Sam Watson’s journal round-up for 30th October 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.

Conditional cash transfers: the case of Progresa/OportunidadesJournal of Economic Literature [RePEc] Published September 2017

The Progresa/Oportunidades programme was instigated in Mexico in 1995. The main innovation of the programme was a series of cash payments conditional on various human capital investments in children, such as regular school attendance and health check-ups. Beginning principally in rural areas, it expanded to urban areas in 2000-1. Excitingly for researchers, randomised implementation of the programme was built into its rollout, permitting evaluation of its effectiveness. Given it was the first such programme in a low- or middle-income country to do this, there has been a considerable amount of analysis and literature published on the topic. This article provides an in-depth review of this literature – incorporating over one hundred articles from economics and health journals. I’ll just focus on the health-related aspects of the review rather than education, labour market, or nutrition outcomes, but they’re also worth a look. The article provides a simple theoretical model about the effects of conditional cash transfers to start with and suggests that they have both a price effect, through reducing the shadow wage of time in activities other than those to which the payment is targeted, and an income effect, by increasing total income. The latter effect is ambiguous in its direction. For health, a large number of outcomes including child mortality and height, behavioural problems, obesity, and depression have all been assessed. For the most part  this has been through health modules applied to a subsample of people in surveys, which may limit the conclusions one can make for reasons such as attrition in the samples of treated and control households. Generally, the programme has demonstrated positive health effects (of varying magnitudes) in both the short and medium terms. Health care utilisation increased and with it there was a reduction in self-reported illness, behavioural problems, and obesity. However, positive effects are not reported universally. For example, one study reported an increase in child height in the short term, but in the medium term little change was reported in height-for-age z-scores in another study, which may suggest children catch-up in their growth. Nevertheless, it seems as though the programme succeeded in its aims, although there remains the question of its cost-benefit ratio and whether these ends could have been achieved more cost-effectively by other means. There is also the political question about the paternalism of the programme. While some political issues are covered, such as the perception of the programme as a vehicle for buying votes, and strategies for mitigating these issues, the issue of its acceptability to poor Mexicans is not well covered.

Health‐care quality and information failure: evidence from Nigeria. Health Economics [PubMedPublished 23rd October 2017

When we conceive of health care quality we often think of preventable harm to patients. Higher quality institutions make fewer errors such as incorrect diagnoses, mistakes with medication, or surgical gaffes. However, determining when an error has been made is difficult and quality is often poorly correlated with typical measures of performance like standardised mortality ratios. Evaluating quality is harder still in resource-poor settings where there are no routine data for evaluation and often an absence of patient records. Patients may also have less knowledge about what constitutes quality care. This may provide an environment for low-quality providers to remain in business as patients do not discriminate on the basis of quality. Patient satisfaction is another important aspect of quality, but not necessarily related to more ‘technical’ aspects of quality. For example, a patient may feel that they’ve not had to wait long and been treated respectfully even if they have been, unbeknownst to them, misdiagnosed and given the wrong medication. This article looks at data from Nigeria to examine whether measures of patient satisfaction are correlated with technical quality such as diagnostic accuracy and medicines availability. In brief, they report that there is little variation in patient satisfaction reports, which may be due to some reporting bias, and that diagnostic accuracy was correlated with satisfaction but other markers of quality were not. Importantly though, the measures of technical quality did little to explain the overall variation in patient satisfaction.

State intimate partner violence-related firearm laws and intimate partner homicide rates in the United States, 1991 to 2015. Annals of Internal Medicine [PubMedPublished 17th October 2017

Gun violence in the United States is a major health issue. Other major causes of death and injury attract significant financial investment and policy responses. However, the political nature of firearms in the US limit any such response. Indeed, a 1996 law passed by Congress forbade the CDC “to advocate or promote gun control”, which a succession of CDC directors has interpreted as meaning no federally funded research into gun violence at all. As such, for such a serious cause of death and disability, there is disproportionately little research. This article (not federally funded, of course) examines the impact of gun control legislation on inter-partner violence (IPV). Given the large proportion of inter-partner homicides (IPH) carried out with a gun, persons convicted of IPV felonies and, since 1996, misdemeanours are prohibited from possessing a firearm. However, there is variation in states about whether those convicted of an IPV crime have to surrender a weapon already in their possession. This article examines whether states that enacted ‘relinquishment’ laws that force IPV criminals to surrender their weapons reduced the rate of IPHs. They use state-level panel data and a negative binomial fixed effects model and find that relinquishment laws reduced the risk of IPHs by around 10% and firearm-related IPH by around 15%.

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Sam Watson’s journal round-up for 23rd 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.

