Tag Archives: Finance

Government vs. Private Schools

CLAHRC WM is not just interested in health care since the methods we use are equally relevant to decision-makers in education, social services, industrial policy, criminology, and so on. We should all be learning from each other. In a previous blog I reported on the (mostly positive) results of the ‘Moving to Opportunity’ experiment in the USA, where families were given an opportunity to move from a deprived neighbourhood to a more salubrious one. So I was interested to spot an RCTs of vouchers that allowed children (over a wide age range) from government schools to attend private schools (also in the USA).[1] The experiment was recent (last five years) and we have outcomes at one year only. Seventy percent of pupils allocated a voucher to attend a private school took up their offer; so both intention to treat and per protocol analyses are reported. The educational outcomes were lower in the intervention group, and were statistically significantly lower for mathematics. This negative effect was greater if the voucher was taken up than if it was not. The negative effect was greater if the child came from a school that was not rated as poor performing than if the previous school was rated satisfactory or good. The negative effect was greatest if the child was in elementary school, and non-significantly positive if they were already in high school.

What caused the negative effect on educational outcomes? Simply moving school does not seem to explain the results, since a proportion of control children moved school with little or no apparent effect. However, private schools provide less instructional time than government schools, especially in elementary school. Other studies have also noted negative effects of moving children to private school on educational outcomes in the short term. But it is far too early to declare the intervention a failure. There is a limit to how much an elementary school child can assimilate, and it is the long-term effects that are important. However, I was surprised by this result – educational interventions have a habit of producing results different to those intended. Full marks to the US Congress, which had the wisdom to evaluate its own policies. The UK Cabinet Office has published a document arguing for more RCTs of policy,[2] and I expect to be able to report the results of further RCTs of educational interventions in the News Blog.

— Richard Lilford, CLAHRC WM Director

References:

  1. Dynarski M, Rui N, Webber A, Gutmann B, Bachman M. Evaluation of the DC Opportunity Scholarship Program. Impacts After One Year. Alexandria, VA: Institute of Education Sciences, 2017.
  2. Haynes L, Service O, Goldacre B, Torgerson D. Test, Learn, Adapt: Developing Public Policy with Randomised Controlled Trials. London: UK Cabinet Office, 2012.

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

References:

  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.

The Second Machine Age

I must thank Dr Sebastiaan Mastenbroek (AMC, Amsterdam) for giving me a copy of the Second Machine Age by Brynjolfsson and McAfee.[1] At first I thought it was just another of those books describing how computers were going to take over the world.[2] Indeed the first part of the book is repetitive and not particularly insightful when it comes to the marvels of modern computers – I recently debated this subject live with another auteur, Daniel Susskind, on BBC World Service. However, the economic consequences of the second machine age are much more adroitly handled. The authors make a case that the wide disparities in wealth that have arisen over the last few decades are not entirely a function of globalization. The coming of computers has also had a large effect by increasing demand for jobs with a high cognitive content while reducing demand at the other end of the intellectual scale. Fortunately the book does not fall into the Luddite error of trying to hold back the progress of technology. That would be like the ancient Ottoman Empire which tried to ban printing. No, progress must continue, but it must be managed. The authors consider a universal income, but argue that it is too early for this. I agree. They also argue for a negative income tax. Such a tax does not act as a disincentive to work and has a lot going for it. All in all, this is one of the more sure-footed accounts of the economic consequences of the second machine age.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Brynjolfsson E & McAfee A. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. New York, NY: W. W. Norton & Company; 2014.
  2. Lilford RJ. A Book for a Change. NIHR CLAHRC West Midlands News Blog. 29 January 2016.

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

Reference:

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

The ‘Robin Hood’ Hypothesis in 33 African Countries

Across low- and middle-income countries (LMICs), over 50% of total health care spending is derived from out-of-pocket expenses. Some of these are formal recognised tariffs in public health systems. However, a proportion are irregular or informal payments (bribes/kick-backs). It is hypothesised that these informal payments are used to subsidise the poor at the expense of the rich after the fashion of Robin Hood in English folklore. Enter results from a series of publically available repeated surveys called ‘Afrobarometer‘. Here public attitudes and experiences relating to democracy and governance are surveyed in 18 African counties. Nationally representative samples of over 25,000 individuals are selected randomly across participating countries. Afrobarometer provides the data for an important study [1] of the extent to which informal payments were elicited across people of different income levels (according to the Lived Poverty Index). Far from confirming the Robin Hood hypothesis, the authors find a higher occurrence of bribe paying among the poorest people across the countries studied – elasticity is negative in that the richer the person, the lower the probability that they will have paid a bribe on attending a health care facility. These results are similar to those obtained in a previous study in Hungary. There is some evidence that the problem is worse in cities where service providers are less likely to have known or have community affiliations with patients. This finding reminds me of the Bible scripture – “For whosoever hath, to him shall be given… but whosoever hath not, from him shall be taken away...” (Matthew 13:12).

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Kankeu HT, Ventelou B. Socioeconomic inequalities in informal payments for health care: An assessment of the ‘Robin Hood’ hypothesis in 33 African countries. Soc Sci Med. 2016; 151: 173-86.

