• Economics
  • The pressure’s on for South Africa’s health system

    South Africa's credit rating was downgraded by Moody’s, the rating agency, on 12 June 2017. This came after Fitch and Standard & Poor's downgraded the country to junk status in March. The consequences of the downgrade are far reaching. It will affect the countries’ ability to borrow money and the healthcare system will feel the pressure too. It’ll probably knock on to eHealth too.

    Health systems and policy manager at the Rural Health Advocacy Project (RHAP), Russell Rensburg, in an article in allAfrica, warns that "We are facing a financial crisis in health and it is being ignored." He says the recession will reduce the level of taxable income as companies become reluctant to invest and create jobs in South Africa. Public spending’s also likely to shrink as more cash goes to service debt.

    So what does this all mean for the healthcare sector? There’s going to be far less money to spend on an already fragile system.

    The real life impacts will be immense and felt sooner rather than later. In September 2016, South Africa introduced new HIV treatment guidelines that now offer Antiretroviral (ARV) drugs to all people who’ve tested HIV positive. As a result, the number of people on HIV treatment will double from 3.5 million to over seven million.

    The health department's deputy director general for HIV, Yogan Pillay has said "By 2025, the health department aims to have 90% of all people diagnosed with HIV on treatment, and by then, the number of people with HIV would also have increased.  "Increasingly limited resources and competing needs are real problems to us,"

    But Rensburg says there may not even be sufficient funding to sustain existing programmes. Symptoms of the budget constraints are already showing. Specialists are still fleeing the under-resourced public sector. The South African Medical Association (Sama) says KwaZulu-Natal has only two public sector oncologists left.  Durban has none. The situation isn’t much better for other specialists with only two urologists left in the province.

    Information presented at the health budget vote in March shows KwaZulu-Natal Department of Health running a deficit of more than ZAR1-billion this year. This includes a ZA R500 million shortage for HIV treatment for 2017/2018. While KwaZulu-Natal may be the first to crumble, Rensburg warns that the public health system is failing nationally, and other provinces may not be far behind.

    The North West Department of Health has already started closing clinics and will cut 2,000, or 20%, of its public sector health jobs to curb rising costs. North West’s spokesperson Tebogo Lekgethwane confirmed the cuts are needed to accommodate smaller budgets.

    How will the restricted resources and added pressure to the healthcare systems impact innovation and implementation of eHealth and mHealth initiatives? Their value and benefits now need to be more explicit, measurable, clear and tangible than ever before to make it worth the investment in the setting of shrinking resources.

  • Africa’s GDP set to take a tumble

    Economic growth provides extra resources for governments. Then they have more to spend on public services, including public health and healthcare. eHealth, towards the end of the chain can expect more money too. It’s not good news that the International Monetary Fund (IMF) has forecast a dip in Africa’s GDP growth.

    Sub-Saharan Africa Regional Economic Outlook: Restarting the Growth Engine says sub-Saharan Africa’s (SSA) economic growth’s fragile. In 2016, it slowed in about two-thirds of the countries, accounting for 83% of GDP. IMF now estimates it to be just 1.5%, the worst performance in over two decades. For 2017, it estimates GDP growth as 2.5%, but not sustainable, driven largely by one-off factors in the three largest countries.

     Nigeria: higher public spending ahead of elections Angola: the fading of effects of droughtSouth Africa: modest improvements in terms of trade.

    While some countries can still expected to their GDP to grow between 5% to 7.5%, the underlying regional momentum’s weak, and down on trends. It’s also just exceeding population growth, a crucial drawback for health and healthcare. 

    Angola, Nigeria, and the Central African Economic and Monetary Community (CEMAC) are adversely affected by low oil prices and the resulting budgetary revenue losses and balance of payments pressures. Other commodity exporters, such as Ghana, Zambia, and Zimbabwe are facing larger fiscal deficits too. 

    Côte d’Ivoire, Kenya, and Senegal, which don’t depend so much on commodities, fiscal deficits have been high for several years as governments aimed to address social and infrastructure deficits.  While their growth remains robust, vulnerabilities are starting to emerge. Public debt’s rising, borrowing costs are up, some arrears are emerging and the banking sector’s non-performing loans are increasing. 

    The IMF says outlook is affected by drought, pests and insecurity. About half of SSA countries report food insecurity.

    Adding North Africa to the SSA forecasts also shows a slight drop in 2017 average GDP growth too, with a pick-up in 2018. It’s not all doom and gloom. An important feature of the IMF data’s that 42% of African countries are still forecast to grow more than the continent’s average. About 52% are forecast to achieve it in 2018. In 2016, GDP was more skewed, with about two thirds of Africa’s countries above average. Will this forecast deterioration translate into Africa’s eHealth having an widenning gap too?

