Tag Archives: Low-income

Private Consultations More Effective than Public Provision in Rural India

Doing work across high-income countries (CLAHRC WM) and lower income countries (CLAHRC model for Africa) provides interesting opportunities to compare and contrast. For example, our work on user fees in Malawi [1] mirrors that in high-income countries [2] – in both settings, relatively small increments in out-of-pocket expenses results in a large decrease in demand and does so indiscriminately (the severity of disease among those who access services is not shifted towards more serious cases). However, the effect of private versus public provision of health care is rather more nuanced.

News Blog readers are likely aware of the famous RAND study in the US.[3] People were randomised to receive their health care on a fee-for-service basis (‘privately’) vs. on a block contract basis (as in a public service). The results showed that fee-for-service provision resulted in more services being provided (interpreted as over-servicing), but that patients were more satisfied clients, compared to those experiencing public provision. Clinical quality was no different. In contrast, a study from rural India [4] found that private provision results in markedly improved quality compared to public provision, albeit with a degree of over-servicing.

The Indian study used ‘standardised patients’ (SPs) to measure the quality of care during consultations covering three clinical scenarios – angina, asthma and the parent of a child with dysentery. The care SPs received was scored against an ideal standard. Private providers spent more time/effort collecting the data essential for making a correct diagnosis, and were more likely to give treatment appropriate to the condition. First, they compared private providers with public providers and found that the former spent 30% more time gathering information from the SPs than the public providers. Moreover, the private providers were more likely to be present when the patient turned up for a consultation. There was a positive correlation between the magnitude of fees charged by private providers and time spent eliciting symptoms and signs, and the probability that the correct treatment would be provided. However, the private providers are often not doctors, so this result could reflect different professional mix, at least in part. To address this point, a second study was done whereby the same set of doctors were presented with the same clinical cases – a ‘dual sample’. The results were even starker, with doctors spending twice as long with each patient when seen privately.

Why were these results from rural India so different from the RAND study? The authors suggest that taking a careful history and examination is part of the culture for US doctors, and that they had reach a kind of asymptote, such that context made little difference to this aspect of their behaviour. Put another way, there was little headroom for an incentive system to drive up quality of care. However, in low-income settings where public provision is poorly motivated and regulated, fee-for-service provision drives up quality. The same seems to apply to education, where private provision was found to be of higher quality than public provision in low-income settings – see previous News Blog.[5]

However, it should be acknowledged that none of the available alternatives in rural India were good ones. For example, the probability of receiving the correct diagnosis varied across the private and public provider, but never exceeded 15%, while the rate of correct treatment varied from 21% to about 50%. Doctors were more likely than other providers to provide the correct diagnosis. A great deal of treatment was inappropriate. CLAHRC West Midlands’ partner organisation in global health is conducting a study of service provision in slums with a view to devising affordable models of improving health care.[6]

— Richard Lilford, CLAHRC WM Director


  1. Watson SI, Wroe EB, Dunbar EL, et al. The impact of user fees on health services utilization and infectious disease diagnoses in Neno District, Malawi: a longitudinal, quasi-experimental study. BMC Health Serv Res. 2016; 16: 595.
  2. Carrin G & Hanvoravongchai P. Provider payments and patient charges as policy tools for cost-containment: How successful are they in high-income countries? Hum Resour Health. 2003; 1: 6.
  3. Brook RH, Ware JE, Rogers WH, et al. The effect of coinsurance on the health of adults. Results from the RAND Health Insurance Experiment. Santa Monica, CA: RAND Corporation, 1984.
  4. Das J, Holla A, Mohpal A, Muralidharan K. Quality and Accountability in Healthcare Delivery: Audit-Study Evidence from Primary Care in India . Am Econ Rev. 2016; 106(12): 3765-99.
  5. Lilford RJ. League Tables – Not Always Bad. NIHR CLAHRC West Midlands News Blog. 28 August 2015.
  6. Lilford RJ. Between Policy and Practice – the Importance of Health Service Research in Low- and Middle-Income Countries. NIHR CLAHRC West Midlands News Blog. 27 January 2017.