More on Bribes to Access Health Care

Further to the previous study,[1] Kankeu et al. also studied how supply-side factors affect informal payments.[2] In contrast to the previous study across multiple diseases and countries, this study concerns itself with one disease (HIV) and one country (Cameroon). The study was built on a naturally representative survey among people with HIV/AIDs. Like the previous paper, this study concerns not all out-of-pocket payments, but specifically payments above stipulated tariffs – i.e. the focus on informal payments / bribes. The Global Corruption Barometer, published by Transparency International, shows that across all conditions, a third of people who visit a health care facility in Cameroon pay a bribe. As it turns out, bribes are less often exacted from HIV payments. Supply-side factors seem to have a large influenza on bribe payment in HIV patients in the study; 12% in private for-profit facilities, 3% in public, and under 1% in private not-for-profit. The actual amount paid when a bribe is elicited is highest in urban areas and in private for-profit facilities. Importantly, facilities where more than one care provider carries out all tasks required for a given patient have a higher probability of eliciting bribes than those where provision is spread among more than one person. The authors caution that increasing salaries might not reduce bribe taking (rent seeking) and may actually increase in line with a previous News Blog report.[3] In both papers the authors recommend National Insurance systems, and in this particular paper the authors fancy performance-related pay, despite its caveats.

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Kankeu HT, Ventelou B. Socioeconomic inequalities in informal payments for health care: An assessment of the ‘Robin Hood’ hypothesis in 33 African countries. Soc Sci Med. 2016; 151: 173-86.
  2. Kankeu HT, Boyer S, Toukam RF, Abu-Zaineh M. How do supply-side factors influence informal payments for healthcare? The case of HIV patients in Cameroon. Int J Health Plann Manage. 2016; 31(1): E41-57.
  3. Lilford RJ. Improving Health Care From Outside Organisations. NIHR CLAHRC West Midlands News Blog. October 14 2016.

More on Free Goods and Aid Dependency

In a previous News Blog we reported results showing that maintenance of communal lavatories was worse among people who had had a subsidy for lavatory maintenance withdrawn than among those who had never had the subsidy in the first place.[1] The ‘free good’ idea was at work here, whereby people can develop a sense of entitlement. A recent study involved providing free shoes for poor people.[2] Those who received the free shoes were more likely to feel that other people should provide family needs in general than those who had not been given free shoes – classic aid dependency. Handing out free shoes did not increase overall ownership of shoes, foot health or self-esteem; presumably because of ‘fungability’ – people used their shoe money for other purposes. Yet not all ‘free goods’ are bad – a recent paper co-authored by CLAHRC WM researchers showed that even very small user fees reduce access to services in Malawi and this hits the most vulnerable – children – the hardest.[3] Taken in the round this leads to the CLAHRC WM Director’s axiom – “ration health care, but not access to health care.”

— Richard Lilford, CLAHRC WM Director

References:

  1. Garn JV, Sclar GD, Freeman MC, et al. The impact of sanitation interventions on latrine coverage and latrine use: A systematic review and meta-analysis. Int J Hyg Environ Health. 2016. [ePub].
  2. Wydick B, Katz E, Calvo F, Gutierrez F, Janet B. Shoeing the Children: The Impact of the TOMS Shoe Donation Program in Rural El Salvador. World Bank Econ Rev. 2016.
  3. 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(1):595.

Unintended Consequences of Pay-For-Performance Based on Readmissions

Introducing fines for readmission rates crossing a certain threshold has been associated with reduced readmissions. Distilling a rather wordy commentary by Friebel and Steventon,[1] there are problems with the policy since it might not lead to optimal care:

  1. The link between quality of care and readmission is not good according to most studies, so that there is a risk that patients who need readmission will not get it.
  2. In support of the above, less than a third of readmissions are for the condition that caused the previous admission (which is not to say that none are preventable, but it suggests that a high proportion might not be).
  3. Risk-adjustment is at best imperfect.
  4. And this probably explains why ‘safety net’ hospitals caring for the poorest clientele come off worst under the pay-for-performance system.

I refer it my iron law of incentives – ‘only use them when providers truly believe that the target of the incentive lies within their control.’

— Richard Lilford, CLAHRC WM Director

Reference:

  1. Friebel R, Steventon A. The multiple aims of pay-for-performance and the risk of unintended consequences. BMJ Qual Saf. 2016.

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

Reference:

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

Accountable Care Organisations

Accountable Care Organisations have been introduced in many settings in the USA. Evaluations are few and far between, but a recent overview [1] finds that while they do not save money, they are associated with improved processes of care (e.g. increased rates of cancer screening), and intermediate outcomes (e.g. HbA1c and blood pressure in people with diabetes). Attempts to create something similar in the UK by merging hospital and primary care budgets are underway in England, notably in Manchester. Before and after studies, such as those typically used in evaluations, are prone to exaggerate effectiveness of quality improvement initiatives,[2] thanks to the rising tide phenomenon.[3] Moreover, merging budgets is not the only way to improve coordination of care across providers, as discussed in a previous post.[4] That said, merged budgets do align provider financial incentives with patient need and core professional values, and we have not reached the end of history on this topic – not nearly.

— Richard Lilford, CLAHRC WM Director

References:

  1. Song Z, Fisher ES. The ACO Experiment in Infancy – Looking Back and Looking Forward. JAMA. 2016; 316(7): 705-6.
  2. Eccles M, Grimshaw J, Campbell M, Ramsay C. Research designs for studies evaluating the effectiveness of change and improvement strategies. Qual Saf Health Care. 2003; 12: 47-52.
  3. Chen YF, Hemming K, Stevens AJ, Lilford RJ. Secular trends and evaluation of complex interventions: the rising tide phenomenon. BMJ Qual Saf. 2015. [ePub].
  4. Lilford RJ. Polycentric Organisations. NIHR CLAHRC West Midlands. 25 July 2014.