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#HEJC for 01/04/2013 (new time!)

This month’s meeting will take place Monday 1st April, at 5pm London time. That’ll be 6pm in Cape Town and 7pm in Riga. Join the Facebook event here. We’ll also hold an antipodal meeting on Tuesday 2nd April, at 5am London time. That’ll be 2pm in Brisbane and 9pm on Monday in Seattle. Join the Facebook event here. For more information about the Health Economics Twitter Journal Club and how to take part, click here.

The paper for discussion this month is a working paper published by the Research Institute of Industrial Economics in Sweden. The authors are Sara Fogelberg and Jonas Karlsson. The title of the paper is:

“Competition and antibiotics prescription”

Following the meeting, a transcript of the discussion can be downloaded here.

Links to the article

Direct: http://www.ifn.se/wfiles/wp/wp949.pdf

RePEc: http://ideas.repec.org/p/hhs/iuiwop/0949.html

Other: tbc

Summary of the paper

Antibiotics resistance is an increasingly apparent problem in medicine, with the prevalence of multi-resistant bacteria on the rise. Over-prescription of antibiotics has short- and long-term implications for public health. Furthermore, there is much debate about the role of competition in healthcare provision. This paper investigates the effect of increased competition between healthcare providers on the prescription of antibiotics. The authors hypothesise that, as a result of increased competition, doctors may be inclined to prescribe more antibiotics in order to meet patients’ demand. The study makes use of a natural experiment where competition-inducing reform was implemented in different counties in Sweden at different points in time during 2007 to 2010. The dataset contains monthly data on all prescribed antibiotics in Sweden, including those defined as narrow spectrum and broad spectrum antibiotics. The authors implement a difference in differences model. The results indicate that increased competition had a positive and significant effect on antibiotics prescription.

Discussion points

  • What is the significance of Swedish reimbursement processes?
  • What does this study tell us about patients’ and doctors’ preferences for antibiotics?
  • What are the implications for the UK and other countries?
  • How can this study inform the debate about competition in healthcare?
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Posted by on March 25, 2013 in #HEJC

 

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Some thoughts on evidence-based policy

I’m currently reading Les Mis (I have been for about 2 years – it’s half a million words long). A few months ago, Hugo described economists to me as “geologists of politics” (géologues de la politique). A pretty smart observation for 1862. It reminded me of a slightly more recent quip by Oswald Falk; telling his friend John Maynard Keynes that all he had really done was codify “the moral feeling of an age”.

Economic theory often follows political theory, no doubt, and policy can follow from either. But there are now calls in the UK for ‘evidence’ to enter the equation; most recently in eduction. In regard to economic and public policy, the argument is presumably that the story should go:

political theory > economic theory > evidence > policy.

A loose parallel in medicine might go:

medical theory > treatment > evidence > policy.

In medicine this is usually feasible, as human biology is relatively predictable. It is reasonably clear how medical questions can be answered; usually by randomised controlled trials and epidemiological studies. But is the step from theory to evidence as simple in public policy?

Evidence-based policy

In public policy, the story rarely goes as described above; evidence can fall anywhere in the schema – usually at the end. Evidence is retrospective, while policy is prospective. Human evolution is relatively slow, and what a drug does to a person now it is likely to do in 12 months’ time. Evidence collected in a trial is therefore largely applicable in the future. The same cannot be said for economies and societies. Evidence becomes heavily dependent on projections of what will happen in the future, and we (economists, humans) are notoriously bad at making predictions.

Evidence-based medicine (future edition)

Medicine is less dependent on projections, so evidence-based medicine is usually a safe bet. However, with the rise of personalised medicine, evidence-based medicine as we know it could be off the table. In personalised medicine, n=1. It won’t be possible to stratify trials by the four quadrillion different human genetic combinations; let alone different socio-economic indicators. Furthermore, some pressing questions are proving to be beyond the scope of evidence and prediction. For example, Richard Smith and Joanna Coast recently highlighted the limitations of evidence in antimicrobial resistance.

I’m all in favour of evidence-based medicine, as I’m not a moron! I’m also in favour of evidence-based policy wherever we can do it. But we need to acknowledge its limitations and avoid hubris whenever we do have ‘evidence’. Health economists live in a very evidence-based world, which is no bad thing, but we mustn’t restrict ourselves to it. We need to consider that, if we can’t find evidence of support for a policy (say, attaching a greater weight to end of life care), it may be that our theory is wrong.

When would the NHS have been created, had we waited for the evidence (or economic theory, for that matter)? How long can we wait for evidence in the case of antimicrobial resistance? In the long run we could all, quite literally, be dead. Sometimes it will be necessary to charge forward with policies that we know are right, but just can’t prove. The economists will add the veneer of theory later.

 

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Cannabis and asbestos: The cost-effectiveness of prohibition as health policy

The aim of a health intervention is generally to cause a cost-effective increase to some normative outcome such as by reducing mortality, increasing productivity and so forth. Often policy makers want to encourage or discourage certain behaviours by using incentives or disincentives. One such way the government may intervene is through prohibition. Often drug prohibition is touted as a health policy intervention to prevent harms both clinical and social. However, it is probable that this form of intervention is not cost-effective.

Let’s distinguish prohibition from other forms of disincentivisation by saying that prohibition does nothing to internalise the externality that harmful behaviours create. A tax on cigarettes disincentivises the consumer into smoking less but the revenue can be used against the negative effects of smoking, it is a Pigouvian tax; whereas putting someone in prison compensates no-one. Admittedly such laws are being reformed to help addicts rehabilitate rather than punish them but these programs are not funded by drug use itself.

One of the most widely discussed prohibitions is against cannabis. (I don’t want to wade into any other arguments than whether it is a successful health policy intervention.) A recently, well-publicised study showed that cannabis use in under 18s was associated with a reduction in IQ of less than 1 point. Firstly, I would argue that this paper does not demonstrate causal effects. The authors used OLS with the outcome as adult IQ minus childhood IQ, and the independent variables were cannabis and other drug use. Without delving too deeply into the discussion, there are potential standard error and endogeneity issues.  Second, this effect is quite small. But, other studies show that cannabis is also associated with an approximate 40% increase in the risk of psychosis. Prohibiting it may be a good way of intervening to prevent these negative effects. But what are the costs?

A report suggests that the cost of policing cannabis in the UK is about £500m annually. On top of this there is a possible opportunity cost in not legalising it of about £6.4b from lost revenue. So what is the cost-effectiveness of prohibition in this case? The current prevalence of psychotic disorders is about 5 in 1,000 in the UK. If everyone used cannabis then this could increase to 6 in 1,000 in the worst case that would be around 60,000 cases of psychosis which may equate to a loss of 30,000 QALYs (based on a QALY of 0.475).  This incredibly crude calculation yields a cost per QALY of about £250,000/QALY. There may be other benefits, such as modestly increasing the IQ of a small number of people, but that is certainly not going to be enough to justify the costs. And since only a small proportion of the population uses cannabis regularly this value is going to be many times larger, and certainly over £1m/QALY. Clearly it is not cost-effective.

This may be true of other bans as well. An older report by the World Bank in 1994 suggested that the ban in asbestos in the US valued the cost per statistical life saved at about $49m, much more that the standard compensation workers receive for risk, about $5m per statistical life.

I would think that there would be much more effective ways of spending such sums of money in increasing health and safety and protecting the worker or consumer. This could be through taxes or subsidising substitute products or compensating workers better and internalising the externality. This is not an argument for a free market, just a well regulated one that uses cost-effectiveness policies more effectively.

 
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Posted by on September 21, 2012 in Economic Evaluation, Public Health

 

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