Living on Less Than One Dollar per Day

Sam Watson recently drew my attention to this fascinating article by my heroes – Adhijit Banerjee and Esther Duflo.[1] How do people in the “bottom billion” spend an income of around $1 per day? The authors turn to household surveys covering 13 countries in Asia, Africa and Central America (one assembled by the World Bank, and the others by the RAND Corporation). Even though it is hard to get a full stomach on $1 per day and many are hungry, not all money is spent on food – the proportion varies from a half to three-quarters of income spent on food. Nor are the cheapest foods always selected – taste crowds out Calories, even if that leaves you hungry. The second largest source of expenditure is festivals, such as weddings and funerals. Radios are a priority and show elastic demand on income. There is an inverse relationship across countries between spending on radios and on festivals. Asset ownership is very low – even in rural areas bicycle ownership is low – at a third of households or less. Education attracts a very low proportion of expenditure; 2-3% of the household budget in Pakistan, for example. People often feel hungry, many are anaemic, and energy levels are low. Illness rates are high and anxiety common when compared to high income countries. I guess many are in a poverty trap and need a little help to get them out of it, but the results resonate with the Gospel of Matthew, ‘Man shall not live by bread alone’.

— Richard Lilford, CLAHRC WM Director


  1. Banerjee AV & Duflo E. The Economic Lives of the Poor. J Econ Perspect. 2007; 21(1): 141-67.

Do Cash Transfers to the Poor Encourage Feckless Behaviour?

In a brilliant working paper, Evans and Popova consider whether non-conditional cash transfers encourage people in low-income countries to increase their use of ‘temptation goods’, such as tobacco and alcohol.[1] Their systematic review found 19 studies. The answer to the question is ‘no’, there is no positive effect on consumption of temptation goods. This effect is confirmed if the analysis is confined to randomised trials. In fact the point estimate signifies lower consumption of the temptation goods in association cash transfers. The extra money provided by the cash transfers seems to be wisely invested, for example, in childhood education. Of course, this does not mean that there are no instances where someone (usually a man I am afraid) took money (which is usually given to a woman) in order to go drinking. But then, it is a poor heart that never rejoices!

— Richard Lilford, CLAHRC WM Director


  1. Evans DK, Popova A. Cash Transfers and Temptation Goods. University of Chicago, IL. 2016.

Neighbourhood Effects and Child Development – Long-Term Results of a RCT

Adults and children in high-income areas fare better than those in low-income areas, as we pointed out in a recent post. What would happen if families from low-income areas moved to high-income areas? This was evaluated in a famous experiment called the “Moving to Opportunity Experiment”, conducted in the 1990s in the USA. Families were randomised to receive or not receive a voucher that enabled them to move from a low to a higher income neighbourhood. Intention-to-treat (ITT) analysis showed that the opportunity to move was associated with improved physical and mental health among adults, despite the fact that only about half of the families in the intervention group availed themselves of the voucher. There were no effects on earnings or employment of these adults, but what about the development of the children? A further cut of the data relating to children has now been published,[1] again using ITT principles, and children under 13 years old when they were randomised to receive the voucher had much better prospects than controls. They were more likely to go to college and experienced substantially higher incomes than control children. However, children who were older when they had an opportunity to move experienced slightly negative effects, consistent with findings by CLAHRC WM.[2] In the older children it is speculated that the effects of disruption outweighed the benefits of the new neighbourhood on average. Inward migration did not appear to have any negative consequences for the receiving communities. This is a fascinating social experiment, up there with the original ‘Head Start’ study of an intervention to support poor, single mothers.[3] What are the policy corollaries? The finding supports policies to prevent the poor concentrating in ghettoes like the banlieues around Paris and the stark segregation of middle class people in gated compounds increasingly seen in African cities. Such policies are further supported by evidence from our last blog showing that the health or poor people was enhanced, rather than undermined, by proximity to richer families.

— Richard Lilford, CLAHRC WM Director


  1. Chetty R, Hendren N, Katz LF. The Effects of Exposure to Better Neighbourhoods on Children: New Evidence from the Moving to Opportunity Experiment. Am Econ Rev. 2016; 106(4): 855-902.
  2. Singh SP, Winsper C, Wolke D, Bryson A. School Mobility and Prospective Pathways to Psychotic-like Symptoms in Early Adolescence: A Prospective Birth Cohort Study. J Am Acad Child Adol Psychiatry. 2014; 53(5): 518-27.
  3. Currie J, & Thomas D. Does Head Start Make a Difference? Am Econ Rev. 1995; 85(3): 361-4.

