction in HbA1c of mHealth users was 0.49% compared with control groups. Sub-group analyses indicated that younger patients were more likely to benefit from mHealth for their diabetes. Benefits increased when health professional provided feedback, indicating that mHealth plus health professionals can be a better healthcare model that mHealth alone.

Two other findings are, mHealth for diabetes can be effective for populations, and mHealth’s functionality and use need standardising. The latter highlights the need for Africa’s health systems to enhance their overall eHealth regulation that can lead to appropriate mHealth policies and guidance.

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Mar 07, 2017
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AeHIN’s conference on ICT and SDGs starts today

AeHIN’s five-day conference starts today in Nay Pyi Taw, Myanmar. Its the fifth general meeting and focuses on Achieving the SDG's with ICT.

In 2007, the foundations of the Asian eHealth Information Network (AeHIN) were laid. Canada’s International Development Research Centre (IDRC) set up the PAN Asian Collaboration for Evidence-based eHealth Adoption and Application (PANACeA). It brought together 16 researchers from ten Asian countries to learn about eHealth and eHealth research. In parallel, eight multi-national research projects were implemented. Its Advisory and Monitoring Team (AMT) mentored the project teams dealing with a wide range of eHealth themes, including evaluating effectiveness of technologies and health informatics to manage health information in hospitals and communities and using telehealth to provide patient care at a distance.

AeHIN became the vehicle for these endeavours in the region. Its aim is to promote better ICT use to achieve better health through peer-to-peer assistance, knowledge sharing and learning through a regional approach for greater country-level impacts across South and Southeast Asia. Four strategic areas underpin its concept that better health can be achieved by strengthening evidence-based policies and health systems with better quality and timely Health Information Systems (HIS), Civil Registration and Vital Statistics (CRVS) and eHealth enables better information flow to support the delivery of quality and equitable healthcare and management of health systems. The four goals are:

  1. Enhance leadership, sustainable governance and Monitoring and Evaluation (M&E)
  2. Effective networking to increase peer assistance, knowledge exchange and sharing
  3. Promote standards and interoperability (IOp) in and across countries
  4. Build capacity for eHealth, HIS and CRVS in the countries and in the region.

These fit Africa’s eHealth initiatives. Partners for the event include Ministry of Health and Sports, the Government of the Union of the Republic of Myanmar, the WHO, the Asian Development Bank (ADB), United Nations Children's Fund (UNICEF).

The Conference objectives include:

  1. Sharing, learning, and preparing to implement digital health capacity building strategies standardized processes, tools and techniques, and ready-to-use IT solutions towards achieving UHC and SDG.
  2. Sharing current state-of-the-art digital health in Asia Pacific region for example interoperability architecture (OpenHIE) implementation, Regional Interoperability lab activities
  3. Motivate stakeholders to invest in digital health to strengthening health systems

Sustainable Development Goals (SDG) are high priorities for Africa’s health systems too. Two of Acfee’s directors, Dr Sean Broomhead and Dr Ousmane Ly are at the event. They’ll be sharing Acfee’s eHealth initiatives and bringing lessons back for Africa.

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Mar 06, 2017
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EXASOL joins Zambia’s Visualize No Malaria campaign

Africa continues to bear the brunt of the global burden of malaria. In 2015, an estimate from WHO says 88% of global cases and 90% of global deaths occurred on the continent.

Malaria can have severe socio-economic impacts on populations. It’s a cause of household poverty as it results in absenteeism from daily activities of productive living and earning an income. It also prevents many children from attending school, diminishing their capacity to realise their full potential.

Malaria is preventable and curable. Increased efforts are dramatically reducing the malaria burden in many countries.

Zambia has undertaken an ambitious campaign to eliminate malaria by 2020. To support its efforts EXASOL, an in-memory analytic database developer, and PATH, an international nonprofit organisation and global leader in health and innovation, have announced a partnership to support the Zambian government’s campaign says, an article in IT News Africa.

“Data analytics is often discussed as a way for business to derive value from the data they hold, whether that is to increase profitability or serve customers better,” said Aaron Auld, CEO, EXASOL. “But data can also unlock important information that can help organizations such as PATH improve the way they address Malaria. This ultimately shows the value of data in saving lives.” EXASOL joins Visualize No Malaria, a partnership between Zambia’s Ministry of Health, PATH, Tableau, and several technical partners including Alteryx, Mapbox, DataBlick, Twilio, DigitalGlobe, and Slalom.