Short-term and long-term effects of GDP on traffic deaths in 18 OECD countries, 1960–2011. Journal of Epidemiology and Community Health [PubMedPublished February 2017

Understanding the relationships between different aspects of the economy or society in the aggregate can reveal to us knowledge about the world. However, they are more complicated than analyses of individuals who either did or did not receive an intervention, as the objects of aggregate analyses don’t ‘exist’ per se but are rather descriptions of average behaviour of the system. To make sense of these analyses an understanding of the system is therefore required. On these grounds I am a little unsure of the results of this paper, which estimates the effect of GDP on road traffic fatalities in OECD countries over time. It is noted that previous studies have shown that in the short-run, road traffic deaths are procyclical, but in the long-run they have declined, likely as a result of improved road and car safety. Indeed, this is what they find with their data and models. But, what does this result mean in the long-run? Have they picked up anything more than a correlation with time? Time is not included in the otherwise carefully specified models, so is the conclusion to policy makers, ‘just keep doing what you’re doing, whatever that is…’? Models of aggregate phenomena can be among the most interesting, but also among the least convincing (my own included!). That being said, this is better than most.

Sources of geographic variation in health care: Evidence from patient migration. Quarterly Journal of Economics [RePEcPublished November 2016

There are large geographic differences in health care utilisation both between countries and within countries. In the US, for example, the average Medicare enrollee spent around $14,400 in 2010 in Miami, Florida compared with around $7,800 in Minneapolis, Minnesota, even after adjusting for demographic differences. However, higher health care spending is generally not associated with better health outcomes. There is therefore an incentive for policy makers to legislate to reduce this disparity, but what will be effective depends on the causes of the variation. On one side, doctors may be dispensing treatments differently; for example, we previously featured a paper looking at the variation in overuse of medical testing by doctors. On the other side, patients may be sicker or have differing preferences on the intensity of their treatment. To try and distinguish between these two possible sources of variation, this paper uses geographical migration to look at utilisation among people who move from one area to another. They find that (a very specific) 47% of the difference in use of health care is attributable to patient characteristics. However, I (as ever) remain skeptical: a previous post brought up the challenge of ‘transformative treatments’, which may apply here as this paper has to rely on the assumption that patient preferences remain the same when they move. If moving from one city to another changes your preferences over healthcare, then their identification strategy no longer works well.

Seeing beyond 2020: an economic evaluation of contemporary and emerging strategies for elimination of Trypanosoma brucei gambiense. Lancet Global Health Published November 2016

African sleeping sickness, or Human African trypanosomiasis, is targeted for eradication in the next decade. However, the strategy to do so has not been determined, nor whether any such strategy would be a cost-effective use of resources. This paper aims to model all of these different strategies to estimate incremental cost-effectiveness threshold (ICERs). Infectious disease presents an interesting challenge for health economic evaluation as the disease transmission dynamics need to be captured over time, which they achieve here with a ‘standard’ epidemiological model using ordinary differential equations. To reach elimination targets, an approach incorporating case detection, treatment, and vector control would be required, they find.

A conceptual introduction to Hamiltonian Monte Carlo. ArXiv Published 10th January 2017

It is certainly possible to drive a car without understanding how the engine works. But if we want to get more out of the car or modify its components then we will have to start learning some mechanics. The same is true of statistical software. We can knock out a simple logistic regression without ever really knowing the theory or what the computer is doing. But this ‘black box’ approach to statistics has clear problems. How do we know the numbers on the screen mean what we think they mean? What if it doesn’t work or if it is running slowly, how do we diagnose the problem? Programs for Bayesian inference can sometimes seem even more opaque than others: one might well ask what are those chains actually exploring, if it’s even the distribution of interest. Well, over the last few years a new piece of kit, Stan, has become a brilliant and popular tool for Bayesian inference. It achieves fast convergence with less autocorrelation between chains and so it achieves a high effective sample size for relatively few iterations. This is due to its implementation of Hamiltonian Monte Carlo. But it’s founded in the mathematics of differential geometry, which has restricted the understanding of how it works to a limited few. This paper provides an excellent account of Hamiltonian Monte Carlo, how it works, and when it fails, all replete with figures. While it’s not necessary to become a theoretical or computational statistician, it is important, I think, to have a grasp of what the engine is doing if we’re going to play around with it.

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Brent Gibbons’s journal round-up for 12th December 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.

As the U.S. moves into a new era with the recent election results, Republicans will have a chance to modify or repeal the Affordable Care Act. The Affordable Care Act (ACA), also called Obamacare, is a comprehensive health reform that was enacted on the 23rd of March, 2010, that helped millions of uninsured individuals and families gain coverage through new private insurance coverage and through expanded Medicaid coverage for those with very low income. The ACA has been nothing short of controversial and has often been at the forefront of partisan divides. The ACA was an attempt to fill the insurance coverage gaps of the patchwork American health insurance system that was built on employer-sponsored insurance (ESI) and a mix of publicly funded programs for various vulnerable subpopulations. The new administration and republican legislators are promising to repeal the law, at least in part, and have suggested plans that will re-emphasize the private insurance model based on ESI. For this reason, the following articles selected for this week’s round-up highlight different aspects of ESI.