Correlation between Schooling and Per Capita GDP Growth

Previous studies have found only a modest correlation between mean years of schooling and GDP growth in low- and medium-income countries (LMICs). But the educational content of a given number of school years varies enormously – on average, school leavers in Honduras are over an unconscionable six years behind their age-controlled peers in Singapore in Science and Maths competence. A recent paper from ‘Science’ [1] shows that it is school achievement that is important and in logistic regression accounts for over half of the variance between countries in growth rate, conditional on economic starting point, and the temporal relationships all but exclude reverse causality. Of course, it is possible that there is some other ingredient that causes both school and economic attainment in the high economic growth countries. The CLAHRC WM Director hypothesises that knowledge is not just knowledge – education has a deeper effect on the psyche leading to a more empathetic, altruistic person. As the old quote has it, “education is what is left after all the facts have been forgotten.” Is this hypothesis testable?

— Richard Lilford, CLAHRC WM Director


  1. Hanushek EA, & Woessmann L. Knowledge Capital, Growth, and the East Asian Miracle. Science. 2016; 51 (6271): 344-5.

How Many Doctors Do We Really Need?

In a previous post we blogged about the changing nature of medical practice: the influences of regulation, guidelines, sub-specialisation, and patient expectations. We mentioned skills substitution, whereby less experienced staff take on tasks previously carried out by doctors. We also mentioned the role of Information Technology, but shied away from discussing the implications for medical manpower. However, it seems important to ask whether Information Technology could reduce the need for medical input by increasing the scope for skill substitution. Some patients have complex needs or vague symptoms, and such patients we assume will need to be seen by someone with deep medical knowledge to underpin professional judgements, and to provide patients with such an informed account of the probable causes of their illness and the risks and benefits of viable options. But much of medicine is rather algorithmic. A patient presents with back pain – follow the guidelines and refer the patient if any ‘red flags’ appear, for example. Many of the criteria for referral and treatment are specified in guidelines. Meanwhile, computers increasingly find abnormal patterns in a patient’s data that the doctor has overlooked. Work in CLAHRC WM shows that many patients do not receive indicated medicines.[1] Health promotion can be delivered by nurse and routine follow-up cases triaged by Physician Assistants. A technician can be trained to perform many surgical operations, such as hernia repair and varicose vein removals, and Physician Assistants already administer anaesthetics safely in many parts of the world.[2] Surely we should re-define medicine to cover the cognitively demanding aspect of care and those where judgements must be made under considerable uncertainty.

In the USA they talk about “people working up to their license”. What they mean is that it is inefficient for people to work for extended periods at cognitive or skill levels well below those they have attained by virtue of their intellect and education. Working way below the level is not only inefficient, but deeply frustrating for the clinician involved, predisposing them to burn out. Use doctors to doctor, not to fill in forms and perform routine surgical operations.

We conclude by suggesting that there is a case for re-engineering medical care or at least articulating a forward vision. The next step is some careful modelling, informed by experts, to map patterns of practice, assign tasks to cognitive categories, and calculate manpower configurations that are both safe and economical. Such a process would likely identify a more specific, cognitively elite role for expensive personnel who have trained for 15 years to obtain their license. In turn, this may suggest that less people of this type will be needed in the future.

While high-income countries should address the question “how much should we reduce the medical workforce, if at all?”, low-income countries face the reciprocal question, “by how much should we increase the medical work-force?” Countries such as Kenya have only two doctors per 10,000 population, compared to 28 in the UK, and 25 in the United States.[3] Much of the shortfall is covered by other cadres, especially medical officers (who work independently), and nurses. Health personnel are strongly buttressed by community health workers, a type of health worker that we have discussed in previous posts.[4] [5] Information Technology is unsurprisingly very under-developed in low-income countries, although telemedicine is increasingly used. It is particularly difficult to attract doctors to work in rural areas, and there is the perennial issue of the medical brain drain. The time is thus propitious to consider carefully the human resource needs not just of high-, but also of low- and middle-income countries, and consider how these may be affected by improving Information Technology infrastructure.

— Richard Lilford, CLAHRC WM Director


  1. Wu J, Yao GL, Zhu S, Mohammed MA. Marshall T. Patient factors influencing the prescribing of lipid lowering drugs for primary prevention of cardiovascular disease in UK general practice: a national retrospective cohort study. PLoS One. 2013; 8(7): e67611.
  2. Mullan F & Frehywot S. Non-Physician Clinicians in 47 Sub-Saharan African Countries. Lancet. 2007; 370: 2158-63.
  3. World Health Organization. Health Workforce: Density of Physicians (total number per 1000 population): Latest available year. 2015.
  4. Lilford RJ. Lay Community Health Workers. NIHR CLAHRC West Midlands News Blog. 10 April 2015.
  5. Lilford RJ. An Intervention So Big You Can see it From Space. NIHR CLAHRC West Midlands News Blog. 4 December 2015.

