Tom Jones

eHealth strategist, planner and evaluator

  • GE sells its healthcare Value-Based Care Division to Veritas for >$1b

    In a shake-up to the health ICT supply side, an announcement by GE says it’s selling its:

    • Enterprise Financial Management, Revenue-Cycle, Centricity Business
    • Ambulatory Care Management, Centricity Practice Solution
    • Workforce Management, formerly API Healthcare.

    The buyer, Veritas Capital takes it on for $1.05b in a cash-will-do-nicely deal. It’s Veritas Capital is a leading, global private equity firm that invests in companies that provide essential products and services. Technology and technology-enabled solutions are its main service range. Governments and commercial organisations are its main customers.

    They extend across aerospace, defence, healthcare, national security, communications, energy, education and government services. It’s Veritas business model seeks to create value by strategically transforming companies that it invests in.

    GE says Veritas is ideal to provide the focus and investment needed to take GE’s former services to the next level of scale and performance. The former GE team  sees the switch as an opportunity to revitalise its product portfolio and pursue complementary acquisitions. The intended result’s better for patients, providers and payers services

    These big outfits seldom see Africa’s health systems as fruitful markets. Affordability’s a constraint. Will Veritas take a different view?


  • AlienVault insider’s guide to cyber-security incident response can help

    Preventing cyber-security breaches is a top priority. On its own, it’s not enough. Cyber-criminals are at least one step ahead, so sound preparation for an incident response’s vital.  A book from Alien Vault can help. It's an Insider’s Guide to Incident Response in one eBook! 


    It provides a detailed insight into the fundamental strategies of efficient and effective incident response that security teams need. The goal should be to do more with less to deal with the rapidly changing cyber-threats. The guide deals with: 


    • Arming and aiming an incident response team
    • Incident response processes and procedures
    • Types of cyber-security incidents
    • Incident response tools
    • Incident response training


    Combating cyber-threats needs teams with a strong mental constitution.  Techniques are needed too. The guide sets out how to build an incident response plan and develop a team that has the right tools and training.


    Observe, Orient, Decide and Act (OODA) loop’s the core methodology.  It’s a cycle developed by military strategist and United States Air Force Colonel John Boyd. He used it to help to prepare for combat operations processes. It’s now applied to understand commercial activities. 


    Benjamin Franklin, the 18th century polymath promoted the original concept. “By failing to prepare, you are preparing to fail.” It applies to eHealth too.


  • Will robots be cooking on gas in hospital kitchens?

    Inpatients need nutritious meals as part of their care plans. This puts hospital catering services as an important part of healthcare teams. While robots in clinical activity have received considerable attention, their opportunities in hospital catering hasn’t. Flippy might change that.


    A report  in Tech Crunch says Miso Robotics is rolling out a robotic kitchen assistant. It’s called Flippy. It’s first job’s flipping burgers. Already, it’s a bit of a celebrity, with a YouTube and Vimeo performances. 


    While burgers may not be the ideal meal for inpatients, Cali Burger makes and sells burgers in twelve countries and found Flippy its first job. It doesn’t look like a chef.


    It’s a small, wheeled cart with a six-axis robotic arm and  a sensor bar. It takes data from thermal sensors, 3D sensors and several cameras to assess its environment. Digital systems send tickets from the counter to the kitchen as Flippy’s orders.


    Then, it picks up unwrapped burgers, puts onto a hot grill, tracks their cooking time and temperature, then alerts chefs when to apply cheese or other toppings. When that’s done, Flippy plates the burgers.


     but doesn’t wrap them or add finishing touches like lettuce, tomatoes, avocado or a restaurant’s signature sauce.


    Momentum Machines makes kitchen robots too. Flippy’s different. It relies on  AI software and machine learning, so it learns to make new foods, adapting to a restaurant’s seasonal menu changes. This might be the potential for Flippy’s descendants to take on more sophisticated jobs in hospital kitchens. Let’s hope they’re not wayward offspring called Floppy.



  • Need a Big Data and AI overview; this’s it

    It seems that Big Data isn’t big after all. David Stephenson, in his book Big Data Demystified, published by Pearson, says “Big” significantly understates the volume and differences to conventional data. Understanding it needs to be in its context of AI and Machine Learning (ML). 


    He ranges over Big Data’s:


    • Usefulness
    • Ecosystem
    • Strategy
    • Implementation
    • Technology selection
    • Team building
    • Governance and legal compliance.