  • 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 lifecycleHelps to manage progressions across stages of maturityImproves the rigour of evidence, optimise allocations of scarce and finite resourcesFacilitates 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 outcomesAlign these with mHealth solutions’ broader stages of maturity and evaluationIncorporate into M&E activities and match outputs to stakeholders’ evidence needsFit 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.

  • Africa’s relative poverty is increasing

    Poverty and poor health worldwide are inextricably linked, and it’s both a cause and a consequence of poor health, which traps communities in poverty. The Health Poverty Action (HPA) initiative’s clear about it, and says links between poverty and poor health are:

    Economic and political structures that sustain poverty and discrimination need to be transformed for poverty and poor health to be tackledMarginalised groups and vulnerable individuals are often worst affected, and deprived of the information, money or access to health services that would help them prevent and treat diseaseVery poor and vulnerable people may have to make harsh choices, knowingly putting their health at risk because they can’t see their children go hungryCultural and social barriers faced by marginalised groups, including indigenous communities, can mean they use health services less, with serious consequences for their health, perpetuating their disproportionate levels of povertyCosts of doctors’ fees, courses of drugs and transport to reach health centres can be devastating for poor people and their relatives who care for them or help them reach and pay for treatmentIn the worst cases, the burden of illness may mean that families have to sell their properties, take their children out of school to earn money, sometimes  by beggingCaring burdens are often taken on by female relatives who may have to give up their education, or take on waged work to help meet households’ costsMissing education has long-term implications for women’s opportunities and their healthOvercrowded and poor living conditions can contribute to the spread of airborne diseases such as tuberculosis and respiratory infections such as pneumoniaReliance on open fires or traditional stoves can lead to deadly indoor air pollutionA lack of food, clean water and sanitation can be fatal.

    The Economist has reviewed data from the World Bank.  The good news is that the number of people living in absolute poverty, defined as having less, than US$,90 a day at 2011 purchasing parity, has dropped from over 1.8 billion in 1990 to under 0.8 billion in 2013, down by about 55%. Within this considerable achievement, Sub Saharan Africa’s (SSA) relatively worse off.

    In 1990, about 15% of its population were in absolute poverty. In 2013, it was approaching 50%. Two reasons are first, absolute poverty in South Asia and East Asia and the Pacific has dropped enormously. Second, Africa’s population has expanded by about 2.5% a year, more than twice Asia’s growth rate. SSA’s absolute poverty rate has dropped from 54% to 41%, but the relatively high population growth means that more people in SSA are now living in absolute poverty.

    For many years, SSA’s been attributed with a relatively high burden of disease. Now that other global regions are pulling away from absolute poverty, it has an increasing relative absolute poverty burden. The HPA commentary indicates a heightening challenge. It’s clear where Africa’s eHealth’s focus should be.

  • Healthcare can save billions with eHealth transformation

    Over the years, there’s been many claims that eHealth can save money. By savings, they usually mean resources can be liberated and redeployed. Accenture researchers have projected that healthcare organisations in the US could save as much as US$60 billion collectively from strategic eHealth investment. An article in HealthcareITNews says Accenture’s report Digital Affectability: Quantifying the Economic Impact of Digital Assets pinpoints six services ready for significant savings. They’re Alzheimer’s, breast cancer, Congestive Heart Failure (CHF), diabetes, HIV and multiple myeloma.  

    Accenture also found that US$2 billion could be avoided every year by using eHealth to predict and mange CHF more effectively. Diagnosing Alzheimer’s early can yield significant savings too.

    “We’ve found that the highest-impact digital opportunities often lie outside the chronic, high-prevalence diseases that receive the most investment attention,” the report authors wrote. “Our analyses showed that 50 percent of system costs can be prevented by targeting investments to rarer, specialized disease states with lower prevalence.” 

    The report goes onto say that “Understanding the economic value potential of digital assets in distinct therapeutic areas and across the patient journey paves the way for the development of products, services and solutions that will optimize returns—for patients, as well as the business.”

    Seeing the long term value and savings in investing in healthcare technology is critical. Acfee’s keen on healthcare organisations understanding the eHealth costs, change management and risks of the investment needed to achieve the benefits. The report reveals eHealth’s potential impact on health systems’ costs. The report shows actual value in dollars of cost reduction in each disease across the phases of prevention, early diagnosis, intervention and monitoring.

    It shares critical insights for African countries starting to invest in eHealth. Africa’s health systems, with their constrained resources, often wrestle with eHealth investment when the benefits can’t bee seen in the short term and seem extremely challenging to realise.

  • MEASURE provides advice on eHealth investment decisions

    Taking decisions on new eHealth is complex. There are many factors to assess and weigh. A technical brief from MEASURE can help to move from ad hoc to rational decisions. It identifies eleven components that decision takers need to consider.

