Alastair Canaway’s journal round-up for 10th July 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.

Use-of-time and health-related quality of life in 10- to 13-year-old children: not all screen time or physical activity minutes are the same. Quality of life Research [PubMedPublished 3rd July 2017

“If you watch too much TV, it’ll make your eyes square” – something I heard a lot as a child. This first paper explores whether this is true (sort of) by examining associations between aspects of time use and HRQL in children aged 10-13 (disclaimer: I peer reviewed it and was pleased to see them incorporate my views). This paper aims to examine how different types of time use are linked to HRQL. Time use was examined by the Multimedia Activity Recall for Children and Adolescents (MARCA) which separates out time into physical activity (sport, active transport, and play), screen time (TV, videogames, computer use), and sleep. The PedsQL was used to assess HRQL, whilst dual x-ray absorptiometry was used to accurately assess fatness. There were a couple of novel aspects to this study, first, the use of absorptiometry to accurately measure body fat percentage rather than the problematic BMI/skin folds in children; second, separating time out into specific components rather than just treating physical activity or screen time as homogeneous components. The primary findings were that for both genders, fatness (negative), sport (positive) and development stage (negative) were associated with HRQL. For boys, the most important other predictor of HRQL was videogames (negative) whilst predictors for girls included television (negative), active transport (negative) and household income (positive). With the exception of ‘active travel’ for girls, I don’t think any of these findings are particularly surprising. As with all cross-sectional studies of this nature, the authors give caution to the results: inability to demonstrate causality. Despite this, it opens the door for various possibilities for future research, and ideas for shaping future interventions in children this age.

Raise the bar, not the threshold value: meeting patient preferences for palliative and end-of-life care. PharmacoEconomics – Open Published 27th June 2017

Health care ≠ end of life care. Whilst health care seeks to maximise health, can the same be said for end of life care? Probably not. This June saw an editorial elaborating on this issue. Health is an important facet of end of life care. However, there are other substantial objects of value in this context e.g. preferences for place of care, preparedness, reducing family burdens etc. Evidence suggests that people at end of life can value these ‘other’ objects more than health status or life extension. Thus there is value beyond that captured by health. This is an issue for the QALY framework where health and length of life are the sole indicators of benefit. The editorial highlights that this is not people wishing for higher cost-per-QALY thresholds at end of life, instead, it is supporting the valuation of key elements of palliative care within the end of life context. It argues that palliative care interventions often are not amenable to integration with survival time in a QALY framework, this effectively implies that end of life care interventions should be evaluated in a separate framework to health care interventions altogether. The editorial discusses the ICECAP-Supportive Care Measure (designed for economic evaluation of end of life measures) as progress within this research context. An issue with this approach is that it doesn’t address allocative efficiency issues (and comparability) with ‘normal’ health care interventions. However, if end of life care is evaluated separately to regular healthcare, it will lead to better decisions within the EoL context. There is merit to this justification, after all, end of life care is often funded via third parties and arguments could, therefore, be made for adopting a separate framework. This, however, is a contentious area with lots of ongoing interest. For balance, it’s probably worth pointing out Chris’s (he did not ask me to put this in!) book chapter which debates many of these issues, specifically in relation to defining objects of value at end of life and whether the QALY should be altogether abandoned at EoL.

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis. European Journal of Health Economics [PubMedPublished 24th June 2017

Payment systems that incentivise cost control and quality improvements are increasingly used. In England, until recently, mental health services have been funded via block contracts that do not necessarily incentivise cost control and payment has not been linked to outcomes. The National Tariff Payment System for reimbursement has now been introduced to mental health care. This paper harnesses the MHMDS (now called MHSDS) using multi-level bivariate regression to investigate whether it is possible to control costs without negatively affecting outcomes. It does this by examining the relationship between costs and outcomes for mental health providers. Due to the nature of the data, an appropriate instrumental variable was not available, and so it is important to note that the results do not imply causality. The primary results found that after controlling for key variables (demographics, need, social and treatment) there was a minuscule negative correlation between residual costs and outcomes with little evidence of a meaningful relationship. That is, the data suggest that outcome improvements could be made without incurring a lot more cost. This implies that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment systems. Something to bear in mind when interpreting the results is that there was a rather large list of limitations associated with the analysis, most notably that the analysis was conducted at a provider level. Although it’s continually improving, there still remain issues with the MHMDS data: poor diagnosis coding, missing outcome data, and poor quality of cost data. As somebody who is yet to use MHMDS data, but plans to in the future, this was a useful paper for generating ideas regarding what is possible and the associated limitations.

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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.

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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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