Chris Sampson’s journal round-up for 16th January 2017

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Competition and quality indicators in the health care sector: empirical evidence from the Dutch hospital sector. The European Journal of Health Economics [PubMed] Published 3rd January 2017

In case you weren’t already convinced, this paper presents more evidence to support the notion that (non-price) competition between health care providers is good for quality. The Dutch system is based on compulsory insurance and information on quality of hospital care is made public. One feature of the Dutch health system is that – for many elective hospital services – prices are set following a negotiation between insurers and hospitals. This makes the setting of the study a bit different to some of the European evidence considered to date, because there is scope for competition on price. The study looks at claims data for 3 diagnosis groups – cataract, adenoid/tonsils and bladder tumor – between 2008 and 2011. The authors’ approach to measuring competition is a bit more sophisticated than some other studies’ and is based on actual market share. A variety of quality indicators are used for the 3 diagnosis groups relating mainly to the process of care (rather than health outcomes). Fixed and random effects linear regression models are used to estimate the impact of market share upon quality. Casemix was only controlled for in relation to the proportion of people over 65 and the proportion of women. Where a relationship was found, it tended to be in favour of lower market share (i.e. greater competition) being associated with higher quality. For cataract and for bladder tumor there was a ‘significant’ effect. So in this setting at least, competition seems to be good news for quality. But the effect sizes are neither huge nor certain. A look at each of the quality indicators separately showed plenty of ‘non-significant’ relationships in both directions. While a novelty of this study is the liberalised pricing context, the authors find that there is no relationship between price and quality scores. So even if we believe the competition-favouring results, we needn’t abandon the ‘non-price competition only’ mantra.

Cost-effectiveness thresholds in global health: taking a multisectoral perspective. Value in Health Published 3rd January 2017

We all know health care is not the only – and probably not even the most important – determinant of health. We call ourselves health economists, but most of us are simply health care economists. Rarely do we look beyond the domain of health care. If our goal as researchers is to help improve population health, then we should probably be allocating more of our mental resource beyond health care. The same goes for public spending. Publicly provided education might improve health in a way that the health service would be willing to fund. Likewise, health care might improve educational attainment. This study considers resource allocation decisions using the familiar ‘bookshelf approach’, but goes beyond the unisectoral perspective. The authors discuss a two-sector world of health and education, and demonstrate the ways in which there may be overlaps in costs and outcomes. In short, there are likely to be situations in which the optimal multisectoral decision would be for individual sectors to increase their threshold in order to incorporate the spillover benefits of an intervention in another sector. The authors acknowledge that – in a perfect world – a social-welfare-maximising government would have sufficient information to allocate resources earmarked for specific purposes (e.g. health improvement) across sectors. But this doesn’t happen. Instead the authors propose the use of a cofinancing mechanism, whereby funds would be transferred between sectors as needed. The paper provides an interesting and thought-provoking discussion, and the idea of transferring funds between sectors seems sensible. Personally I think the problem is slightly misspecified. I don’t believe other sectors face thresholds in the same way, because (generally speaking) they do not employ cost-effectiveness analysis. And I’m not sure they should. I’m convinced that for health we need to deviate from welfarism, but I’m not convinced of it for other sectors. So from my perspective it is simply a matter of health vs everything else, and we can incorporate the ‘everything else’ into a cost-effectiveness analysis (with a societal perspective) in monetary terms. Funds can be reallocated as necessary with each budget statement (of which there seem to be a lot nowadays).

Is the Rational Addiction model inherently impossible to estimate? Journal of Health Economics [RePEc] Published 28th December 2016

Saddle point dynamics. Something I’ve never managed to get my head around, but here goes… This paper starts from the problem that empirical tests of the Rational Addiction model serve up wildly variable and often ridiculous (implied) discount rates. That may be part of the reason why economists tend to support the RA model but at the same time believe that it has not been empirically proven. The paper sets out the basis for saddle point dynamics in the context of the RA model, and outlines the nature of the stable and unstable root within the function that determines a person’s consumption over time. The authors employ Monte Carlo estimation of RA-type equations, simulating panel data observations. These simulations demonstrate that the presence of the unstable root may make it very difficult to estimate the coefficients. So even if the RA model can truly represent behaviour, empirical estimation may contradict it. This raises the question of whether the RA model is essentially untestable. A key feature of the argument relates to use of the model where a person’s time horizon is not considered to be infinite. Some non-health economists like to assume it is, which, as the authors wryly note, is not particularly ‘rational’.

