Sam Watson’s journal round-up for 6th March 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.

It’s good to be first: order bias in reading and citing NBER working papers. The Review of Economics and Statistics [RePEcPublished 23rd February 2017

Each week one of the authors at this blog choose three or four recently published studies to summarise and briefly discuss. Making this choice from the many thousands of articles published every week can be difficult. I browse those journals that publish in my area and search recently published economics papers on PubMed and Econlit for titles that pique my interest. But this strategy is not without its own flaws as this study aptly demonstrates. When making a choice among many alternatives, people aren’t typically presented with a set of choices, rather a list. This arises in healthcare as well. In an effort to promote competition, at least in the UK, patients are presented with a list of possible of providers and some basic information about those providers. We recently covered a paper that explored this expansion of choice ‘sets’ and investigated its effects on quality. We have previously criticised the use of such lists. People often skim these lists relying on simple heuristics to make choices. This article shows that for the weekly email of new papers published by the National Bureau of Economic Research (NBER), being listed first leads to an increase of approximately 30% in downloads and citations, despite the essentially random ordering of the list. This is certainly not the first study to illustrate the biases in human decision making, but it shows that this journal round-up may not be a fair reflection of the literature, and providing more information about healthcare providers may not have the impact on quality that might be hypothesised.

Economic conditions, illicit drug use, and substance use disorders in the United States. Journal of Health Economics [PubMed] Published March 2017

We have featured a large number of papers about the relationship between macroeconomic conditions and health and health-related behaviours on this blog. It is certainly one of the health economic issues du jour and one we have discussed in detail. Generally speaking, when looking at an aggregate level, such as countries or states, all-cause mortality appears to be pro-cyclical: it declines in economic downturns. Whereas an examination at individual or household levels suggest unemployment and reduced income is generally bad for health. It is certainly possible to reconcile these two effects as any discussion of Simpson’s paradox will reveal. This study takes the aggregate approach to looking at US state-level unemployment rates and their relationship with drug use. It’s relevant to the discussion around economic conditions and health; the US has seen soaring rates of opiate-related deaths recently, although whether this is linked to the prevailing economic conditions remains to be seen. Unfortunately, this paper predicates a lot of its discussion about whether there is an effect on whether there was statistical significance, a gripe we’ve contended with previously. And there are no corrections for multiple comparisons, despite the well over 100 hypothesis tests that are conducted. That aside, the authors conclude that the evidence suggests that use of ecstasy and heroin is procyclical with respect to unemployment (i.e increase with greater unemployment) and LSD, crack cocaine, and cocaine use is counter-cyclical. The results appear robust to the model specifications they compare, but I find it hard to reconcile some of the findings with the prior information about how people actually consume drugs. Many drugs are substitutes and/or compliments for one another. For example, many heroin users began using opiates through abuse of prescription drugs such as oxycodone but made the switch as heroin is generally much cheaper. Alcohol and marijuana have been shown to be substitutes for one another. All of this suggesting a lack of independence between the different outcomes considered. People may also lose their job because of drug use. Taken all together I remain a little sceptical of the conclusions from the study, but it is nevertheless an interesting and timely piece of research.

Child-to-adult neurodevelopmental and mental health trajectories after early life deprivation: the young adult follow-up of the longitudinal English and Romanian Adoptees study. The Lancet [PubMedPublished 22nd February 2017

Does early life deprivation lead to later life mental health issues? A question that is difficult to answer with observational data. Children from deprived backgrounds may be predisposed to mental health issues, perhaps through familial inheritance. To attempt to discern whether deprivation in early life is a cause of mental health issues this paper uses data derived from a cohort of Romanian children who spent time in one of the terribly deprived institutions of Ceaușescu’s Romania and who were later adopted by British families. These institutions were characterised by poor hygiene, inadequate food, and lack of social or educational stimulation. A cohort of British adoptees was used for comparison. For children who spent more than six months in one of the deprived institutions, there was a large increase in cognitive and social problems in later life compared with either British adoptees or those who spent less than six months in an institution. The evidence is convincing, with differences being displayed across multiple dimensions of mental health, and a clear causal mechanism by which deprivation acts. However, for this and many other studies that I write about on this blog, a disclaimer might be needed when there is significant (pun intended) abuse and misuse of p-values. Ziliak and McClosky’s damning diatribe on p-values, The Cult of Statistical Significance, presents examples of lists of p-values being given completely out of context, with no reference to the model or hypothesis test they are derived from, and with the implication that they represent whether an effect exists or not. This study does just that. I’ll leave you with this extract from the abstract:

Cognitive impairment in the group who spent more than 6 months in an institution remitted from markedly higher rates at ages 6 years (p=0·0001) and 11 years (p=0·0016) compared with UK controls, to normal rates at young adulthood (p=0·76). By contrast, self-rated emotional symptoms showed a late onset pattern with minimal differences versus UK controls at ages 11 years (p=0·0449) and 15 years (p=0·17), and then marked increases by young adulthood (p=0·0005), with similar effects seen for parent ratings. The high deprivation group also had a higher proportion of people with low educational achievement (p=0·0195), unemployment (p=0·0124), and mental health service use (p=0·0120, p=0·0032, and p=0·0003 for use when aged <11 years, 11–14 years, and 15–23 years, respectively) than the UK control group.