The Mental Health Parity and Addiction Equity Act evaluation study: Impact on specialty-behavioral health utilization and expenditures among “carve-out” enrollees. Journal of Health Economics [PubMed] Published December 2016

Behavioral health services have historically been covered at lower levels and with more restrictions by ESI than physical health services. Advocates for behavioral health system reform have pushed for equal coverage of behavioral health services for decades. In 2008, the Mental Health Parity and Addiction Equity Act (MHPAEA) was passed with a fairly comprehensive set of rules for how behavioral health coverage would need to be comparable to medical/surgical coverage, including for ESI. This first article in our round-up examines the impact of this law on utilization and expenditures of behavioral health services in ESI plans. The authors use an individual-level interrupted time series design using panel data with monthly measures of outcomes. Administrative claims and enrollment data are used from a large private insurance company that provides health insurance for a number of large employers in the years 2008 – 2013. A segmented regression analysis is used in order to measure the impact of the law at two different time points, first in 2010 for what is considered a transition year, and then in the 2011 – 2013 period, both compared to the pre-MHPAEA time period, 2008 – 2009. Indicator variables are used for the different periods as well as spline variables to measure the change in level and slope of the time trends, controlling for other explanatory variables. Results suggest that MHPAEA had little effect on utilization and total expenditures, but that out-of-pocket expenditures were shifted from the patient to the health plan. For patients who had positive expenditures, there was a post-MHPAEA level increase in health plan expenditures of $58.03 and a post-MHPAEA level decrease in out-of-pocket expenditure of $21.58, both per-member-per-month. To address worries of confounding time trends, the authors performed several sensitivity analyses, including a difference-in-difference (DID) analysis that used states that already had strict parity legislation as a comparison population. The authors also examined those with a bipolar or schizophrenia disorder to test the hypothesis that impacts may be stronger for individuals with more severe conditions. Sensitivity analyses tended to result in larger p-values. These results, which were examined at the mean, are consistent with reports that the primary change in behavioral health coverage in ESI was the elimination of treatment limits. In addition to using a sensitivity analysis with individuals with bipolar and schizophrenia, it would have been interesting to see impacts for individuals defined as “high-utilizers”. It would also have been nice to see a longer pre-MHPAEA time period since insurers could have adjusted plans prior to the 2010 effective date.

Health plan type variations in spells of health-care treatment. American Journal of Health Economics [RePEcPublished 12th October 2016

Health care costs in the U.S. were roughly 17.8 percent of the GDP in 2015 and attempts to rein in health insurance costs have largely proved elusive. Different private insurance health plans have tried to rein in costs through different plan types that have a mix of supply-side mechanisms and demand-side mechanisms. Two recent plan types that have emerged are exclusive provider organizations (EPOs) and consumer-driven/high-deductible health plans (CDHPs). EPOs use a more narrowly restricted network of providers that agree to lower payments and presumably also deliver quality care while CDHPs give patients broader networks but shift cost-sharing to patients. EPOs therefore are more focused on supply-side mechanisms of cost reduction, while CDHPs emphasize demand-side incentives to reduce costs. Ellis and Zhu use a large ESI claims-based dataset to examine the impact of these two health plan types and to try to answer whether supply-side or demand-side mechanisms of cost reduction are more effective. The authors present an extremely extensive analysis that is really worth reading. They use a technique for modeling periods of care, called treatment “spells” that is a mix of monthly treatment periods and episode-based models of care. Utilization and expenditures are examined in the context of these treatment “spells” for the different health plan types. A 2SLS regression model is used that controls for endogenous plan choice in the first-stage. The predicted probabilities from plan choice are used as an instrument in the second stage along with a number of controls, including risk-adjustment techniques and individual fixed effects. The one drawback in using the predicted probabilities as the sole instrument is it is not possible to perform an exclusion test. The results, however, suggest that neither of the new plan types performs better than a standardly used health plan. EPOs have the lowest overall spending, but are not significantly different than the standard plan type, and CDHPs have 16 percent higher spending than the standard plan type. The CDHPs in particular have not been studied carefully and these results suggest that previous research on CDHPs found cost-savings due to younger and healthier patients and not because of plan type effects. There are also worries with high deductible plans that patients may elect to forgo necessary healthcare services.

The financial burdens of high-deductible plans. Health Affairs [PubMed] Published December 2016

Having discussed the consumer-directed/high deductible health plans, this third journal article looks at the Medical Expenditure Panel Survey (MEPS) data to examine the burden high deductible health plans place on individuals and families with low incomes. High deductible health plans like the CDHPs are increasingly offered. High deductible plans are sometimes paired with the option to use a flexible spending account (FSA). An FSA gives the patient the option to set aside money from her salary or paycheck that can only be used for healthcare costs, with the benefit that the money set aside will not be subject to various income taxes. The benefit of the high deductible plan is supposed to be lower premiums and the possibility of saving money through the FSA, if that option is available. Yet descriptive analyses using MEPS data from 2011 – 2013 from ESI plans show that high deductible plans impose a particularly high burden on individuals with family incomes below 250 percent of the poverty line. Specifically, the authors found that 29.1 percent of individuals with high deductible plans had financial costs exceeding 20 percent of family income, compared to 20.6 percent of individuals with low deductible plans. For individuals with family income greater than 400 percent of the poverty line, financial burden was not different for high deductible plans compared to other plan types. Yet worryingly, individuals with low incomes were just as likely to have high deductible plans as individuals with high incomes.

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