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Sam Watson’s journal round-up for October 24th 2016

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

Mortality decrease according to socioeconomic groups during the economic crisis in Spain: a cohort study of 36 million people. The Lancet [PubMed] Published 13th October 2016

There is no shortage of studies examining the relationship between macroeconomic conditions and population health. Papers have come up on the journal round-up here, here, and here, and we previously discussed economic conditions and baby health. So what does this study add? Using data from the 2011 Spanish census on 36 million individuals, the study compares age-adjusted mortality rates for different socioeconomic groups before and after the economic crisis in Spain. The socioeconomic status of households was classified on the basis of household wealth, household floor space, and number of cars. The study compares the annual change in mortality rates for 2004-7 to the annual percentage change in the post-crisis period 2008-11. In essence the authors are looking for a structural break. The article reports that mortality rates declined faster post-crisis than before and that this effect was more pronounced in low socioeconomic status households. However, this conclusion is based on observed differences in estimated changes of rate: differences between the socioeconomic groups are not directly tested. The authors seem to fall foul of the problem that the difference between “significant” and “not significant” is not itself statistically significant. The plots in the paper illustrate strong differences in age-adjusted mortality rates by socioeconomic status, but a structural break in changes in rates is not so clearly evident. A large econometric literature has arisen around measuring structural breaks in macroeconomic series, many of these methods may have been of use. Indeed, there have been a number of sophisticated and careful analyses of the effect of macroeconomic conditions and health previous published, including the seminal study by Christopher Ruhm. Why this study landed in The Lancet therefore seems somewhat mysterious.

The ambiguous effect of GP competition: the case of hospital admissions. Health Economics [PubMedPublished 14th October 2016

Another mainstay of this blog: competition in healthcare. We’ve covered papers on this topic in previous journal round-ups here and here, and critically discussed a paper on the topic here. It seems to be one of those topics with important implications for healthcare policy but one which becomes less certain the more is known. Indeed, this paper recognises this in its title. The ambiguity to which it refers is the effect of GP competition on hospital admissions: if GPs retain more patients due to increased competition then admissions go down; if they recruit new patients due to increased competition then admissions go up. Typically studies in this area either compare outcomes before and after a pro-competitive policy change, or compare outcomes between areas with different densities (and hence competition) between GPs. This study adopts a variant of the latter approach using the number of open list practices in an area as their proxy for competition. They find that increased competition reduces inpatient attendances and increases outpatient attendances. I’ve often been skeptical of the use of GP density as a proxy for competition. Do people really compare GP practices before choosing them or do they just go to the nearest one? If a person is already registered at one practice, how often do they search around to choose another if care isn’t that bad? An observed effect of a change in GP density could be attributable to entry into or exit from the ‘market’ of differently performing providers, which may have little to do with competition, more the type of GP, GP age, and differences in medical training. Nevertheless, this article does present a well-considered analysis, the difficulty is in the interpretation in light of all the previous studies.

Modeling the economic burden of adult vaccine-preventable diseases in the United States. Health Affairs [PubMed] Published 12th October 2016

Andrew Wakefield, disbarred doctor and disgraced author of the fraudulent Lancet paper on MMR and autism, is currently promoting his new anti-vaccine film. His work and a cabal of conspiracy theorists have led many parents to refuse to get their children vaccinated. All this despite vaccines being one of the safest and most cost-effective of health interventions. This new paper seeks to determine the economic burden of vaccine-preventable diseases is in the US. The diseases considered include hepatitis A and B; measles, mumps, and rubella; and shingles (herpes zoster). Epidemiological models were developed in conjunction with experts; economic costs were assessed using both cost-of-illness and full income methodologies; and, parameters were specified on the basis of a literature review. Taking into account healthcare costs and productivity losses, the burden of the considered diseases was estimated at $9 billion annually. The authors also discuss taking into account social welfare losses using the value of a statistical life, however I think I may be misinterpreting the results when it states

The current-dollar value of statistical life calculated from each source was $5.9 billion from the FDA; $6.3 billion from the NHTSA; and $8.3 billion from the EPA. The full income value of death as a result of vaccine-preventable diseases is estimated to be $176 billion annually (plausibility range: $166 billion–$231 billion).

That seems way too large to me so I’m not sure what to make of that. Nevertheless, the study illustrates the potentially massive burden that vaccine-preventable diseases may present.