    Severity of disease                           Average population health         Ease of implementation                                 Emergency situations                     Burden of disease                             Economic growthIrresponsible behaviour                                 Vulnerable populations                                  Budget impact                                                                         Disease of the poor                          Cost effectiveness.

    These have four decision criteria. They’re evidence-based medicine, burden of disease, cost-effectiveness and equity. Burden of disease and cost-effectiveness are decision component that are also a decision criteria. Examples of criteria are:

    Anticipated impact: what’s the magnitude of an intervention’s impact expected on health outcomes or on quality of care?Costs and expenses: will the intervention require buying expensive equipment, such as servers that need maintaining?Usability: is the software easy to use or will it need intensive training for expected users?

    Long-standing, proven business cases, such as the five case model, have important extra decision components. One’s the realism of eHealth procurement. This needs assessing rigorously in a business case before the procurement stage’s reached to ensure that suppliers can meet requirements. Another’s healthcare organisations’ capacity and capability to succeed with the whole eHealth life-cycle that stretches from engagement, planning and design, ICT, and on to benefits realisation. These softer costs can exceed health ICT costs, so are an essential resource that need including in eHealth projects’ financial and economic models.

    Another’s efficiency. eHealth can improve productivity, often in numerous small margins across several healthcare resources. Their contributions to benefits can exceed significantly the estimated value of other benefits. They can create opportunities to expand healthcare’s capacity, but the decisions are complex.

    For large-scale eHealth, such as EHRs and Health Information Exchange (HIE), the wide range and types of healthcare, patients, communities and research activities covered can be beyond the scope of cost-effectiveness. For these, Cost Benefit Analysis (CBA) may be more appropriate.

    Three specific themes are essential. One’s sustainability, especially the availability of comprehensive and reliable connectivity that may depend on entities beyond the health sector. Second’s cyber-security, that’s become a big issue in eHealth. It needs continuous monitoring, learning, skill development and training for all users.

    The third’s risk mitigation. eHealth investment is risky. Risk’s a cost, and unmitigated, can increase costs by more than 40%, and in some cases, Acfee has found unmitigated risk costs of some 500%. It’s a vital component of all eHealth decisions.

    MEASURE’s technical brief provides helpful advice on several components needed for a sound eHealth business case. It’s a welcome step forward.

  • An eHealth costs checklist is handy for business cases

    For large scale eHealth, estimating the Total Cost or Ownership (TCO) can be a tortuous process. Athena Health, a cloud service provider, has guidelines that can help. Health Care IT: The Real (and Hidden) Costs of Ownership adds to costs that are often omitted from some TCO models. It can be used as a foundation for converting into both economic and financial costs, which are related, but not the same. While the cost items included are more than US methodologies, they’re still not complete. Examples are costs of engaging and consulting stakeholders, and for financial costs, depreciation and debt servicing.

    The first task’s to set the eHealth life-cycle.

    One-time eHealth implementation costs include:Initial software license fees                        Staff trainingInitial hardware acquisitionMaintenance fees           Interface fees   Implementation feesOngoing eHealth costs:Annual fees including upgrades                                  Software maintenance feesStaff training for upgrades                             Future product purchasesBackup and disaster recovery                    Server feesOngoing operating labour costs:Full Time Equivalent (FTE) clinical document managementFTE ICT personnel                                                 FTE billing office personnelFTE front office and front desk personnelFTE P4P Programme support                        FTE patient communications personnelOngoing operating non-pay costs:Patient statements administration       LockboxEligibility checking          Electronic Document Interchange (EDI) transaction feesClearinghouse feesTranscription    Paper claim storagePatient no-shows                                                Billing under-performanceOther costs not in Athena’s checklist include:Change management, including workflow standardisationProject managementRisk exposure where up to 70% percent of healthcare providers are dissatisfied with their EHRs and healthcare professionals spend more time on documentation.

    Estimating benefits is not as easy as estimating costs. Many are the potential to redeploy numerous small amounts of resources across healthcare activities. Many are intangible and need sophisticated techniques. They include:

    Increased efficiency and quality, such as fewer interruptions and distractionsBetter care coordination among providersAgility and an ability to scale eHealth up or down quickly as organisation evolveResponsive to changes in reimbursement models, reporting, clinical requirements, and otherregulationsRegulation compliance by having the right reporting, data and workflows in place to meet new mandates and standardsIntegration ability to build effective, low-cost links to clinical partners, such as laboratories, imaging pharmacies, to exchange information, and build and connect with expanding mHealth programmesMitigated risks with high adoption and user satisfaction where up to 70% percent of healthcare providers are dissatisfied with their EHRs.