    Case studies bring each of these into practical environments. While Stephenson’s keen on Big Data, his book’s not an exhortation to rush into initiatives. Instead, his “Keep in mind” boxes are valuable switches from his commentary that provide realistic insights for policy makers, strategists, executives, managers, practitioners, health workers and students.


    It’s clearly written and offers new, late and in between comers to Big Data many very valuable insights and case studies. Examples are his analyses of Big Data’ infrastructure requirements and its 3Vs, Volume, Velocity and Variety. His concept of a “data lake” draws a vivid perspective of Big Data’s difference to databases 


    He includes a salutary lesson. Many Big Data projects “Die on the launch pad because of inadequate preparation, internal resistance or poor programme management.” His case study was a $62m crash.


    As Africa’s health systems move towards more Big Data opportunities, Big Data Demystified will help to set scenarios that lie ahead. Investment in new skills is part of it.


  • Cyber-security projects reveal priorities

    As cyber-security activities step up, Barkly shows how their priorities can indicate strategies that organisations can adopt. 


    Its report identifies twelve cyber-security investment in relative priority order. They’re: 


    • Endpoint security using advanced malware protection and prevention, the top priority
    • Access and authorisation
    • Endpoint protection using response and threat hunting
    • Cyber-security intelligence
    • Data protection using encryption
    • Application security
    • Network traffic visibility
    • Wireless security
    • Incident response tools
    • Bring Your Own Devices(BYOD) security
    • Embedded security in IoT
    • Distributed Denial of Service (DDOS) protection, the lowest priority. 


    Alongside these initiatives, cyber-security teams are researching and evaluation cyber-security tools. It’s an activity that needs considerable cyber-security skills and resources. For Africa’s eHealth, it means two initiatives are needed, one to recruit, train and retain experts, and provide additional resources needed by them to fulfil their role. 


  • mHealth’s proven impact still seems elusive

    Africa has an expanding, diverse mHealth core to its eHealth initiatives. The Journal of Medical Internet Research (JMIR) found limited evidence of mHealth’s impact, and hinted that in low-income countries, mHealth’s still at an early development stage.


    JMIR’s systematic review covered 10,689 mHealth articles, including 23 systematic reviews of 371 studies with over 79,609 patients. Seventeen reviews included studies of low- and middle-income countries’ initiatives. 


    SMS for a wide range of purposes seems to be the most common type of mHealth. It includes reminders, alerts, educations, motivation and illness prevention. Ten reviews gave them an Assessment of Multiple Systematic Reviews (AMSTAR) score of 0 to 4, low quality. Seven were rated as moderate quality, an AMSTAR score of 5 to 8. Six were rated as high quality, an AMSTAR score of 9 to 11. 


    mHealth for  chronic disease management scored well for impacts of:


    • Improved symptoms and peak flow variability in asthma patients and fewer hospital admissions and improving forced expiratory volume in one second
    • Improving Chronic Obstructive Pulmonary Diseases (COPD) symptoms
    • Improving heart failure symptoms and fewer deaths and hospital admissions
    • Improving glycaemic control in diabetes patients
    • Improving blood pressure in hypertensive patients
    • Reducing weight in overweight and obese patients
    • Better attendance rates
    • Better adherence to tuberculosis and human immunodeficiency virus therapy in some scenarios, with evidence of decreased viral loads.


    While these are positive results, the benefits may still be moderate.  JMIR concluded that “Evidence for efficacy is still limited. In general, the methodological quality of the studies included in the systematic reviews is low. For some fields, its impact is not evident, the results are mixed, or no long-term studies exist.”


    The lack of reliable evidence doesn’t mean that Africa should slow down its mHealth investment. Instead, it means it should set up a reliable methodology to reveal the range of good and bad impacts. Lessons from these will be invaluable.


  • Telehealth providers have five trends

    As Africa’s mHealth initiatives move on, opportunities to include telehealth are expanding. Options for health systems can follow five provider trends. MDLIVE has described these in Wellness Gone Wireless:Top 5 Trends Driving Telehealth in 2018, available from Fierce Markets. 


    The trends are: 


    • Expansion of cloud-based smartphone technology and health and wellness wearables, creating more engaged consumers
    • AI innovation enabling more refined data analytics and personalised patients’ experiences
    • Reduced reliance on reimbursement models, expanding providers and patients populations
    • Consumer satisfaction driving more demand and lower costs
    • Disciplined focus on data security, driving increased consumer confidence and suppliers’ oversight. 


    Removing barriers to access telemedicine’s part of these trends. It can improve healthcare quality and removes geographic limitations on access. It’s becoming easier to match providers to community needs.


    These are encouraging signs for Africa’s telehealth priorities.