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.


Chris Sampson’s journal round-up for 3rd 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.

Using discrete choice experiments with duration to model EQ-5D-5L health state preferences: testing experimental design strategies. Medical Decision Making [PubMedPublished 28th September 2016

DCEs are a bit in vogue for the purpose of health state valuation, so it was natural that EuroQol turned to it for valuation of the EQ-5D-5L. But previous valuation studies have highlighted challenges  associated with this approach, some of which this paper now investigates. Central to the use of DCE in this way is the inclusion of a duration attribute to facilitate anchoring from 1 to dead. This study looks at the effect of increasing the options when it comes to duration, as previous studies were limited in this regard. In this study, possible durations were 6 months or 1, 2, 4, 7 or 10 years. 802 online survey respondents we presented with 10 DCE choice sets, and the resulting model had generally logically ordered coefficients. So the approach looks feasible, but it isn’t clear whether or not there are any real advantages to including more durations. Another issue is that the efficiency of the DCE design might be improved by introducing prior information from previous studies to inform the selection of health profiles – that is, by introducing non-zero prior values. With 800 respondents, this design resulted in more disordering with – for example – a positive coefficient on level 2 for the pain/discomfort dimension. This was not the expected result. However, the design included a far greater proportion of more difficult choices, which the authors suggest may have resulted in inconsistencies. An alternative way of increasing efficiency might be to use a 2-stage approach, whereby health profiles are selected and then durations are selected based on information from previous studies. Using the same number of pairs but a sample half the size (400), the 2-stage design seemed to work a treat. It’s a promising design that will no doubt see further research in this context.

Is the distribution of care quality provided under pay-for-performance equitable? Evidence from the Advancing Quality programme in England. International Journal for Equity in Health [PubMedPublished 23rd September 2016

Suppose a regional health care quality improvement initiative worked, but only for the well-off. Would we still support it? Maybe not, so it’s important to uncover for whom the policy is working. QOF is the most-studied pay-for-performance programme in England and it does not seem to have reduced health inequalities in the context of primary care. There is less evidence regarding P4P in hospital care, which is where this study comes in by looking at the Advancing Quality initiative across five different health conditions. Using individual-level data for 73,002 people, the authors model the probability of receiving a quality indicator according to income deprivation in their local area. There were 23 indicators altogether, across which the results were not consistent. Poorer patients were more likely to receive pre-surgical interventions for hip and knee replacements and for coronary artery bypass grafting (CABG). And poorer people were less likely to receive advice at discharge. On the other hand, for hip and knee replacement and CABG, richer people were more likely to receive diagnostic tests. The main finding is that there is no obvious systematic pro-poor or pro-rich bias in the effects of this pay-for-performance initiative in secondary care. This may not be a big surprise due to the limited amount of self-selection and self-direction for patients in secondary care, compared with primary care.

The impact of social security income on cognitive function at older ages. American Journal of Health Economics [RePEc] Published 19th September 2016

Income correlates with health, as we know. But it’s useful to be more specific – as this article is – in order to inform policy. So does more social security income improve cognitive function at older ages? The short answer is yes. And that wasn’t a foregone conclusion as there is some evidence that higher income leads to earlier retirement, which in turn can be detrimental to cognitive function. In this study the authors use changes in the Social Security Act in the US in the 1970s. Between 1972 and 1977, Congress messed up a bit and temporarily introduced a policy that made payments increase at a rate faster than inflation, which was therefore enjoyed by people born between 1910 and 1916, with a 5 year gradual transition until 1922. Unsurprisingly, this study follows many others that have made the most of this policy quirk. Data are taken from a longitudinal survey of older people, which includes a set of scores relating to cognition, with a sample of 4139 people. Using an OLS model, the authors estimate the association between Social Security income and cognition. Cognition is measured using a previously developed composite score with 3 levels: ‘normal’, ‘cognitively impaired’ and ‘demented’. To handle the endogeneity of income, an instrumental variable is constructed on the basis of year of birth to tie-in with the peak in benefit from the policy (n=673). In today’s money the beneficiary cohort received around $2000 extra. It’s also good to see the analysis extended to a quantile regression to see whereabouts in the cognition score distribution effects accrue. The additional income resulted in improvements in working memory, knowledge, languages and orientation and overall cognition. The effects are strong and clinically meaningful. A $1000 (in 1993 prices) increase in annual income lead to a 1.9 percentage point reduction in the likelihood of being classified as cognitively impaired. The effect is strongest for those with higher levels of cognition. The key take-home message here is that even in older populations, policy changes can be beneficial to health. It’s never too late.