The Obesity Challenge is Very Real, but What About Extreme Low Weight?

A body mass index under 16 in women is associated with anorexia in rich countries, but with malnutrition in low- and middle-income countries. It is associated with reduced life span, but the effects of energy supplementation in people who were seriously malnourished as children are uncertain. A recent cross-sectional study of over 40 countries using Demographic and Health Surveys shows a pooled incidence of extreme underweight of 1.8% (standardised for age). The prevalence is highest in India at over 6% and Bangladesh at over 3%.[1] Rates are declining quite rapidly in these countries, but overall at a very low rate and in some countries they are actually increasing.

— Richard Lilford, CLAHRC WM Director


  1. Razak F, Corsi DJ, Slutsky AS, et al. Prevalence of Body Mass Index Lower Than 16 Among Women in Low- and Middle-Income Countries. JAMA. 2015; 314(20): 2164-71.

An Intervention So Big You Can See it From Space

Over the last two decades there have been innumerable health service interventions around the world. But there has been nothing as large as the development of lay Community Health Workers (CHWs). By way of example, Africa is set to acquire around one million CHWs by the end of this year.[1] Moreover, the success of CHWs in low- and middle-income countries (LMICs) has inspired policy makers to increase CHW deployment in high-income countries (HICs), in places as far apart as New York [2] and Wales.[3]

In a previous blog we showed RCT and observational evidence that attests to the overall effectiveness of CHWs.[4] [5] They appear most effective when they are well supported, both in their communities and in the local health service. Much is made in sociological studies of the local roots of CHWs – they are ‘of the people, for the people’. Their motivation rests on their close link to the communities they serve and is strongly related to the esteem in which they are held.[6]

However, the fundamental nature of CHWs is changing. To an ever-greater extent, governments in LMICs are turning to CHWs to solve pressing problems. As they are doing the bidding of the government, they increasingly get paid for their work. Their emoluments might not be great, but all public expenditure must be accounted for. So CHWs no longer just ‘emerge’ – they must be appointed and trained, and they can be fired. India, for example, provides employment for no less than 600,000 CHWs on the basis of fee-for-service.[7] Their link to the health services is becoming more formal – they are a part of the family health teams in Brazil, for example. It would appear that the cadre of CHWs is being professionalised, albeit at different rates in different places.

It is appropriate to ask whether something may be lost in this process of professionalisation. For example, it has been shown that extrinsic motivation can ‘crowd out’ intrinsic motivation.[8] If the direction of travel is towards professionalisation, then this has implications for management of the service. It may be advisable to go with the grain and provide or facilitate privileges that other professions have, such as professional societies and well sign-posted opportunities for advancement and promotion. It will also be important to recognise that the market-clearing price for CHWs is likely to inflate, in part because of the putative crowding out of intrinsic motivations, but also because of generally improving salaries in emerging economies.

The CLAHRC WM Director hypothesises that many CHWs are going through an uncomfortable period, where they lose some of the satisfaction and kudos that comes with being a volunteer, but still lack the status, pay, and camaraderie of a fully-fledged profession. Different countries will deal with this phenomenon in different ways – in Ethiopia, for example, two cadres of CHWs have come into existence, one more formal than the other. CLAHRC Africa is actively studying education for CHWs and the ideal work configurations in two projects supported by the Medical Research Council, UK. This work complements CLAHRC WM studies on the use of unpaid lay health workers in improving outcomes for pregnant women with high social risk, e.g. single teenage parents (see previous blog).

— Richard Lilford, CLAHRC WM Director


  1. Singh P, Sachs JD. 1 million community health workers in sub-Saharan Africa by 2015. Lancet. 2013; 382: 363-5.
  2. Peretz PJ, Matiz LA, Findley S, et al. Community Health Workers as Drivers of a Successful Community-Based Disease Management Initiative. Am J Public Health. 2012; 102(8): 1443-6.
  3. Johnson CD, Noyes J, Haines A, et al. Learning from the Brazilian community health worker model in North Wales. Global Health. 2013; 9: 25.
  4. Lilford R. Lay Community Health Workers. CLAHRC WM News Blog. April 10 2015.
  5. Lewin S, Munabi-Babigumira S, Glenton C, et al. Lay health workers in primary and community health care for maternal and child health and the management of infectious diseases. Cochrane Database Syst Rev. 2010; 3: CD004015.
  6. Glenton C, Colvin CJ, Carlsen B, Swartz A, Lewin S, Noyes J, Rashidian A. Barriers and facilitators to the implementation of lay health worker programmes to improve access to maternal and child health: qualitative evidence synthesis. Cochrane Database Syst Rev. 2013; 10: CD010414.REF
  7. Singh P, & Chokshi DA. Community Health Workers – A Local Solution to a Global Problem. N Engl J Med. 2013; 369(10): 894-6.
  8. Frey BS. How Intrinsic Motivation is Crowded Out and In. Rationality Society. 1994; 6(3): 334-52.