  • eHealth for mental health needs more intelligence

    Cinderella never thought that her success would attach her name to parts of healthcare. Countries’ mental health service is one of them, and its eHealth investment is being held back too. A study in the Journal of Medical Internet Research (JMIR) sets out to explain why. It investigated individual characteristics that influence both preferences and intentions to use eHealth for mental health in Australia. It identifies factors that might inhibit or enable eHealth.


    It found low reported preferences for eHealth for mental health services. Despite this, intentions to access these services are higher. This raises the challenge of how to translate these intentions into activities that use eHealth services. It found that strategies designed to enhance confidence and familiarity and ease people into new Internet-based mental health service programs may be important for increasing the chances of sustainable use. But, will users return to eHealth later? 


    It’s a worthy goal, but the study found that most respondents, almost 86%, prefer face-to-face services. The scope to engage eHealth users was found to be up to 40%. It’s a significant user base that needs supporting.


    Acfee identifies several factors that needed in eHealth to secure benefits. They include:


    • Stakeholder engagement
    • Meeting users’ information requirements
    • Easy to use
    • High level of utilisation. 


    Putting these in place for the 40% will increase the chances of sustainable use and benefits realisation. For Africa, with its limited healthcare resource base, supporting up 40% mental health patients with eHealth access offers a valuable way to expand mental health services at minimal cost. It’s an opportunity. It’s not easy to achieve.


  • Can Africa adopt a modern master patient index?

    Paper patient administration and medical records can be unreliable in sustaining patient identification. Overcoming their limitations needs a sound Master Patient Index (MPI) and effective patient identification as a foundation for dependable eHealth. A white paper from Verato, an MPI vendor, describes a way to do it.


    A thesis in The Future of Healthcare Depends on a New Architecture for Patient Identity Interoperability has five components:

    • Healthcare will involve extensive co-ordination across the full care continuum
    • The ability to access patient information is the cornerstone of co-ordination
    • Resolving patient identities across disparate systems and enterprises is critical to accessing information
    • Current MPI technologies can’t resolve patient identities consistently enough or well enough to support emerging information needs
    • MPIs patient identity resolution technology must support the new needs as part of a highly accurate, national patient identity resolution service.


    Africa’s health systems can apply these criteria to their strategic and procurement choices. They apply to all types of eHealth, not just EHRs. It’s a core requirement for improving healthcare efficiency. It supports a shift from point-in-time service towards effective healthcare co-ordination too.

    Three themes are needed for effective access to patient information: 


    •  Agreed rules and policies for sharing patient data
    • Standardised access protocols and content in EMRs and EHRs
    • Patient identity matching.


    A unique national patient ID number is seen as supporting these. But Verato sees this as logistically

    Impossible, politically untenable because of privacy implications and would not help link people to pre-existing medical records. Relying on basic demographic identifiers such as name, address, birthdate, gender, phone, email, and social security numbers aren’t a solution because they’re prone to error when patients register at receptions and can change over time. About 8 to 12% of people may have more than one identity in any given hospital system, with actual medical histories spread randomly across them.


    MPI matching techniques was invented in 1969, and obsolete. Verato sees the solution as a pre-built, cloud-based, nationwide MPI that healthcare organisations  can plug into. It can avoid the need for extensive algorithm tuning, data standardisation, data governance, data cleansing, or data stewardship. It can help to achieve better compliance with data standards. 


    As Africa’s eHealth moves on, the concept can be assessed as an investment option. If it’s not, then an option to deal with the limitations of conventional MPIs may be needed.


  • Limited IOp’s a drag on benefits

    For several years, health informaticians and other eHealth’s ICT experts have recognised the link for effective Interoperability (IOp) and eHealth benefits. Now, US finance executives have added to the case for more IOp.


    A US Healthcare Financial Management Association (HFMA) survey of 117 financial executives identified their views. It found an increasing need for an increased IOp priority, slightly up to from 68% in 2015 to over 70%. Almost a quarter, 24%, said their organisations can’t share data effectively with other providers and payers.


    Their views extended to external and internal IOp. Both are seen as a combined, upcoming primary focus of healthcare providers. Three drivers are:


    • Current shortcomings
    • Anticipated future need
    • Increasing demand for access to numerous data sources.


    While the survey may not have revealed much that’s new about IOp, it’s a valuable reminder that progress is slow. For Africa’s health systems, it confirms the long timescales needed to reach high IOp levels. If it’s taking the rich US health systems so long, Africa’s can’t expect rapid results. Slow, steady and sustained seem to be their IOp plan.