    Costs and benefits over timescales need converting into Net Present values (NPV) using Discounted Cash Flow (DCF). For TCOs for public healthcare organisations, a discount rate of about 3%’s appropriate.  There’s a recognised tendency for estimators to suffer from optimism bias. Estimated costs need adjusting for it. For eHealth, it can be between 40% and 100%.

  • Africa’s eHealth financing’s not typical – unpacking WHO's 3rd Global Survey on eHealth

    Sustainable eHealth is a goal for Africa. Affordability is a crucial component. WHO Global Survey 2015, the data source for 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. 

    Chapter 1 provides insights. It shows a profile of four main sources. Africa’s is very different, confirming one of its biggest challenges, securing sufficient sustainable eHealth finance. The comparison is:

    The telling challenge is that Africa’s reliance on donor and public finance is nearly as much as the global rate for public finance. It’s widely recognised in Africa that this is not sustainable enough, but realigning it to match the global profile more closely isn’t realistic in the medium term.

    Instead, a strategy of seeking donor support for non-recurring resources that matches Africa’s eHealth priorities seems a better option. This isn’t easy either. Africa’s eHealth needs investment in a wide range of capacities and infrastructure to expand and deepen its foundations. This can be less attractive to donors who have their own priorities that are often for more visible and tangible projects.

    The other important feature is that PPP is close to the global average too. PPP often has high operational costs and limited risk sharing and almost no risk transfer. It’s attractive to start up big scale eHealth programmes, but its annual operating costs can be extremely rigid and onerous. If WHO’s survey shows Africa moving towards PPP instead of the more demanding initiative of expanding public finance, it signals a need for rigorous financial and risks assessments as part of a robust business case before proceeding.  

    eHNA’s posted on an extreme example of a crashed PPP. The health system believed it had transferred the risk, but the legal system didn’t see it that way.


    Image from the global eHealth observatory report 

  • Africa’s GDP’s shrinking a bit

    Like many countries, the scale of Africa’s healthcare, so eHealth, depends on Gross Domestic Product (GDP) growth, population expansion and political priorities. The report from the IMF Regional Economic Outlook Sub-Saharan Africa Time for a Policy Reset, as it title suggest, shows some signs of concern, but it may not be all gloom.

    Comparisons of GDP and GDP per head since 2004, show that the estimate growth for 2017 might be slowing down compared to earlier highs. While the estimated growth rate of 4% is 1% higher than 2016’s 3%, it’s lower than the average growth rate of 4.3% since 2004. It might not be much, but it could constrain eHealth investment.   

    GDP per head shows slightly different position. Estimated growth in 2017’s 1.6%, 1% up on 2016’s growth, but a shade closer to the average of 1.8% since 2004. As Africa’s population continues to expand, GDP isn’t keeping up. The average GDP growth per head’s less than half the overall GDP growth rate, but the curve is wide.

    A simple comparison of 45 African countries’ changes shows:




    2017 to 2016GDP




    GDP per Head








    2017 to Average Since 2004GDP




    GDP per Head








    It’s not possible to say that Africa’s GDP’s on a new trajectory. The IMF seems to think it is. It says it’s “Time for a Policy Reset Economic activity in sub-Saharan Africa has weakened markedly, but, as usual, with a large variation in country circumstances.”  This may extend to the resources for eHealth. The next set of IMF numbers might shed more light.

  • How will Africa’s falling GDP affect eHealth?

    Recent high growth in Africa’s Gross Domestic Product (GDP) has increased the possibility of eHealth being more affordable. It looks set to take a bit of a knock. An article in Nigeria’s Business Post describes Sub-Saharan Africa’s (SSA) latest, low GDP forecast from the World Bank.

    While GDP growth may range across SSA countries, the average forecast’s a drop to 1.6%, the lowest level in twenty years, and nearly half of 2015’s 3%. The weak performance is mainly due to deterioration in the continent’s largest economies: Nigeria and South Africa. Together, they comprise half the region’s output. Ethiopia, Rwanda, and Tanzania have continued to achieve annual average growth rates of over 6%. Côte d’Ivoire and Senegal have recently joined the ranks of top performing countries. Resilient SSA countries show more diversified export structures. They’ve also made more progress on structural reforms, business regulation, rule of law and government effectiveness. It’d be good to see eHealth adding to healthcare effectiveness.

    Adjusting to low commodity prices has affected several commodity exporters as vulnerabilities have increased. Measures are now needed to:

    Strengthen domestic resource mobilisationReduce over dependence on resource-based revenuesIncrease agricultural productivity, central to transforming SSA economiesAddress the quality of public spending and the efficiency of resource, an objective more critical than addressing the level of spending.

    Stimulating countries eHealth supply and developers could be part of this, especially if their solutions can be transferable and exported. Could it be the key to avoiding eHealth affordability and sustainability risks?