Systematic Review of Effects of User Fees on Uptake of Services in Low- and Middle-Income Countries

This very thorough systematic review screened no less than 24,125 studies reported among 25 databases, but only 16 studies survived the screening process.[1] They were mostly interrupted time series studies, with five controlled before-and-after studies and two cluster experimental studies also. Five studies were concerned with introduction of user fees when none previously existed, and three examined the effect of increasing user fees. The findings show that:

  1. User fees cause a marked reduction in utilisation of curative services, suggesting that demand is elastic to changes in price.
  2. The effect is immediate and does not appear to ‘recover’.
  3. The above effect appears to be less sensitive for preventive services, but this is based on one study only.

The statistical analysis is elegant, comparing slopes (not just mean values) before and after changing fee policy and allowing for any autocorrelation. These study results have been replicated in a systematic review of ‘co-payments’ in high-income countries [2] and are consistent with the model proposed in a previous post.[3]

— Richard Lilford, CLAHRC WM Director


  1. Lagarde M & Palmer N. The impact of user fees on health service utilization in low- and middle-income countries: how strong is the evidence? Bull World Health Organ. 2008; 86(11): 839-48.
  2. Kiil A, & Houlberg K. How does copayment for health care services affect demand, health and redistribution? A systematic review of the empirical evidence from 1990 to 2011. Eur J Health Econ. 2014; 15: 813-28.
  3. Lilford R. User Fees and Co-Payments: The Evidence Accumulates. NIHR CLAHRC West Midlands News Blog. 25 Sept 2015.

How Much for a Year of Human Life?

£20,000 is England’s answer to the above question – this is the threshold price for a year of healthy life according to NICE. This threshold willingness-to-pay (WTP) is based on the concept of the opportunity cost – the value of the treatment that the index intervention should supplant because it is the next best use of money in terms of health benefit per unit cost. The WTP threshold has been the subject of much investigation in England and remains controversial.

The threshold for low- and middle-income countries (LMICs) is also the subject of much discussion and is usually based on mean per capita GDP – for instance the World Bank states that a healthy life year should be valued at the per capita GDP to be highly cost-effective, or three times the per capita GDP to be cost-effective.[1]

A recent article considers methods to determine thresholds for cost-effective interventions [2]; the WTP threshold described above, benchmarking against an intervention already adopted and league tables. Benchmarks invert the logic – they say if it is used, then it is cost-effective. However, health economics is supposed to be normative, and say that if it is cost-effective, then it should be used.

So we can eliminate benchmarks as a credible method, leaving the WTP threshold and league tables in contention. The problem with the latter is that the relative payback of an intervention varies materially across countries. However, it is based on the realism that budgets are limited and ephemeral, and league tables have been constructed for reference purposes, notably the WHO-Choice list [3] and the Tufts cost-effectiveness registry.[4]

The CLAHRC WM Director’s view is that both the WTP threshold and the league table approach have advantages and disadvantages. So, if you have been to all the trouble to calculate an ICER (Incremental Cost-Effectiveness Ratio), then why not use both methods; compare your results with a threshold and also see how the result compares with alternative interventions in a league table?

— Richard Lilford, CLAHRC WM Director


  1. World Bank. World Development Report 1993: Investing in Health. New York: Oxford University Press. 1993.
  2. Marseille E, Larson B, Kazi DS, Kahn JG, Rosen S. Thresholds for the cost-effectiveness of interventions: alternative approaches. Bull World Health Organ. 2015; 93: 118-24.
  3. Tan-Torres Edejer T, Baltussen R, Adam T, et al. Making Choices in Health: WHO guide to cost-effectiveness analysis. Geneva: World Health Organization. 2003.
  4. Tufts Medical Center. Tufts Cost Effectiveness Analysis Registry. 2013.