EXASOL‘s contribution includes providing access to its database in the cloud on Amazon Web Services. It’ll enable the Visualize No Malaria team to perform complex, real-time analysis and queries of Big Data.

Allan Walker, a volunteer with expertise in data analytics and visualisation, is helping PATH’s Visualize No Malaria team to create analyses that estimate where malaria cases are more likely to occur and find relationships between mosquito vectors and human carriers of the disease.

The team’s project involves loading complex geospatial data into EXASOL’s database to model geological features in Zambia’s Southern Province, such as elevation, slope and hydrological features such as topographic wetness and stream power. It shows if land is dry or wet, and if water is still or moving.

The team also uses time-series regression models of population density and mobility, and meteorological models of precipitation and temperature to establish relationships with epidemiological data. The analyses can then be used by Zambian decision-makers to focus on probable malaria outbreak areas then respond quickly to new cases. This data can be life-saving for many communities. Other African countries battling  malaria can benefit too.

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Mar 06, 2017
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Kenya’s cancer screening app ETiCCS’s now available

Cervical cancer is the second most common cause of death for women worldwide. In Kenya, it’s the leading cause of death for women of reproductive age.  Kenyan Network of Cancer Organizations says there are approximately 39,000 new cases of cancer each year in Kenya, leading to more than 27,000 deaths. The star has a report estimating increases in cervical cancers cases from 3,000 to 4,200 by 2025. It’s largely due to lack of access to healthcare resources and treatments.

To address this gap and improve the quality of life among women in Africa, and particularly Kenya, the SAP’s Design and Co-Innovation Center together with Heidelberg University Hospital has optimised a cervical cancer screening test that combines practical medical research with cloud technology from SAP. The digitised screening test, called Emerging Technologies in Cervical Cancer Screening (ETiCCS) strives to support the fight against cancer in developing countries.

An article in IT online reports that ETiCCS was piloted during a one-year study, which tested 800 women at the Moi Teaching and Referral Hospital in Eldoret, Kenya. The program is ongoing and SAP East Africa plans to include the countrywide self-sampling and IoT scenarios, deep learning, pattern recognition, remote diagnostics support and validation into the program. SAP East Africa will collaborate with technology including SAP HANA Cloud Platform, as development continues SAP HANA Cloud allows seamless communication between healthcare providers including those in remote areas and environments with unstable Internet connectivity.

The technology will allow the healthcare screening services to:

  1. Keep medical records safely stored in the cloud providing instant access to results. Enabling labs to accelerate the screening process and empower medical staff through improved quality control embedded in the screening process
  2.  Enforce compliance with data privacy and security requirements, meaning labs can make informed diagnoses regardless of location or region
  3. Enable healthcare professionals to uncover critical patient insights and adapt the solution to other screening processes and field research.

The ETiCCS program has already enabled hundreds of women in Kenya access to screening for cervical cancer.

574 Views
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Mar 03, 2017
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IHE’s point of care ID management

Accurate unique patients’ IDs are more than essential. Deviations from them can cause harm when using electronic sensors to observe patients’ physiological states are a common part of clinical treatment of patients, especially those critically ill. Recognising the importance of correct patient IDs in this context, the IHE Patient Care Device Technical Committee has published Point-of-Care Identity Management, a white paper for consultation. It considered comments submitted by 26 February 2017 and will now be moving on to finalise the proposals.

With devices providing routine and regular mission-critical data, clinicians must be able to rely on the accuracy, currency, completeness and routing of eMessages between these devices and systems. Where this fails, treatment may be harmful rather than helpful. The IHE concept of Device-Patient Association (DPA) is consistent with the five rights of medication administration, the right patient, drug, dose, route and time.

For devices, it translates into the right patient, devices and time. Every measurement must go to the right chart, every chart must have every measurement, and every device command affecting a patient must be sent to the correct device acting on that patient.

The white paper:

  1. Reviews use cases and system architectures in which electronic information exchanges about device-patient associations may and may not be beneficial
  2. Discusses risk analysis approaches that may be appropriate for institutions reviewing their risks of data misdirection due to incomplete, incorrect or untimely DPA assumptions
  3. Suggests basic eMessaging formats for reporting, collecting, disseminating and querying DPAs.

As Africa’s health systems expands in EHRs, mHealth and medical device investments, adopting and applying the IHE’s standards are crucial. The white paper’s a lot more than just essential reading.

330 Views
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Mar 03, 2017
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