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Sam Watson’s journal round-up for 10th October 2016

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

This week’s journal round up-is a special edition featuring a series of papers on health econometrics published in this month’s issue of the Journal of the Royal Statistical Society: Series A.

Healthcare facility choice and user fee abolition: regression discontinuity in a multinomial choice setting. JRSS: A [RePEcPublished October 2016

Charges for access to healthcare – user fees – present a potential barrier to patients in accessing medical services. User fees were touted in the 1980s as a way to provide revenue for healthcare services in low and middle income countries, improve quality, and reduce overuse of limited services. However, a growing evidence base suggests that user fees do not achieve these ends and reduce uptake of preventative and curative services. This article seeks to provide new evidence on the topic using a regression discontinuity (RD) design while also exploring the use of RD with multinomial outcomes. Based on South African data, the discontinuity of interest is that children under the age of six are eligible for free public healthcare whereas older children must pay a fee; user fees for the under sixes were abolished following the end of apartheid in 1994. The results provide evidence that removal of user fees resulted in more patients using public healthcare facilities than costly private care or care at home. The authors describe how their non-parametric model performs better, in terms of out-of-sample predictive performance, than the parametric model. And when the non-parametric model is applied to examine treatment effects across income quantiles we find that the treatment effect is among poorer families and that it is principally due to them switching between home care and public healthcare. This analysis supports an already substantial literature on user fees, but a literature that has previously been criticised for a lack of methodological rigour, so this paper makes a welcome addition.

Do market incentives for hospitals affect health and service utilization?: evidence from prospective pay system–diagnosis-related groups tariffs in Italian regions. JRSS: A [RePEcPublished October 2016

The effect of pro-market reforms in the healthcare sector on hospital quality is a contentious and oft-discussed topic, not least due to the difficulties with measuring quality. We critically discussed a recent, prominent paper that analysed competitive reforms in the English NHS, for example. This article examines the effect of increased competition in Italy on health service utlisation: in the mid 1990s the Italian national health service moved from a system of national tariffs to region-specific tariffs in order for regions to better incentivise local health objectives and reflect production costs. For example, the tariffs for a vaginal delivery ranged from €697 to €1,750 in 2003. This variation between regions and over time provides a source of variation to analyse the effects of these reforms. The treatment is defined as a binary variable at each time point for whether the regions had switched from national to local tariffs, although one might suggest that this disposes of some interesting variation in how the policy was enacted. The headline finding is that the reforms had little or no effect on health, but did reduce utilisation of healthcare services. The authors interpret this as suggesting they reduce over-utilisation and hence improve efficiency. However, I am still pondering how this might work: presumably the marginal benefit of treating patients who do not require particular services is reduced, although the marginal cost of treating those patients who do not need it is likely also to be lower as they are healthier. The between-region differences in tariffs may well shed some light on this.

Short- and long-run estimates of the local effects of retirement on health. JRSS: A [RePEcPublished October 2016

The proportion of the population that is retired is growing. Governments have responded by increasing the retirement age to ensure the financial sustainability of pension schemes. But, retirement may have other consequences, not least on health. If retirement worsens one’s health then delaying the retirement age may improve population health, and if retirement is good for you, the opposite may occur. Retirement grants people a new lease of free time, which they may fill with health promoting activities, or the loss of activity and social relations may adversely impact on ones health and quality of life. In addition, people who are less healthy may be more likely to retire. Taken all together, estimating the effects of retirement on health presents an interesting statistical challenge with important implications for policy. This article uses the causal inference method du jour, regression discontinuity design, and the data are from that workhorse of British economic studies, the British Household Panel Survey. The discontinuity is obviously the retirement age; to deal with the potential reverse causality, eligibility for the state pension is used as an instrument. Overall the results suggest that the short term impact on health is minimal, although it does increase the risk of a person becoming sedentary, which in the long run may precipitate health problems.

 

Other articles on health econometrics in this special issue:

The association between asymmetric information, hospital competition and quality of healthcare: evidence from Italy.

This paper finds evidence that increased between hospital competition does not lead to improved outcomes as patients were choosing hospitals on the basis of information from their social networks. We featured this paper in a previous round-up.

A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs.

This article considers the problem of modelling non-normally distributed healthcare costs data. Linear models with square root transformations and generalised linear models with square root link functions are found to perform the best.

Phantoms never die: living with unreliable population data.

Not strictly health econometrics, more demographics, this article explores how to make inferences about population mortality rates and trends when there are unreliable population data due to fluctuations in birth patterns. For researchers using macro health outcomes data, such corrections may prove useful.

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